SAA-C03 AWS Certified Solutions Architect - Associate (SAA-C03) Questions and Answers

To store and access files that are 25 GB or larger across many EC2 instances and across multiple Availability Zones, Amazon Elastic File System (Amazon EFS) is a suitable solution. Amazon EFS provides a simple, scalable, elastic file system that can be mounted on multiple EC2 instances concurrently. Amazon EFS supports high availability and durability by storing data across multiple Availability Zones within a Region.

Requirement Analysis: The application involves batch processing of large data transfers between EC2 instances.

Data Transfer Costs: Data transfer within the same Availability Zone (AZ) is typically free, while cross-AZ transfers incur additional costs.

Implementation:

Launch all EC2 instances within the same Availability Zone.

Ensure the instances are part of the same subnet to facilitate seamless data transfer.

Conclusion: Placing all EC2 instances in the same AZ reduces data transfer costs significantly without affecting the application’s functionality.

References

AWS Pricing:AWS Data Transfer Pricing

This answer is correct because it meets the requirements of maximizing the reliability of the application’s infrastructure. You can update the DB instance to be Multi-AZ, which means that Amazon RDS automatically provisions and maintains a synchronous standby replica in a different Availability Zone. The primary DB instance is synchronously replicated across Availability Zones to a standby replica to provide data redundancy and minimize latency spikes during system backups. Running a DB instance with high availability can enhance availability during planned system maintenance. It can also help protect your databases against DB instance failure and Availability Zone disruption. You can also enable deletion protection on the DB instance, which prevents the DB instance from being deleted by any user. You can place the EC2 instances behind an Application Load Balancer, which distributes incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones. This increases the availability and fault tolerance of your applications. You can run the EC2 instances in an EC2 Auto Scaling group across multiple Availability Zones, which ensures that you have the correct number of EC2 instances available to handle the load for your application. You can use scaling policies to adjust the number of instances in your Auto Scaling group in response to changing demand.

The company wants to improve the availability and performance of the application, as well as protect it against common web exploits. The company also needs static IP addresses for the application. To meet these requirements, a solutions architect should recommend the following solution:

Put the EC2 instances behind Network Load Balancers (NLBs) in each Region. NLBs are designed to handle millions of requests per second while maintaining high throughput at ultra-low latency. NLBs also support static IP addresses for each Availability Zone, which can be useful for whitelisting or firewalling purposes.

Deploy AWS WAF on the NLBs. AWS WAF is a web application firewall that helps protect web applications from common web exploits that could affect availability, security, or performance. AWS WAF lets you define customizable web security rules that control which traffic to allow or block to your web applications.

Create an accelerator using AWS Global Accelerator and register the NLBs as endpoints. AWS Global Accelerator is a service that improves the availability and performance of your applications with local or global users. It provides static IP addresses that act as a fixed entry point to your application endpoints in any AWS Region. It uses the AWS global network to optimize the path from your users to your applications, improving the performance of your TCP and UDP traffic.

This solution will provide high availability across Availability Zones and Regions, improve performance by routing traffic over the AWS global network, protect the application from common web attacks, and provide static IP addresses for the application.

Amazon RDS for Microsoft SQL Server is a fully managed service that offers SQL Server 2014, 2016, 2017, and 2019 editions while offloading database administration tasks such as backups, patching, and scaling. Amazon RDS supports read replicas, which are read-only copies of the primary database that can be used for reporting purposes without affecting the performance of the online application. This solution will meet the requirements with the least operational overhead, as it does not require any code changes or manual intervention.

A gateway endpoint is a gateway that is a target for a specified route in your routetable, used for traffic destined to a supported AWS service1. Amazon S3 does not support gateway endpoints, only interface endpoints2. Therefore, option A is incorrect.

An interface endpoint is an elastic network interface with a private IP address that serves as an entry point for traffic destined to a supported service1. An interface endpoint can provide secure access toAmazon S3 from within the Region, but not from the on-premises location. Therefore, option C is incorrect.

AWS Key Management Service (AWS KMS) is a service that allows you to create and manage encryption keys to protect your data3. AWS KMS does not provide a way to access data on Amazon S3 without traversing the internet. Therefore, option D is incorrect.

AWS Transit Gateway is a service that enables you to connect your Amazon Virtual Private Clouds (VPCs) and your on-premises networks to a single gateway. You can create a gateway in AWS Transit Gateway to access Amazon S3 securely from both the Region and the on-premises location using AWS Direct Connect. Therefore, option B is correct.

This answer is correct because it meets the requirements of displaying a top-10 scoreboard in near-real time and offering the ability to stop and restore the game while preserving the current scores. Amazon ElastiCache for Redis is a blazing fast in-memory data store that provides sub-millisecond latency to power internet-scale real-time applications. You can use Amazon ElastiCache for Redis to set up an ElastiCache for Redis cluster to compute and cache the scores for the web application to display. You can use Redis data structures such as sorted sets and hashes to store and rank the scores of the players, and use Redis commands such as ZRANGE and ZADD to retrieve and update the scores efficiently. You can also use Redis persistence features such as snapshots and append-only files (AOF) to enable point-in-time recovery of your data, which can help you stop and restore the game while preserving the current scores.

it allows the compliance team to manage the KMS keys used for server-side encryption, thereby providing the necessary control over the encryption keys. Additionally, the use of the "aws:SecureTransport" condition on the bucket policy ensures that all connections to the S3 bucket are encrypted in transit.

Consider using the default aws/s3 KMS key if: You're uploading or accessing S3 objects using AWS Identity and Access Management (IAM) principals that are in the same AWS account as the AWS KMS key. You don't want to manage policies for the KMS key. Consider using a customer managed key if: You want to create, rotate, disable, or define access controls for the key. You want to grant cross-account access to your S3 objects. You can configure the policy of a customer managed key to allow access from another account.https://repost.aws/knowledge-center/s3-object-encryption-keys

This JSON text is an identity-based policy that grants specific permissions. The IAM principals that the solutions architect can attach this policy to are Role and Group. This is because the policy is written in JSON and is an identity-based policy, which can be attached to IAM principals such as users, groups, and roles. Identity-based policies are permissions policies that you attach to IAM identities (users, groups, or roles) and explicitly state what that identity is allowed (or denied) to do1. Identity-based policies are different from resource-based policies, which define the permissions around the specific resource1. Resource-based policies are attached to a resource, such as an Amazon S3 bucket or anAmazon EC2 instance1. Resource-based policies can also specify a principal, which is the entity that is allowed or denied access to the resource1. Organization is not an IAM principal, but a feature of AWS Organizations that allows you to manage multiple AWSaccountscentrally2. Amazon ECS resource and Amazon EC2 resource are not IAM principals, but AWS resources that can have resource-based policies attached to them34.

it allows the company to deploy an application that processes large quantities of data in parallel and prevent groups of nodes from sharing the same underlying hardware. By running the EC2 instances in a spread placement group, the company can launch a small number of instances across distinct underlying hardware to reduce correlated failures. A spread placement group ensures that each instance is isolated from each other at the rack level. References:

Placement Groups

Spread Placement Groups

AWS Global Accelerator directs traffic to the optimal healthy endpoint based on health checks, it can also route traffic to the closest healthy endpoint based on geographic locationof the client. By configuring an accelerator and attaching it to a Regional endpoint in each Region, and adding the ALB as the endpoint, the solution will redirect traffic to healthy endpoints, improving the user experience by reducing latency and ensuring that the application is running optimally. This solution will ensure that traffic is directed to the closest healthy endpoint and will help to improve the overall user experience.

Kubernetes API requests within your cluster's VPC (such as node to control plane communication) use the private VPC endpoint.https://docs.aws.amazon.com/eks/latest/userguide/cluster-endpoint.html

it allows the application EC2 instances to access the DynamoDB tables without exposing API credentials in the template. By creating an IAM role that has the required permissions to read and write from the DynamoDB tables and adding it to the EC2 instance profile, the application instances can use temporary security credentials that are automatically rotated by AWS. This is a secure and best practice way to grant access to AWS resources from EC2 instances. References:

IAM Roles for Amazon EC2

Using Instance Profiles

To meet the requirements of the use case in a cost-effective way, the following steps are recommended:

Deploy an AWS Storage Gateway on premises in Amazon S3 File Gateway mode. This will allow the company to write the .csv files generated by the devices to an SMB file share, which will be stored as objects in Amazon S3 buckets. AWS Storage Gateway is a hybrid cloud storage service that integrates on-premises environments with AWS storage. Amazon S3 File Gateway mode provides a seamless way to connect to Amazon S3 and access a virtually unlimited amount of cloud storage1.

Set up an AWS Glue crawler to create a table based on the data that is in Amazon S3. This will enable the company to use standard SQL to query the data stored in Amazon S3 buckets. AWS Glue is a serverless data integration service that simplifies data preparation and analysis. AWS Glue crawlers can automatically discover and classify data from various sources, and create metadata tables in the AWS Glue Data Catalog2. The Data Catalog is a central repository that stores information about data sources and how to access them3.

Set up Amazon Athena to query the data that is in Amazon S3. This will provide the company analysts with a serverless and interactive query service that can analyze data directly in Amazon S3 using standard SQL. Amazon Athena is integrated with the AWS Glue Data Catalog, so users can easily point Athena at the data source tables defined by the crawlers. Amazon Athenacharges only for the queries that are run, and offers a pay-per-query pricing model, which makes it a cost-effective option for periodic queries4.

The other options are not correct because they are either not cost-effective or not suitable for the use case. Deploying an AWS Storage Gateway on premises in Amazon FSx File Gateway mode is not correct because this mode provides low-latency access to fully managed Windows file shares in AWS, which is not required for the use case. Setting up an Amazon EMR cluster with EMR File System (EMRFS) to query the data that is in Amazon S3 is not correct because this option involves setting up and managing a cluster of EC2 instances, which adds complexity and cost to the solution. Setting up an Amazon Redshift cluster to query the data that is in Amazon S3 is not correct because this option also involves provisioning and managing a cluster of nodes, which adds overhead and cost to the solution.

This solution provides the appropriate user access most cost-effectively because it uses the Amazon S3 Intelligent-Tiering storage class, which automatically optimizes storage costs by moving data to the most cost-effective access tier when access patterns change, without performance impact or operational overhead1. This storage class is ideal for datawith unknown, changing, or unpredictable access patterns, such as photos that are heavily viewed for months or less than a week. By storing the photo metadata and its S3 location in DynamoDB, the application can quickly query and retrieve the relevant photos for each user. DynamoDB is a fast, scalable, and fully managed NoSQL database service that supports key-value and document data models2.

AWS Lambda charges you based on the number of invocations and the execution time of your function. Since the data processing job is relatively small (2 MB of data), Lambda is a cost-effective choice. You only pay for the actual usage without the need to provision and maintain infrastructure.

AWS Snowball is a petabyte-scale data transport service that uses secure devices to transfer large amounts of data into and out of the AWS Cloud. Snowball addresses common challenges with large-scale data transfers including high network costs, long transfer times, and security concerns. AWS Snowball can transfer up to 80 TB of data per device, and multiple devices can be used in parallel to meet the migration deadline. AWS Snowball is more cost-effective than AWS Snowmobile, which is designed for exabyte-scale data transfers, or Amazon S3 Transfer Acceleration, which is optimized for fast transfers over long distances. Amazon S3 VPC endpoint does not increase the upload speed, but only provides a secure and private connection between the VPC and S3. References: AWS Snowball, AWS Snowmobile, Amazon S3 Transfer Acceleration, Amazon S3 VPC endpoint

company need to setup a cheaper connection (200 M) but B is incorrect because you can only order port speeds of 1, 10, or 100 Gbps for more flexibility you can go with hosted connection, You can order port speeds between 50 Mbps and 10 Gbps.https://docs.aws.amazon.com/whitepapers/latest/aws-vpc-connectivity-options/aws-direct-connect.html

Dynamic scaling is a type of autoscaling that automatically adjusts the number of EC2 instances in an Auto Scaling group based on demand or load. It uses CloudWatch alarms to trigger scaling actions when a specified metric crosses a threshold. It can scale out (addinstances) or scale in (remove instances) as needed1. By using dynamic scaling, the solution can maintain application performance during sudden traffic increases most cost-effectively.

A. Use manual scaling to change the size of the Auto Scaling group. This solution will not meet the requirement of maintaining application performance during sudden traffic increases, as manual scaling requires users to manually increase or decrease the number of instances through a CLI or console. It does not respond automatically to changes in demand or load2.

B. Use predictive scaling to change the size of the Auto Scaling group. This solution will not meet the requirement of most cost-effectiveness, as predictive scaling uses machine learning and artificial intelligence tools to evaluate traffic loads and anticipate when more or fewer resources are needed. It performs scheduled scaling actions based on the prediction, which may not matchthe actual demand or load at any given time. Predictive scaling is more suitable for scenarios where there are predictable traffic patterns or known changes in traffic loads3.

D. Use schedule scaling to change the size of the Auto Scaling group. This solution will not meet the requirement of maintaining application performance during sudden traffic increases, as schedule scaling performs scaling actions at specific times that users schedule. It does not respond automatically to changes in demand or load. Schedule scaling is more suitable for scenarios where there are predictable traffic drops or spikes at specific times of the day.

Reference URL: https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scale-based-on-demand.html

This answer is correct because it meets the requirements of accessing a shared file system that is highly durable, can recover data to another AWS Region, and can provide a mount target in each Availability Zone within a Region. Amazon FSx for NetApp ONTAP is a fully managed service that provides enterprise-grade data management and storage for your Windows and Linux applications. You can use Amazon FSx for NetApp ONTAP to create file systems that span multiple Availability Zones within an AWS Region, providing high availability and durability. You can also use AWS Backup to manage the replication of your file systems to another AWS Region, with a recovery point objective (RPO) of 8 hours or less. AWS Backup is a fully managed backup service that automates and centralizes backup of data over AWS services. You can use AWS Backup to create backup policies and monitor activity for your AWS resources in one place.

Using an interface endpoint will allow the BuyStock RESTful web service and the CheckFunds RESTful web service to communicate through the VPC without any changes to the code. An interface endpoint creates an elastic network interface (ENI) in the customer's VPC, and then configures the route tables to route traffic from the APIs to the ENI. This will ensure that the two APIs will communicate through the VPC without any changes to the code.

S3 Object Lock enables a write-once-read-many (WORM) model for objects stored in Amazon S3. It can help prevent objects from being deleted or overwritten for a fixed amount of time or indefinitely1. S3 Object Lock has two retention modes: governance mode and compliance mode. Compliance mode provides the highest level of protection and prevents any user, including the root user, from deleting or modifying an object version until the retention period expires. To use S3 Object Lock, a new bucket with Object Lock enabled must be created, and a default retention period can be optionally configured for objects placed in the bucket2. To bring existing objects into compliance, they must be recopied into the bucket with a retention period specified.

Option A is incorrect because S3 Versioning and S3 Lifecycle do not provide WORM protection for objects. Moreover, MFA delete only applies to deleting object versions, not modifying them.

Option B is incorrect because governance mode allows users with special permissions to override or remove the retention settings or delete the object if necessary. This does not meet the legal requirement of retaining all data for 7 years.

Option D is incorrect because S3 Batch Operations cannot be used to apply compliance mode retention periods to existing objects. S3 Batch Operations can only apply governance mode retention periods or legal holds. Reference URL: 2: https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock-console.html 3:https://docs.aws.amazon.com/AmazonS3/latest/userguide/storage-class-intro.html#sc-dynamic-data-access 4:https://docs.aws.amazon.com/AmazonS3/latest/userguide/transfer-acceleration.html 1: https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock.html : https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock-overview.html : https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock-managing.html : https://aws.amazon.com/blogs/storage/managing-amazon-s3-access-with-vpc-endpoints-and-s3-access-points/

Workload Discovery on AWS (formerly called AWS Perspective) is a tool that visualizes AWS Cloud workloads. It maintains an inventory of the AWS resources across your accounts and Regions, mapping relationships between them, and displaying them in a web UI. It also allows you to query AWS Cost and Usage Reports, search for resources, save and export architecture diagrams, and more1. By using Workload Discovery on AWS, the solution can build and map the relationship details of the various workloads across all accounts with the least operational effort.

A. Use AWS Systems Manager Inventory to generate a map view from the detailed view report. This solution will not meet the requirement of building and mapping the relationship details of the various workloads across all accounts, as AWS Systems Manager Inventory is a feature thatcollects metadata from your managed instances and stores it in a central Amazon S3 bucket. It does not provide a map view or architecture diagrams of the workloads2.

B. Use AWS Step Functions to collect workload details Build architecture diagrams of the work-loads manually. This solution will not meet the requirement of the least operational effort, as it involves creating and managing state machines to orchestrate the workload details collection, and building architecture diagrams manually.

D. Use AWS X-Ray to view the workload details Build architecture diagrams with relationships. This solution will not meet the requirement of the least operational effort, as it involves instrumenting your applications with X-Ray SDKs to collect workload details, and building architecture diagrams manually.

Reference URL: https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/

API Gateway + Lambda is the perfect solution for modern applications with serverless architecture.

To back up EC2 instances and RDS DB instances in a separate Region with the least operational overhead, AWS Backup is a simple and cost-effective solution. AWS Backup can copy EC2 backups and RDS backups to another Region automatically and securely. AWS Backup also supports backup policies, retention rules, and monitoring features.

The most cost-effective solution for the online video game company is to configure a Network Load Balancer with the required protocol and ports for the internet traffic and specify the EC2 instances as the targets. This solution will enable the company to handle millions of UDP requests per second with ultra-low latency and high performance.

A Network Load Balancer is a type of Elastic Load Balancing that operates at the connection level (Layer 4) and routes traffic to targets (EC2 instances, microservices, or containers) within Amazon VPC based on IP protocol data. A Network Load Balancer is ideal for load balancing of both TCP and UDP traffic, as it is capable of handling millions of requests per second while maintaining high throughput at ultra-low latency. A Network Load Balancer also preserves the source IP address of the clients to the back-end applications, which can be useful for logging or security purposes1.

AWS Global Accelerator is a networking service that improves the performance and availability of applications for global users. It uses the AWS global network to route user traffic to the optimal endpoint based on performance and health. It also provides static IP addresses that act as a fixed entry point to the applications and support both TCP and UDP protocols1. By using AWS Global Accelerator, the solution can ensure the lowest possible latency for all users.

A. Use AWS Global Accelerator to create an accelerator. Create an Application Load Balancer (ALB) behind an accelerator endpoint that uses Global Accelerator integration and listening on the TCP and UDP ports. Update the Auto Scaling group to register instances on the ALB. This solution will not work, as ALB does not support UDP protocol2.

C. Create an Amazon CloudFront content delivery network (CDN) endpoint. Create a Network Load Balancer (NLB) behind the endpoint and listening on the TCP and UDP ports. Update the Auto Scaling group to register instances on the NLB. Update CloudFront to use the NLB as the origin. This solution will not work, as CloudFront does not support UDP protocol3.

D. Create an Amazon Cloudfront content delivery network (CDN) endpoint. Create an Application Load Balancer (ALB) behind the endpoint and listening on the TCP and UDP ports. Update the Auto Scaling group to register instances on the ALB. Update CloudFront to use the ALB as the origin. This solution will not work, as CloudFront and ALB do not support UDP protocol23.

Reference URL: https://aws.amazon.com/global-accelerator/

To store and retrieve reports that are frequently accessed during the first week and must be stored for several years, S3 Standard and S3 Glacier are suitable solutions. S3 Standard offers high durability, availability, and performance for frequently accessed data. S3 Glacier offers secure and durable storage for long-term data archiving at a low cost. S3 Lifecycle rules can be used to transition the reports from S3 Standard to S3 Glacier after 7 days, which can reduce storage costs. S3 Glacier also supports retrieval within 6 hours.

This answer is correct because it provides high availability at the node level and at the Region level for the ElastiCache for Redis solution. A Multi-AZ Redis replication groupconsists of a primary cluster and up to five read replica clusters, each in a different Availability Zone. If the primary cluster fails, one of the read replicas is automatically promoted to be the new primary cluster. A Redis replication group with shards enables partitioning of the data across multiple nodes, which increases the scalability and performance of the solution. Each shard can have one or more replicas to provide redundancy and read scaling.

AWS Glue is a serverless data integration service that can crawl, catalog, and prepare data for analysis. AWS Glue can automatically discover the schema and partitioning of the data stored in Apache Parquet format in S3, and create a table in the AWS Glue Data Catalog. Amazon Athena is a serverless interactive query service that can run SQL queries directly on data in S3, without requiring any data loading or transformation. Athena can use the table metadata from the AWS Glue Data Catalog to query the data in S3. By using AWS Glue and Athena, you can analyze the log files in S3 most cost-effectively, as you only pay for the resources consumed by the crawler and the queries, and you do not need to provision or manage any servers or clusters.

This option is the most cost-effective solution because it leverages the Spot Instances, which are unused EC2 instances that are available at up to 90% discount compared to On-Demand prices.Spot Instances can be interrupted by AWS when the demand for On-Demand instances increases, but since the batch jobs are fault-tolerant and can be reprocessed by another instance, this is not a major issue. By using a launch template, the company can specify the configuration of the Spot Instances, such as the instance type, the operating system, and the user data. By using an Auto Scaling group, the company can automatically scale the number of Spot Instances based on the CPU usage, which reflects the load of the batch jobs. This way, the company can optimize the performance and the cost of the EC2 instances for the nightly batch jobs.

A. Purchase a 1-year Savings Plan for Amazon EC2 that covers the instance family of the Auto Scaling group that the batch job uses. This option is not optimal because it requires a commitment to a consistent amount of compute usage per hour for a one-year term, regardless of the instance type, size, region, or operating system. This can limit the flexibility and scalability of the Auto Scaling group and result in overpaying for unused compute capacity. Moreover, Savings Plans do not provide a capacity reservation, which means the company still needs to reserve capacity with On-Demand Capacity Reservations and pay lower prices with Savings Plans.

B. Purchase a 1-year Reserved Instance for the specific instance type and operating system of the instances in the Auto Scaling group that the batch job uses. This option is not ideal because it requires a commitment to a specific instance configuration for a one-year term, which can reduce the flexibility and scalability of the Auto Scaling group and result in overpaying for unused compute capacity. Moreover, Reserved Instances do not provide a capacity reservation, which means the company still needs to reserve capacity with On-Demand Capacity Reservations and pay lower prices with Reserved Instances.

D. Create a new launch template for the Auto Scaling group Increase the instance size Set a policy to scale out based on CPU usage. This option is not cost-effective because it does not take advantage of the lower prices of Spot Instances. Increasing the instance size can improve the performance of the batch jobs, but it can also increase the cost of the On-Demand instances. Moreover, scaling out based on CPU usage can result in launching more instances than needed, which can also increase the cost of the system.

This solution meets the requirements because it allows the company to use both predictive scaling and dynamic scaling to optimize the capacity of its Auto Scaling group. Predictive scaling uses machine learning to analyze historical data and forecast future traffic patterns. It then adjusts the desired capacity of the group in advance of the predicted changes. Dynamic scaling uses target tracking to maintain a specified metric (such as CPU utilization) at a target value. It scales the group in or out as needed to keep the metric close to the target. By using both scaling methods, the company can benefitfrom faster, simpler, and more accurate scaling that responds to both forecasted and live changes in utilization.

Versioning is a feature of Amazon S3 that allows users to keep multiple versions of the same object in a bucket. It can help prevent accidental deletion of the documents and ensure that all versions of the documents areavailable1. MFA Delete is a feature of Amazon S3 that adds an extra layer of security by requiring two forms of authentication to delete a version or change the versioning state of a bucket. It can help preventunauthorized or accidental deletion of the documents2. By enabling both versioning and MFA Delete on the bucket, the solution can meet the requirements.

A. Enable a read-only bucket ACL. This solution will not meet the requirement of allowing users to download, modify, and upload documents, as a read-only bucket ACL will prevent write access to the bucket3.

C. Attach an IAM policy to the bucket. This solution will not meet the requirement of preventing accidental deletion of the documents and ensuring that all versions of the documents are available, as an IAM policy is used to grant or deny permissions to users or roles, not to enable versioning or MFA Delete4.

E. Encrypt the bucket using AWS KMS. This solution will not meet the requirement of preventing accidental deletion of the documents and ensuring that all versions of the documents are available, as encrypting the bucket using AWS KMS is a method of protecting data at rest, not enabling versioning or MFA Delete.

Reference URL: https://docs.aws.amazon.com/AmazonS3/latest/userguide/Versioning.html

This option is the best solution because it allows the company to decouple the analytics software from the user requests and scale the EC2 instances dynamically based on the demand. By using Amazon SQS, the company can create a queue that stores the user requests and acts as a buffer between the users and the analytics software. This way, the software can process the requests at its own pace without losing any data or overloading the EC2 instances. By using EC2 Auto Scaling, the company cancreate an Auto Scaling group that launches or terminates EC2 instances automatically based on the size of the queue. This way, the company can ensure that there are enough instances to handle the load and optimize the cost and performance of the system. By updating the software to read from the queue, the company can enable the analytics software to consume the requests from the queue and process the data from Amazon S3.

A. Create a copy of the instance Place all instances behind an Application Load Balancer. This option is not optimal because it does not address the root cause of the problem, which is the high CPU utilization of the EC2 instances. An Application Load Balancer can distribute the incoming traffic across multiple instances, but it cannot scale the instances based on the load or reduce the processing time of the analytics software. Moreover, this option can incur additional costs for the load balancer and the extra instances.

B. Create an S3 VPC endpoint for Amazon S3 Update the software to reference the endpoint. This option is not effective because it does not solve the issue of the high CPU utilization of the EC2 instances. An S3 VPC endpoint can enable the EC2 instances to access Amazon S3 without going through the internet, which can improve the network performance and security. However, it cannot reduce the processing time of the analytics software or scale the instances based on the load.

C. Stop the EC2 instances. Modify the instance type to one with a more powerful CPU and more memory. Restart the instances. This option is not scalable because it does not account for the variability of the user load. Changing the instance type to a more powerful one can improve the performance of the analytics software, but it cannot adjust the number of instances based on the demand. Moreover, this option can increase the cost of the system and cause downtime during the instance modification.

Understanding the Requirement: The company needs to redesign the architecture to be highly available and use AWS managed solutions for hosting a web application with static content, PHP application, and Redis for user sessions.

Analysis of Options:

AWS Elastic Beanstalk: Suitable for simplifying deployment but may not provide the desired flexibility and control for complex architectures.

AWS Lambda and API Gateway: Not ideal for hosting a stateful PHP application and handling static content.Adding complexity without significant benefit.

EC2 instance with ElastiCache and S3: Provides some high availability but involves managing EC2 instances, which increases operational overhead.

CloudFront with S3, ALB, ECS with Fargate, and ElastiCache: This solution leverages fully managed AWS services for each component, ensuring high availability and scalability.

Best Solution:

CloudFront with S3, ALB, ECS with Fargate, and ElastiCache: This combination of services meets the requirements for a highly available and managed solution, ensuring optimal performance and minimal operational overhead.

Understanding the Requirement: The company needs to transfer 50 TB of data to AWS with minimal operational overhead and no available network bandwidth for the transfer. The transformation job must continue running in the AWS Cloud.

Analysis of Options:

AWS DataSync and AWS Glue: DataSync is suitable for online data transfer, but there is no available network bandwidth. AWS Glue can be used for data transformation but does not solve the bandwidth issue.

AWS Snowcone: Snowcone is a smaller device suitable for smaller data transfers, and deploying the transformation application on it may not be feasible for 50 TB of data.

AWS Snowball Edge Storage Optimized with Glue: This device is designed for large data transfers. Copying the data to the device is straightforward, and AWS Glue can handle data transformation in the cloud.

AWS Snowball Edge Storage Optimized with EC2: This involves setting up EC2 instances for transformation, adding operational complexity compared to using AWS Glue.

Best Solution:

AWS Snowball Edge Storage Optimized with AWS Glue: This provides the least operational overhead for transferring large amounts of data and setting up the transformation job in the cloud.

A Network Load Balancer can be assigned one Elastic IP address for each Availability Zone it uses1. This allows the clients to reach the load balancer using a static IP address that can be authorized on their firewalls. An Application Load Balancer cannot be assigned an Elastic IP address2. An A record in an Amazon Route 53 hosted zone pointing to an Elastic IP address would not work because the load balancer would still use its own IP address as the source of the forwarded requests to the web service. An EC2 instance with a public IP address running as a proxy in front of the load balancer would add unnecessary complexity and cost, and would not provide the same scalability and availability as a Network Load Balancer. References: 1: Network Load Balancers - Elastic Load Balancing3, IP address type section2: How to assign Elastic IP to Application Load Balancer in AWS?4, answer section.

This option is the most efficient because it uses AWS Storage Gateway, which is a service that connects an on-premises software appliance with cloud-based storage to provide seamless integrationwith data security features between your on-premises ITenvironment and the AWS storage infrastructure1. It also uses a stored volume gateway, which is a type of volume gateway that stores your primary data locally and asynchronously backs up point-in-time snapshots of your data to Amazon S32. It also runs the Storage Gateway software application on premises and maps the gateway storage volumes to on-premises storage,which enables you to use your existing storage hardware and network infrastructure. It also mounts the gateway storage volumes to provide local access to the data, which ensures that your data is available for low latency access on premises while also getting backed up to AWS. This solution meets the requirement of maintaining local access to all the data while it is backed up on AWS and ensuring that the data backed up on AWS is automatically and securely transferred. Option A is less efficient because it uses AWS Snowball, which is a physical device that lets you transfer large amounts of data into and out of AWS3. However, this does not provide a periodic backup solution, as it requires manual handling and shipping of the device. It also configures on-premises systems to mount the Snowball S3 endpoint to provide local access to the data, which could introduce additional complexity and latency. Option B is less efficient because it uses AWS Snowball Edge, which is a physical device that has onboard storage and compute capabilities for select AWS capabilities. However, this does not provide a periodic backup solution, as it requires manual handling and shipping of the device. It also uses the Snowball Edge file interface to provide on-premises systems with local access to the data, which could introduce additional complexity and latency. Option C is less efficient because it uses AWS Storage Gateway and configures a cached volume gateway, which is a type of volume gateway that stores your primary data in Amazon S3 and retains a copy of frequently accessed data subsets locally. However, this does not provide local access to all the data, as only some datasubsets are cached locally. It also configures a percentage of data to cache locally, which could incur higher costs and complexity than using a stored volume gateway.

Amazon Inspector is an automated security assessment service that helps improve the security and compliance of applications deployed on AWS. Amazon Inspector automatically assesses applications for exposure, vulnerabilities, and deviations from best practices. After performing an assessment, Amazon Inspector produces a detailed list of security findings prioritized by level of severity1. Amazon Inspector can scan the EC2 instances for software vulnerabilities and provide a report of each instance’s patch status. AWS Systems Manager Patch Manager is a capability of AWS Systems Manager that automates the process of patching managed nodes with both security-related updates and other types of updates. Patch Manager uses patch baselines, which include rules for auto-approving patches within days of their release, in addition to optional lists of approved and rejected patches. Patch Manager can patch fleets of Amazon EC2 instances, edge devices, on-premises servers, and virtual machines (VMs) by operating system type2. PatchManager can patch the EC2 instances on a regular schedule and provide a report of each instance’s patch status. Therefore, the combination of Amazon Inspector and AWS Systems Manager Patch Manager will meet the requirements of the question.

The other options are not valid because:

Amazon Macie is a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. Amazon Macie does not scan the EC2 instances for software vulnerabilities, but rather for data classification and protection3. A cron job is a Linux command for scheduling a task to be executed sometime in the future. A cron job is not a reliable way to patch the EC2 instances on a regular schedule, as it may fail or be interrupted by other processes4.

Amazon GuardDuty is a threat detection service that continuously monitors for malicious activity and unauthorized behavior to protect your AWS accounts and workloads. Amazon GuardDuty does not scan the EC2 instances for software vulnerabilities, but rather for network and API activity anomalies5. AWS Systems Manager Session Manager is a fully managed AWS Systems Manager capability that lets you manage your Amazon EC2 instances, edge devices, on-premises servers, and virtual machines (VMs) through an interactive one-click browser-based shell or the AWS Command Line Interface (AWS CLI). Session Manager does not patch theEC2 instances on a regular schedule, but rather provides secure and auditable node management2.

Amazon Detective is a security service that makes it easy to analyze, investigate, and quickly identify the root cause of potential security issues or suspicious activities. Amazon Detective does not scan the EC2 instances for software vulnerabilities, but rather collects and analyzes data from AWS sources such as Amazon GuardDuty, Amazon VPC Flow Logs, and AWS CloudTrail. Amazon EventBridge is a serverless event bus that makes it easy to connect applications using data from your own applications, integrated Software-as-a-Service (SaaS) applications, and AWS services. EventBridge delivers a stream of real-time data from event sources, such as Zendesk, Datadog, or Pagerduty, and routes that data to targets like AWS Lambda. EventBridge does not patch the EC2 instances on a regular schedule, but rather triggers actions based on events.

A cross-account IAM role is a way to grant users from one AWS account access to resources in another AWS account. The cross-account IAM role can have a read-only access policy attached to it, which allows the users to download objects from the S3 buckets without modifying or deleting them. The cross-account IAM role also reduces the operational overhead of managing multiple IAM users and policies in each account. The cross-account IAM role meets all the requirements of the question, while the other options do not. References:

https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-walkthroughs-managing-access-example2.html

https://aws.amazon.com/blogs/storage/setting-up-cross-account-amazon-s3-access-with-s3-access-points/

https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-user_externalid.html

This solution meets the requirements most cost-effectively because it enables the company to migrate its on-premises NFS data store to AWS without changing the existing applications or workflows. AWS Storage Gateway is a hybrid cloud storage service that provides seamless and secure integration between on-premises and AWS storage. Amazon S3 File Gateway is a type of AWS Storage Gateway that provides a file interface to Amazon S3, with local caching for low-latency access. By setting up an Amazon S3 File Gateway, the company can store and retrieve files as objects in Amazon S3 using standard file protocols such as NFS. The company can also use an Amazon S3 Lifecycle policy to automatically transition the data to the appropriate storage class based on the frequency of access and the cost of storage. For example, the company can use S3 Standard for frequently accessed data, S3 Standard-Infrequent Access (S3 Standard-IA) or S3 One Zone-Infrequent Access (S3 One Zone-IA) for less frequently accessed data, and S3 Glacier or S3 Glacier Deep Archive for long-term archival data.

Option A is not a valid solution because AWS Storage Gateway Volume Gateway is a type of AWS Storage Gateway that provides a block interface to Amazon S3, with local caching for low-latency access. Volume Gateway is not suitable for migrating an NFS data store, as it requires attaching the volumes to EC2 instances or on-premises servers using the iSCSI protocol. Option C is not a valid solution because Amazon Elastic File System (Amazon EFS) is a fully managed elastic NFS file system that is designed for workloads that require high availability, scalability, and performance. Amazon EFS Standard-Infrequent Access (Standard-IA) is a storage class within Amazon EFS that is optimized for infrequently accessed files, with a lower price per GB and a higher price per access. Using Amazon EFS Standard-IA for migrating an NFS data store would not be cost-effective, as it would incur higher access charges and require additional configuration to enable lifecycle management. Option D is not a valid solution because Amazon EFS One Zone-Infrequent Access (One Zone-IA) is a storage class within Amazon EFS that isoptimized for infrequently accessed files that do not require the availability and durability of Amazon EFS Standard or Standard-IA. Amazon EFS One Zone-IA stores data in a single Availability Zone, which reduces the cost by 47% compared to Amazon EFS Standard-IA, but also increases the risk of data loss in the event of an Availability Zone failure. Using Amazon EFS One Zone-IA for migrating an NFS data store would not be cost-effective, as it would incur higher access charges and require additional configuration to enable lifecycle management. It would also compromise the availability and durability of the data.

This solution meets the requirements because it allows the company to move the application to a fully managed service without managing any servers or storage infrastructure. AWS Fargate is a serverless compute engine for containers that runs the Amazon ECS tasks. With Fargate, the company does not need to provision, configure, or scale clusters of virtual machines to run containers. Amazon EFS is a fully managed file system that can be accessed by multiple containers concurrently. With EFS, the company does not need to provision and manage storage capacity. EFS provides a simple interface to create and configure file systems quickly and easily. The company can use the EFS volume as a persistent storage volume mounted in the containers to store the persistent data. The company can also use the EFS mount helper to simplify the mountingprocess. References: Amazon ECS on AWS Fargate, Using Amazon EFS file systems with Amazon ECS, Amazon EFS mount helper.

To ensure that the shopping cart data is preserved at all times, a solutions architect should configure Amazon ElastiCache for Redis to cache catalog data from Amazon DynamoDB and shopping cart data from the user’s session. This solution has the following benefits:

It offers the lowest possible latency from the application, as ElastiCache for Redis is a blazing fast in-memory data store that provides sub-millisecond latency to power internet-scale real-time applications1.

It scales with traffic volume, as ElastiCache for Redis supports horizontal scaling by adding more nodes or shards to the cluster, and vertical scaling by changing the node type2.

It ishighly available, as ElastiCache for Redis supports replication across multiple Availability Zones and automatic failover in case of a primary node failure3.

It preserves user session data even if the user is disconnected and reconnects, as ElastiCache for Redis can store session data, such as user login information and shopping cart contents, in a persistent and durable manner using snapshots or AOF (append-only file) persistence4.

The company wants to reduce the compute costs and maintain service latency for its Lambda functions that process a constantly increasing number of messages in a message queue. The Lambda functions use CPU intensive code to process the messages. To meet these requirements, a solutions architect should recommend the following solution:

Configure provisioned concurrency for the Lambda functions. Provisioned concurrency is the number of pre-initialized execution environments that are allocated to the Lambda functions. These execution environments are prepared to respond immediately to incoming function requests, reducing the cold start latency. Configuring provisioned concurrency also helps to avoid throttling errors due to reaching the concurrency limit of the Lambda service.

Increase the memory according to AWS Compute Optimizer recommendations. AWS Compute Optimizer is a service that provides recommendations for optimal AWS resource configurations based on your utilization data. By increasing the memory allocated to the Lambda functions, you can also increase the CPU power and improve the performance of your CPU intensive code.AWS Compute Optimizer can help you find the optimal memory size for your Lambda functions based on your workload characteristics and performance goals.

This solution will reduce the compute costs by avoiding unnecessary over-provisioning of memory and CPU resources, and maintain service latency by using provisioned concurrency and optimal memory size for the Lambda functions.

This solution meets the requirements most securely because it uses IAM roles and the STS AssumeRole API operation to authenticate and authorize the inventory application to access the DynamoDB tables in different accounts. IAM roles are more secure than IAM users or certificates because they do not require long-term credentials or passwords. Instead, IAM roles provide temporary security credentials that are automatically rotated and can be configured with a limited duration. The STS AssumeRole API operation enables you to request temporary credentials for a role that you are allowed to assume. By using this operation, you can delegate access to resources that are in different AWS accounts that you own or that are owned by third parties. The trust policy of the role defines which entities can assume the role, and the permissions policy of the role defines which actions can be performed on the resources. By using this solution, you can avoid hard-coding credentials or certificates in the inventory application, and you can also avoid storing them in Secrets Manager or ACM. You can also leverage the built-in security features of IAM and STS, such as MFA, access logging, and policy conditions.

This solution meets the requirements because it allows the monitoring account to query and visualize observability data across the accounts by using CloudWatch. CloudWatch cross-account observability is a feature that enables a central monitoring account to view and interact with observability data shared by other accounts. To enable cross-account observability, the monitoring account needs to configure the types of data to be shared (metrics, logs, and traces) and the source accounts to be linked. The source accounts can be specified by account IDs, organization IDs, or organization paths. To share the data with the monitoring account, the source accounts need to deploy an AWS CloudFormation template provided by the monitoring account. This template creates an observability link resource that represents the link between the source account and the monitoring account. The template also creates a sink resource that represents an attachment point in the monitoring account. The source accounts can share theirobservability data with the sink in the monitoring account. The monitoring account can then use the CloudWatch console, API, or CLI to search, analyze, and correlate the observability data across the accounts. References: CloudWatch cross-account observability, Setting up CloudWatch cross-account observability, [Observability Access Manager API Reference]

The solution that meets the requirements of high availability, resiliency, and minimal operational effort is to use AWS Transfer for SFTP and an Amazon S3 bucket for storage. This solution allows the company to securely transfer files over SFTP to Amazon S3, which is a durable and scalable object storage service. The company can then modify the application to pull the batch files from Amazon S3 to an Amazon EC2 instance for processing. The EC2 instance can be part of an Auto Scaling group with a scheduled scaling policy to run the batch operation only at night. This way, the company can save costs by scaling down the EC2 instances when they are not needed. The other solutions do not meet all the requirements because they either use Amazon EFS or Amazon EBS for storage, which are more expensive and less scalable than Amazon S3, or they do not use a scheduled scaling policy to optimize the EC2 instances usage. References :=

AWS Transfer for SFTP

Amazon S3

Amazon EC2 Auto Scaling

The solution that meets the requirements is to develop an on-premises custom identity broker application or process that uses AWS Security Token Service (AWS STS) to get short-lived credentials. This solution allows the company to use its existing LDAP directory service to authenticate its users to the AWS Management Console, without requiring SAML compatibility.The custom identity broker application or process can act as a proxy between the LDAP directory service and AWS STS, and can request temporary security credentials for the users based on their LDAP attributes and roles. The users can then use these credentials to access the AWS Management Console via a sign-in URL generated by the identity broker. This solution also enhances security by using short-lived credentials that expire after a specified duration.

The other solutions do not meet the requirements because they either require SAML compatibility or do not provide access to the AWS Management Console. Enabling AWS IAM Identity Center (AWS Single Sign-On) between AWS and the on-premises LDAP would require the LDAP directory service to support SAML 2.0, which is not the case for this scenario. Creating an IAM policy that uses AWS credentials and integrating the policy into LDAP would not provide access to the AWS Management Console, but only to the AWSAPIs. Setting up a process that rotates the IAM credentials whenever LDAP credentials are updated would also not provide access to the AWS Management Console, but only to the AWS CLI. Therefore, these solutions are not suitable for the given requirements.

1. database shows no signs of being overloaded. CPU, memory, and disk access metrics are all low==>A and C out. We cannot only add nodes instance or add read replica, because database workload is totally fine, very low. 2. "least operational overhead"==>B out, because b need to configure lambda. 3. ROS proxy: Shares infrequently used connections; High availability with failover; Drives increased efficiency==>proxy can leverage failover to redirect traffic from timeout rds instance to healthy rds instance. So D is right.

The company is looking for a solution that provides single sign-on (SSO) across multiple AWS accounts while continuing to manage users and groups in their on-premises Active Directory (AD). AWS IAM Identity Center (formerly AWS SSO) is the recommended solution for this type of requirement.

AWS IAM Identity Centerprovides a centralized identity management solution, enabling single sign-on across multiple AWS accounts and other cloud applications. It can integrate with on-premises Active Directory to leverage existing users and groups.

By configuring a two-way forest trust relationship between AWS Directory Service for Microsoft Active Directory and the company's on-premises Active Directory, users can be authenticated by their on-premises AD and still access AWS resources through IAM Identity Center. This solution allows centralized management of AWS accounts within AWS Organizations.

The two-way trust allows mutual access between the on-premises AD and the AWS Directory Service. This means that users and groups in the on-premises AD can be used for authentication in AWS IAM Identity Center while maintaining the existing identity management system.

AWS References:

AWS IAM Identity Center Documentation

AWS Directory Service for Microsoft Active Directory Trust Relationships

AWS Directory Service Integration with IAM Identity Center

Why the other options are incorrect:

A. Create an Enterprise Edition Active Directory in AWS Directory Service: This would require setting up a new directory and managing it in AWS, which adds unnecessary overhead. The requirement is to continue using the existing on-premises AD, making this option unsuitable.

C. Use AWS Directory Service and create a two-way trust relationship: While this approach establishes a trust between on-premises AD and AWS Directory Service, it does not address the single sign-on (SSO) requirements across multiple AWS accounts through IAM Identity Center.

D. Deploy an identity provider (IdP) on Amazon EC2: This is more complex than necessary and introduces more management overhead. AWS IAM Identity Center natively supports integration with on-premises Active Directory without requiring a custom IdP.

Amazon Kinesis Data Streams is a scalable and reliable service that can ingest, buffer, and process streaming data in real-time. It can handle large traffic spikes and preserve the order ofthe incoming data records. AWS Lambda is a serverless compute service that can process the data streams from Kinesis Data Streams without requiring any infrastructure management. It can also scale automatically to match the throughput of the data stream. Amazon DynamoDB is a fully managed, highly available, and fast NoSQL database that can store the processed updates from Lambda. It can also handle high write throughput and provide consistent performance. By using these services, the solutions architect can design a solution that meets the requirements of the company with the least operational overhead.

it allows the company to monitor costs and notify responsible stakeholders in the event of unusual spending. By creating an AWS Cost Anomaly Detection monitor in the AWS Billing and Cost Management console, the company can use a machine learning service that automatically detects and alerts on anomalous spend. By configuring alert thresholds, notification preferences, and root cause analysis, the company can prevent unusual spending and identify its source. References:

AWS Cost Anomaly Detection

Creating a Cost Anomaly Monitor

Amazon EFS is a fully managed, elastic, and scalable file system that can be shared between multiple containers. It provides high availability and fault tolerance by replicating data across multiple Availability Zones. Amazon EFS is compatible with Amazon EKS and AWS Fargate, and can be registered in a StorageClass object on an EKS cluster. Amazon EBS volumes are not supported by AWS Fargate, and cannot be shared between multiple containers without using EBS Multi-Attach, which has limitations and performance implications. EBS Multi-Attach also requires the volumes to be in the same Availability Zone as the worker nodes, which reduces availability and fault tolerance. Synchronizing data between multiple EFS file systems using AWS Lambda is unnecessary, complex, and prone to errors. References:

Amazon EFS Storage Classes

Amazon EKSStorage Classes

Amazon EBS Multi-Attach

AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. You can use Lambda to create and test microservices that are written in Python or other supported languages. Lambda scales automatically to handle the number of requests per second. You only pay for the compute time you consume. Lambda also integrates with other AWS services, such as Amazon API Gateway, Amazon S3, Amazon DynamoDB, and Amazon SQS, to enable event-driven architectures. Lambda has minimal infrastructure andoperational overhead, as you do not need to manage servers, operating systems, patches, or scaling policies.

The other options are not serverless solutions and require more infrastructure and operational support. They also do not scale automatically to handle the number of requests per second. A Spot Fleet is a collection of EC2 instances that run on spare capacity at low prices. However, Spot Instances can be interrupted by AWS at any time, which can affect the availability and performance of your microservice. AWS Elastic Beanstalk is a service that automates the deployment and management of web applications on EC2 instances. However, you still need to provision, configure, and monitor the underlying EC2 instances and load balancers. Amazon EKS is a service that runs Kubernetes on AWS. However, you still need to create, configure, and manage the EC2 instances that form the Kubernetes cluster and nodes. You also need to install and update the Kubernetes software and tools.

Understanding the Requirement: The application is stateful and requires at least two EC2 instances to be running at all times, with a highly available and fault-tolerant architecture.

Analysis of Options:

Minimum capacity of two with instances in separate AZs: Ensures high availability by distributing instances across multiple AZs, fulfilling the requirement of always having two instances running.

Minimum capacity of four: Provides redundancy but is more than what is required and increases cost without additional benefit.

Spot Instances: Not suitable for a stateful application requiring guaranteed availability, as Spot Instances can be terminated at any time.

Combination of On-Demand and Spot Instances: Mixing instance types might provide cost savings but does not ensure the required availability for a stateful application.

Best Solution:

Minimum capacity of two with instances in separate AZs: This setup ensures high availability and meets the requirement with the least cost and complexity.

To provide access to the SQS queue to the other company without giving up its own account permissions, a solutions architect should create an SQS access policy that provides the other company access to the SQS queue. An SQS access policy is a resource-based policy that defines who can access the queue and what actions they can perform. The policy can specify the AWS account ID of the other company as a principal, and grant permissions for actions such as sqs:ReceiveMessage, sqs:DeleteMessage, and sqs:GetQueueAttributes. This way, the other company can poll the queue using its own credentials, without needing to assume a role or use cross-account access keys. References:

Using identity-based policies (IAM policies) for Amazon SQS

Using custom policies with the Amazon SQS access policy language

The least outstanding requests (LOR) algorithm is a load balancing algorithm that distributes incoming requests to the target with the fewest outstanding requests. This helps to avoid overloading any single target and improves the overall performance and availability of the web application. The LOR algorithmcan use the RequestCount and TargetResponseTime CloudWatch metrics to determine the number of outstanding requests and the response time of each target. These metrics measure the number of requests processed by each target and the time elapsed after the request leaves the load balancer until a response from the target is received by the load balancer, respectively. By using these metrics, the LOR algorithm can route new requests to the targets that are less busy and more responsive, and avoid sending requests to the targets that are already overloaded or slow. This solution meets the requirements of the company.

Deletion protection is a feature of DynamoDB that prevents accidental deletion of tables. When deletion protection is enabled, you cannot delete a table unless you explicitly disable it first. This adds an extra layer of security and reduces the risk of data loss and operational disruption. Deletion protection is easy to enable and disable using the AWS Management Console, the AWSCLI, or the DynamoDB API. This solution has the least operational overhead, as you do not need to create, manage, or invoke any additional resources or services. References:

Using deletion protection to protect your table

Preventing Accidental Table Deletion in DynamoDB

Amazon DynamoDB now supports table deletion protection

This combination of actions will provide high availability and minimum latency for global users by using AWS Global Accelerator and Application Load Balancers. AWS GlobalAccelerator is a networking service that helps you improve the availability, performance, and security of your internet-facing applications by using the AWS global network. It provides two global static public IPs that act as a fixed entry point to your application endpoints, such as Application Load Balancers, in multiple Regions1. Global Accelerator uses the AWS backbone network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure. It also offers TCP and UDP support, traffic encryption, and DDoS protection2. Application Load Balancers are external load balancers that distribute incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones. They support both HTTP and HTTPS (SSL/TLS) protocols, and offer advanced features such as content-based routing, health checks, and integration with other AWS services3. By creatingexternal Application Load Balancers in front of the application in each Region, you can ensure that the application can handle varying load patterns and scale on demand. By creating an AWS Global Accelerator accelerator to route traffic to the load balancers in each Region, you can leverage the performance, security, and availability of the AWS global network to deliver the best possible user experience.

This option is the most suitable way to improve the game’s metadata load times without migrating the database. Amazon ElastiCache for Redis is a fully managed, in-memory data store that provides sub-millisecond latency and high throughput for read-intensive workloads. You can use it as a caching layer in front of your RDS DB instance to store frequently accessed metadata and reduce the load on thedatabase. You can also take advantage of Redis features such as snapshots, replication, and data persistence to ensure data durability and availability. ElastiCache for Redis scales automatically to meet your demand and integrates with other AWS services such as CloudFormation, CloudWatch, and IAM.

Option A is not optimal because migrating the database to Amazon Aurora with Aurora Replicas would incur additional costs and complexity. Amazon Aurora is a relational database service that provides high performance, availability, and compatibility with MySQL and PostgreSQL. Aurora Replicas are read-only copies of the primary database that can be used for scaling read capacity and enhancing availability. However, migrating the database to Aurora would require modifying the application code, testing the compatibility, and performing the data migration. Moreover, Aurora Replicas may not provide sub-millisecond response times as ElastiCache for Redis does.

Option B is not optimal because migrating the database to Amazon DynamoDB with global tables would incur additional costs and complexity. Amazon DynamoDB is a NoSQL database service that provides fast and flexible data access for any scale. Global tables are a feature of DynamoDB that enables you to replicate your data across multiple AWS Regions for high availability and performance. However, migrating the database to DynamoDB would require changing the data model, modifying the application code, and performing the data migration. Moreover, global tables may not be necessary for the game’s metadata, as they are mainly used for cross-region data access and disaster recovery.

Option D is not optimal because adding an Amazon ElastiCache for Memcached layer in front of the database would not provide the same capabilities as ElastiCache for Redis. Amazon ElastiCache for Memcached is another fully managed, in-memory data store that provides high performance and scalability for caching workloads. However, Memcached does not support snapshots, replication, or data persistence, which means that the cached data may be lost in case of a node failure or a cache eviction. Moreover, Memcached does not integrate with other AWS services as well as Redis does. Therefore, ElastiCache for Redis is a better choice for this scenario. References:

What Is Amazon ElastiCache for Redis?

What Is Amazon Aurora?

What Is Amazon DynamoDB?

What Is Amazon ElastiCache for Memcached?

This solution meets the requirements because it uses the following components and features:

AdministratorAccess identity-based policy: This is an AWS managed policy that provides full access to AWSservices and resources1. By attaching this policy to the IAM user group, the solutions architect can grant the permissions needed for the designated employees to perform any task in the AWS account.

IAM user group: This is a collection of IAM users that share common permissions2. By creating a user group and adding the five designated employees as members, the solutions architect can simplify the management of permissions and reduce the risk of human errors or inconsistencies.

IAM users: These are identities that represent the designated employees in AWS2. By creating an IAM user for each employee and requiring them to sign in with their own credentials, the solutions architect can enhance the security and accountability of the AWS account.

https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Replication.html

#Aurora.Replication.Replicas Aurora Replicas have two main purposes. You can issue queries to them to scale the read operations for your application. You typically do so by connecting to the reader endpoint of the cluster. That way, Aurora can spread the load for read-only connections across as many Aurora Replicas as you have in the cluster. Aurora Replicas also help to increase availability. If the writer instance in a cluster becomes unavailable, Aurora automatically promotes one of the reader instances to take its place as the new writer.

https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Overview.html

This solution meets the requirements with the least operational overhead because it leverages the features of IAM Identity Center and AWS Control Tower to centrally manage multiple user permissions across all the accounts. By creating new groups and permission sets, the company can assign fine-grained permissions to the developer and administrator teams based on their roles and responsibilities. The permission sets are applied to the groups at the organization level, so they are automatically inherited by all the accounts in the organization. When new users are hired, the company only needs to add them to the appropriate group in IAM Identity Center, and they will automatically get the permissions assigned to that group. This simplifies the user management and reduces the manual effort of assigning permissions to each user individually.

This solution meets the requirements because it enables the company to observe the performance and behavior of its microservices-based application on Amazon EKS. Amazon CloudWatch Container Insights is a feature that collects, aggregates, and summarizes metrics and logs from containerized applications and microservices. Container Insights integrates with Amazon EKS and Kubernetes to provide metrics at the cluster, node, pod, task, and service level. You can use Container Insights to monitor the CPU, memory, disk, and network utilization of your EKS clusters and identify bottlenecks, latency spikes, and other issues. AWS X-Ray is a service that collects data about requests that your application serves, and provides tools that you can use to view, filter, and gain insights into that data. X-Ray integrates with Amazon EKS and Kubernetes to trace the requests that your microservices make to downstream AWS resources, microservices, databases, and web APIs. You can use X-Ray to analyze the root cause of errors, faults, and performance issues, and visualize the service map of your application.

This solution meets the following requirements:

It is cost-effective, as it only charges for the storage and data transfer of the replicated objects, and does not require any additional AWS services or custom scripts. S3 Same-Region Replication (SRR) is a feature that automatically replicates objects across S3 buckets within the same AWS Region. SRR can help you aggregate logs from multiple sources to a single destination for analysis and auditing. SRR also preserves the metadata, encryption, and access control of the source objects.

It is operationally efficient, as it does not require any manual intervention or scheduling. SRR replicates objects as soon as they are uploaded to the source bucket, ensuring that the destination bucket always has the latest log data. SRR also handles any updates or deletions of the source objects, keeping the destination bucket in sync. SRR can be enabled with a few clicks in the S3 console or with a simple API call.

It is secure, as it does not allow the logs to leave the us-west-2 Region. SRR only replicates objects within the same AWS Region, ensuring that the data sovereignty and compliance requirements are met. SRR also supports encryption of the source and destination objects, using either server-side encryption with AWS KMS or S3-managed keys, or client-side encryption.

B and D are the correct answers because they ensure that the Lambda execution role has the permissions to decrypt and use the environment variables, and that the AWS KMS key policy allows the Lambda execution role to use the key. The Lambda execution role is an IAM role that grants the Lambda function permission to access AWS resources, such as AWS KMS. The AWS KMS key policy is a resource-based policy that controls access to the key. By adding AWS KMS permissions in the Lambda execution role and allowing the Lambda execution role in the AWS KMS key policy, the solutions architect can implement the correct permissions for encrypting and decrypting environment variables. References:

AWS Lambda Execution Role

Using AWS KMS keys in AWS Lambda

To improve the architecture of this application, the best solution would be to use Amazon Simple Queue Service (Amazon SQS) to buffer the requests and decouple the S3 bucket from the Lambda function. This will ensure that the documents are not lost and can be processed at a later time if the Lambda function is not available. This will ensure that the documents are not lost and can be processed at a later time if the Lambda function is not available. By using Amazon SQS, the architecture is decoupled and the Lambda function can process the documents in a scalable and fault-tolerant manner

The most suitable design change for the company’s application is to request strongly consistent reads for the table. This change will ensure that the requests to the table return the latest data, reflecting the updates from all prior write operations.

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB supports two types of read consistency: eventually consistent reads and strongly consistent reads.By default, DynamoDB uses eventually consistent reads, unless users specify otherwise1.

Eventually consistent reads are reads that may not reflect the results of a recently completed write operation. The response might not include the changes because of the latency of propagating the data to all replicas. If users repeat their read request after a short time, the response should return the updated data.Eventually consistent reads are suitable for applications that do not require up-to-date data or can tolerate eventual consistency1.

Strongly consistent reads are reads that return a result that reflects all writes that received a successful response prior to the read. Users can request a strongly consistent read by setting the ConsistentRead parameter to true in their read operations, such as GetItem, Query, or Scan.Strongly consistent reads are suitable for applications that require up-to-date data or cannot tolerate eventual consistency1.

The other options are not correct because they do not address the issue of read consistency or are not relevant for the use case. Adding read replicas to the table is not correct because this option is not supported by DynamoDB. Read replicas are copies of a primary database instance that can serve read-only traffic and improve availability and performance.Read replicas are available for some relational database services, such as Amazon RDS or Amazon Aurora, but not for DynamoDB2. Using a global secondary index (GSI) is not correct because this option is not related to read consistency. A GSI is an index that has a partition key and an optional sort key that are different from those on the base table.A GSI allows users to query the data in different ways, with eventual consistency3. Requesting eventually consistent reads for the table is not correct because this option is already the default behavior of DynamoDB and does not solve the problem of requests not returning the latest data.

AWS Transfer Family is a secure transfer service that enables you to transfer files into and out of AWS storage services using SFTP, FTPS, FTP, and AS2 protocols. You can use AWS Transfer Family to create an SFTP-enabled server with a public endpoint that allows only trusted IP addresses. You can also attach an Amazon S3 bucket with default encryption enabled to the SFTP service endpoint, which will provide high IOPS performance and highly configurable security for your data at rest. You can also maintain control over user permissions by granting users access to the SFTP service using IAM roles or service-managed identities. References: https://docs.aws.amazon.com/transfer/latest/userguide/what-is-aws-transfer-family.htmlhttps://docs.aws.amazon.com/transfer/latest/userguide/create-server-s3.html

Client-side encryption is a method of encrypting data before uploading it to Amazon S3. It allows users to manage the encryption process, encryption keys, and related tools1. By using client-side encryption, the solution can ensure that the data is encrypted at rest andin transit, as Amazon S3 will not have access to the encryption keys or the unencrypted data2.

To achieve high availability for an application that runs on EC2 instances, the application should be deployed across multiple Availability Zones and use a load balancer to distribute traffic. An Auto Scaling group can be used to launch and manage EC2 instances in multiple Availability Zones and perform health checks on them. A Network Load Balancer can be used to handle transport layer traffic to the EC2 instances.

AWS WAF is a web application firewall that helps protect web applications from common web exploits that could affect application availability, compromise security, or consume excessive resources. AWS WAF allows users to create rules that block, allow, or count web requests based on customizable web security rules. One of the types of rules that can be created is an SQL injection rule, which allows users to specify a list of IP addresses or IP address ranges that they want to allow or block. By using AWS WAF to protect the application, the company can prevent SQL injection and other web-based attacks from reaching the application and the database.

RDS parameter groups are collections of parameters that define how a database instance operates. Users can modify the parameters in a parameter group to change the behavior and performance of the database. By using RDS parameter groups to configure the security settings, the company can enforce best practices such as disabling remote root login, requiring SSL connections, and limiting the maximum number of connections.

The other options are not correct because they do not effectively protect the application and the database from SQL injection and other web-based attacks. Using security groups and network ACLs to secure the database and application servers is not sufficient because they only filter traffic at the network layer, not at the application layer. Using AWS Network Firewall to protect the application and the database is not necessary because it is a stateful firewall service that provides network protection for VPCs, not for individual applications or databases. Using different database accounts in the application code for different functions is a good practice, but it does not prevent SQL injection attacks from exploiting vulnerabilities in the application code.

AWS Control Tower is a fully managed service that simplifies the setup and governance of a secure, compliant, multi-account AWS environment. It establishes a landing zone that is based on best-practices blueprints, and it enables governance using controls you can choose from a pre-packaged list. The landing zone is a well-architected, multi-account baseline that follows AWS best practices. Controls implement governance rules for security, compliance, and operations. AWS Security Hub is a service that provides a comprehensive view of your security posture across your AWS accounts. It aggregates, organizes, and prioritizes security alerts and findings from multiple AWS services, such as Amazon GuardDuty, Amazon Inspector, Amazon Macie, AWS Firewall Manager, and AWS IAM Access Analyzer, as well as from AWS Partner solutions. AWS Security Hub continuously monitors your environment using automatedcompliance checks based on the AWS best practices and industry standards, such as the AWS Foundational Security Best Practices (FSBP) standard. AWS Control Tower Account Factory is a feature that automates the provisioning of new AWS accounts that are preconfigured to meet your business, security, and compliance requirements. By deploying an AWS Control Tower environment in the Organizations management account, you can leverage the existing organization structure and policies, and enable AWS Security Hub and AWS Control Tower Account Factory in the environment. This way, you can audit all API calls and logins in any existing or new AWS account, monitor the compliance status of each account with the FSBP standard, and provision new accounts with ease and consistency. This solution meets the requirements with the least operational overhead, as you do not need to manage any infrastructure, perform any data migration, or submit any requests for changes.

This solution meets the requirements most cost-effectively because it leverages the serverless and event-driven capabilities of AWS Lambda and Amazon EventBridge. AWS Lambda allows you to run code without provisioning or managing servers, and you pay only for the compute time you consume. Amazon EventBridge is a serverless event bus service that lets you connect your applications with data from various sources and routes that data to targets such as AWS Lambda. By using Amazon EventBridge, you can create a rule that triggers a Lambda function to run the program when reports are requested, and you can also schedule the rule to run during the last week of each month. This way, you can generate reports in the least amount of time and pay only for the resources you use.

Amazon DocumentDB (with MongoDB compatibility) is a fast, reliable, and fully managed database service. Amazon DocumentDB makes it easy to set up, operate, and scale MongoDB-compatible databases in the cloud. With Amazon DocumentDB, you can run the same application code and use the same drivers and tools that you use with MongoDB.

https://docs.aws.amazon.com/documentdb/latest/developerguide/what-is.html

This solution will allow the company to host all three tiers on Amazon EC2 instances while using Amazon FSx for Windows File Server to provide Windows-based file sharing betweenthe tiers. This will allow the company to use specific features of SQL Server, such as native backups and Data Quality Services, while sharing files for processing between the tiers.

This answer is correct because it allows the web tier to access the database tier by using security groups as a source, which is a recommended best practice for VPC connectivity. Security groups are stateful and can reference other security groups in the same VPC, which simplifies the configuration and maintenance of the firewall rules. By adding an inbound rule to the database tier’s security group, the web tier’s EC2 instances can connect to the RDS instance on port 3306, regardless of their IP addresses or subnets.

To grant the necessary permissions to an AWS Lambda function to upload files to Amazon S3, a solutions architect should create an IAM execution role with the required permissions andattach the IAM role to the Lambda function. This approach follows the principle of least privilege and ensures that the Lambda function can only access the resources it needs to perform its specific task.

These two steps will meet the requirements with the fewest changes to the application because they will enable the company to replicate the data to the new S3 buckets and minimize latency for both video streaming and uploads. One-way replication from the us-east-2 S3 bucket to the other two S3 buckets will ensure that the data is synchronized across all three regions. The company can use S3 Cross-Region Replication (CRR) to automatically copy objects across buckets in different AWS Regions. CRR can help the company achieve lower latency and compliance requirements by keeping copies of their data in different regions. Creating an S3 Multi-Region Access Point and modifying the application to use its ARN will allow the company to access the data through a single global endpoint. An S3 Multi-Region Access Point is a globally unique name that can be used to access objects stored in S3 buckets across multiple regions. It automatically routes requests to the closest S3 bucket with the lowest latency. By using an S3 Multi-Region Access Point, the company can simplify the application architecture and improve the performance and reliability of the application.

The S3 Block Public Access feature allows you to restrict public access to S3 buckets and objects within the account. You can enable this feature at the account level to prevent any S3 bucket from being made public, regardless of the bucket policy settings. AWS Organizations can be used to apply a Service Control Policy (SCP) to the account to prevent IAM users from changing this setting, ensuring that all S3 objects remain private. This is a straightforward and effective solution that requires minimal operational overhead.

Enabling Amazon Elastic Block Store (Amazon EBS) fast snapshot restore on a snapshot allows you to quickly create a new Amazon Machine Image (AMI) from a snapshot, which can help reduce the initialization latency when provisioning new instances. Once the AMI is provisioned, you can replace the AMI in the Auto Scaling group with the new AMI. This will ensure that new instances are launched from the updated AMI and are able to meet the increased demand quickly.

Reserved is cheaper than on demand the company has. And it's meet the availabilty (HA) requirement as to spot instance that can be disrupted at any time. PRICING BELOW. On-Demand: 0% There’s no commitment from you. You pay the most with this option. Reserved : 40%-60%1-year or 3-year commitment from you. You save money from that commitment. Spot 50%-90% Ridiculously inexpensive because there’s no commitment from the AWS side.

This answer is correct because it provides a resilient and durable replacement for the on-premises file share that is compatible with a serverless web application. Amazon S3 is a fully managed object storage service that can store any amount of data and serve it over the internet. It supports the following features:

Resilience: Amazon S3 stores data across multiple Availability Zones within a Region, and offers 99.999999999% (11 9’s) of durability. It also supports cross-region replication, which enables automatic and asynchronous copying of objects across buckets in different AWS Regions.

Durability: Amazon S3 encrypts data at rest using server-side encryption with either Amazon S3-managed keys (SSE-S3), AWS KMS keys (SSE-KMS), or customer-provided keys (SSE-C). It also supports encryption in transit using SSL/TLS. Amazon S3 also provides data protection features such as versioning, which keeps multiple versions of an object in the same bucket, and MFA Delete, which requires additional authentication for deleting an object version or changing the versioning state of a bucket.

Performance: Amazon S3 delivers high performance and scalability for serving static and dynamic web content. It also supports features such as S3 Transfer Acceleration, which speeds up data transfers by routing requests to AWS edge locations, and S3 Select, which enables retrieving only a subset of data from an object by using simple SQL expressions.

The S3 Standard-Infrequent Access (S3 Standard-IA) storage class is suitable for storing images that are rarely accessed, but must be immediately available when needed. It offers the same high durability, throughput, and low latency as S3 Standard, but with a lower storage cost per GB and a higher per-request cost.

https://aws.amazon.com/blogs/networking-and-content-delivery/adding-http-security-headers-using-lambdaedge-and-amazon-cloudfront/

Amazon CloudFront is a global content delivery network (CDN) service that can securely deliver web content, videos, and APIs at scale. It integrates with Cognito for authentication and with Lambda@Edge for authorization, making it an ideal choice for serving web content globally. Lambda@Edge is a service that lets you run AWS Lambda functions globally closer to users, providing lower latency and faster response times. It can also handle authorization logic at the edge to secure content in CloudFront. For this scenario, Lambda@Edge can provide authorization for the web application while leveraging the low-latency benefit of running at the edge.

By configuring scheduled scaling, the solutions architect can set the Auto Scaling group to automatically scale up to the desired compute level at a specific time (IAM) when the batch job starts and then automatically scale down after the job is complete. This will allow the desired EC2 capacity to be reached quickly and also help in reducing the cost.

To migrate a MySQL database to AWS with compatibility and scalability, Amazon Aurora is a suitable option. Aurora is compatible with MySQL and can scale automatically with Aurora Auto Scaling. AWS Database Migration Service (AWS DMS) can be used to migrate the database from on-premises to Aurora with minimal downtime.

This option will scale up capacity faster in the morning to improve performance, but will still allow capacity to scale down during off hours. It achieves this as follows: • A target tracking action scales based on a CPU utilization target. By triggering at a lower CPU threshold in the morning, the Auto Scaling group will start scaling up sooner as traffic ramps up, launching instances before utilization gets too high and impacts performance. • Decreasing the cooldown period allows Auto Scaling to scale more aggressively, launching more instances faster until the target is reached. This speeds up the ramp-up of capacity. • However, unlike a scheduled action to set a fixed minimum/maximum capacity, with target tracking the group can still scale down during off hours based on demand. This helps minimize costs.

Deploy Amazon API Gateway as an HTTPS endpoint and AWS Lambda to process and save the messages to an Amazon DynamoDB table. This option provides a highly available and scalable solution that can easily handle large amounts of data. It also integrates with other AWS services, making it easier to analyze and visualize the data for the security team.

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/PrivateContent.html

Understanding the Requirement: The company needs to enable communication between VPCs across multiple AWS Regions with minimal administrative effort.

Analysis of Options:

VPC Peering: Managing multiple VPC peering connections across regions is complex and difficult to scale, leading to significant administrative overhead.

AWS Direct Connect Gateways: Primarily used for creating private connections between AWS and on-premises environments, not for inter-VPC communication across regions.

AWS Transit Gateway: Simplifies VPC interconnections within a region and supports Transit Gateway peering for cross-region connectivity, reducing administrative complexity.

AWS PrivateLink: Used for accessing AWS services and third-party services over a private connection, not for inter-VPC communication.

Best Solution:

AWS Transit Gateway with Transit Gateway Peering: This option provides a scalable and efficient solution for managing VPC communications both within a single region and across multiple regions with minimal administrative overhead.

Understanding the Requirement: Senior leadership wants a custom dashboard displaying NAT gateway costs daily, starting from the beginning of the current month.

Analysis of Options:

QuickSight with DataSync: While QuickSight is suitable for dashboards, DataSync is not designed for querying and analyzing data reports.

QuickSight with Athena: QuickSight can visualize data queried by Athena, which is designed to analyze data directly from S3.

CloudWatch with DataSync: CloudWatch is primarily for monitoring metrics, not for creating detailed cost analysis dashboards.

CloudWatch with Athena: Similarly, using CloudWatch with Athena does not align well with the requirement for a visual dashboard.

Best Solution for Visualization and Querying:

Amazon QuickSight with Athena: This combination allows for powerful data visualization and querying capabilities. QuickSight can create dynamic dashboards, while Athena efficiently queries the cost and usage report data stored in S3.

https://aws.amazon.com/efs/features/infrequent-access/

This answer is correct because it provides a resilient and durable replacement for the on-premises file share that is compatible with Windows IIS web servers. Amazon FSx for Windows File Server is a fully managed service that provides shared file storage built on Windows Server. It supports the SMB protocol and integrates with Microsoft Active Directory, which enables seamless access and authentication for Windows-based applications. Amazon FSx for Windows File Server also offers the following benefits:

Resilience: Amazon FSx for Windows File Server can be deployed in multiple Availability Zones, which provides high availability and failover protection. It also supports automatic backups and restores, as well as self-healing features that detect and correct issues.

Durability: Amazon FSx for Windows File Server replicates data within and across Availability Zones, and stores data on highly durable storage devices. It also supports encryption at rest and in transit, as well as file access auditing and data deduplication.

Performance: Amazon FSx for Windows File Server delivers consistent sub-millisecond latencies and high throughput for file operations. It also supports SSD storage, native Windows features such as Distributed File System (DFS) Namespaces and Replication, and user-driven performance scaling.

By purchasing a Compute Savings Plan, the company can save on the costs of running both EC2 instances and Lambda functions. The Lambda functions can be connected to the private subnet that contains the EC2 instances through a VPC endpoint for AWS services or a VPC peering connection. This provides direct network access to the EC2 instances while keeping the traffic within the private network, which helps to minimize network latency. Optimizing the Lambda functions’ duration, memory usage, number of invocations, and amount of data transferred can help to further minimize costs and improve performance. Additionally, using a private subnet helps to ensure that the EC2 instances are not directly accessible from the public internet, which is a security best practice.

Enforce column-level authorization with Amazon QuickSight and AWS Lake Formationhttps://aws.amazon.com/blogs/big-data/enforce-column-level-authorization-with-amazon-quicksight-and-aws-lake-formation/

The best solution to meet these requirements with the least amount of operational overhead is to enable Amazon DynamoDB Streams on the table and use triggers to write to a single AmazonSimple Notification Service (Amazon SNS) topic to which the teams can subscribe. This solution requires minimal configuration and infrastructure setup, and Amazon DynamoDB Streams provide a low-latency way to capture changes to the DynamoDB table. The triggers automatically capture the changes and publish them to the SNS topic, which notifies the internal teams.

This solution meets the requirement of reducing the number of database reads while ensuring high availability for a batch application that consists of a backend with multiple Amazon RDS databases. Amazon RDS read replicas are copies of the primary database instance that can serve read-only traffic. You can create one or more read replicas for a primary database instance and connect to them using a special endpoint. Read replicas can improve the performance and availability of your application by offloading read queries from the primary database instance.

Option B is incorrect because using Amazon ElastiCache for Redis can provide a fast, in-memory data store that can cache frequently accessed data, but it does not support replication from Amazon RDS databases. Option C is incorrect because using Amazon Route 53 DNS caching can improve the performance and availability of DNS queries, but it does not reduce the number of database reads. Option D is incorrect because using Amazon ElastiCache forMemcached can provide a fast, in-memory data store that can cache frequently accessed data, but it does not support replication from Amazon RDS databases.

This option is the most efficient because it uses aMulti-AZ deployment for the DB instance, which provides enhanced availability and durability for RDS database instances by automatically replicating the data to a standby instance in a different AvailabilityZone1. It also provides a recovery point objective (RPO) of less than 1 second for all its production databases, as the standby instance is kept in sync with the primary instanceusing synchronous physical replication2. This solution meets the requirement of requiring a RPO of less than 1 second for all its production databases. Option B is less efficientbecause it uses auto scaling for the DB instance in one Availability Zone, which is a way to automatically adjust the compute capacity of your DB instance based on load or a schedule3. However, this does not provide a RPO of lessthan 1 second for all its production databases, as it does not replicate the data to another Availability Zone. Option C is less efficient because it uses read replicas in a separate Availability Zone, which are read-only copies of your primary database that can serve read traffic and support scaling. However, this does not provide a RPO of less than 1 second for all its production databases, as read replicas use asynchronous replication and can lag behind the primary database. Option D is less efficient because it uses AWS Database Migration Service (AWS DMS) change data capture (CDC) tasks, which are tasks that capture changes made to source data and apply them to target data. However, this does not provide a RPO of less than 1 second for all its production databases, as AWS DMS uses asynchronous replication and can lag behind the source database.

https://aws.amazon.com/dynamodb/dax/

Q: What does Amazon RDS manage on my behalf?

Amazon RDS manages the work involved in setting up a relational database: from provisioning the infrastructure capacity you request to installing the database software. Once your database is up and running, Amazon RDS automates common administrative tasks such as performing backups and patching the software that powers your database. With optional Multi-AZ deployments, Amazon RDS also manages synchronous data replication across Availability Zones with automatic failover.

https://aws.amazon.com/rds/faqs/

**AWS PrivateLink provides private connectivity between VPCs, AWS services, and your on-premises networks, without exposing your traffic to the public internet**. AWS PrivateLink makes it easy to connect services across different accounts and VPCs to significantly simplify your network architecture. Interface **VPC endpoints**, powered by AWS PrivateLink, connect you to services hosted by AWS Partners and supported solutions available in AWS Marketplace. https://aws.amazon.com/privatelink/

Create a t2 micro Amazon EC2 instance. Deploy a LAMP (Linux Apache MySQL, PHP/Perl/Python) stack to host the webpage. Use client-side scripting to build the contact form. Integrate the form with Amazon WorkMail. This solution will provide the company with the necessary components to host the contact form page and integrate it with Amazon WorkMail at the lowest cost. Option A requires the use of Amazon ECS, which is more expensive than EC2, and Option B requires the use of Amazon API Gateway, which is also more expensive than EC2. Option C requires the use of Amazon Lightsail, which is more expensive than EC2.

Using AWS Lambda with Amazon API Gateway - AWS Lambda

https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway.html

AWS Lambda FAQs

https://aws.amazon.com/lambda/faqs/

A NAT gateway is a type of network address translation (NAT) device that enables instances in a private subnet to connect to the internet or other AWS services, butprevents the internet from initiating connections with those instances1. A NAT gateway is a managed service that requiresminimal operational maintenance and can handle up to 45Gbps of bursty traffic1. A NAT gateway is suitable for scenarios where EC2 instances inprivate subnets need to communicate with a license server over the internet, such as the three-tier web application in the scenario1.

To meet the requirements of the scenario, the solutions architect should provision a NAT gateway in a public subnet. The solutions architect should also modify each private subnet’s route table with a default route that points to the NAT gateway1. This way, the EC2 instances that run in private subnets can access the license server over the internet through the NAT gateway.

Since the application has no local data on instances, AMIs alone can meet the RPO by restoring instances from the most recent AMI backup. When combined with automated RDS backups for the database, this provides a complete backup solution for this environment. The other options involving EBS snapshots would be unnecessary given the stateless nature of the instances. AMIs provide all the backup needed for the app tier. This uses native, automated AWS backup features that require minimal ongoing management: - AMI automated backups provide point-in-time recovery for the stateless app tier. - RDS automated backups provide point-in-time recovery for the database.

https://docs.aws.amazon.com/apigateway/latest/developerguide/apigateway-integrate-with-cognito.html

To control access to the REST API and reduce development efforts, the company can use an Amazon Cognito user pool authorizer in API Gateway. This will allow Amazon Cognito to validate each request and ensure that only authenticated users can access the API. This solution has the LEAST operational overhead, as it does not require the company to develop and maintain any additional infrastructure or code.

This solution satisfies the requirements in the following ways:

• AWS Backup will automatically take full backups of the DynamoDB table on the schedule defined in the backup plan (the first of each month).

• The lifecycle policy can transition backups to cold storage after 6 months, meeting that requirement.

• Setting a 7-year retention period in the backup plan will ensure each backup is retained for 7 years as required.

• AWS Backup manages the backup jobs and lifecycle policies, requiring no custom scripting or management.

This solution meets the requirements of creating digital copies for a large collection of historical written records, analyzing the documents, extracting the medical information, and storing the documents so that an application can run SQL queries on the data. Writing the document information to an Amazon S3 bucket can provide scalable and durable storage for the scanned files. Using Amazon Athena to query the data can provide serverless and interactive SQL analysis on data stored in S3. Creating an AWS Lambda function that runs when new documents are uploaded can provide event-driven and serverless processing of the scanned files. Using Amazon Textract to convert the documents to raw text can provide accurate optical character recognition (OCR) and extraction of structured data such as tables and forms from documents using artificial intelligence (AI). Using Amazon Comprehend Medical to detect and extract relevant medical information from the text can provide natural language processing (NLP) service that uses machine learning that has been pre-trained to understand and extract health data from medical text.

Option A is incorrect because writing the document information to an Amazon EC2 instance that runs a MySQL database can increase the infrastructure overhead and complexity, and it may not be able to handle large volumes of data. Option C is incorrect because creating an Auto Scaling group of Amazon EC2 instances to run a custom application that processes the scanned files and extracts the medical information can increase the infrastructure overhead and complexity, and it may not be able to leverageexisting AI and NLP services such as Textract and Comprehend Medical. Option D is incorrect because using Amazon Rekognition to convert the documents to raw text can provide image and video analysis, but it does not support OCR or extraction of structured data from documents. Using Amazon Transcribe Medical to detect and extract relevant medical information from the text can provide speech-to-text transcription service for medical conversations, but it does not support text analysis or extraction of health data from medical text.

https://www.omnicalculator.com/other/data-transfer

- First 30 days- data access every morning ( predictable and frequently) – S3 standard - After 30 days, accessed 4 times a year – S3 infrequently access - Data preserved- S3 Gllacier Deep Archive

• Amazon S3 for large-scale, durable, and inexpensive storage of the video content. S3 storage costs are significantly lower than EFS. • Amazon EBS only temporarily during processing. By mounting an EBS volume only when a video needs to be processed, and unmounting it after, the time the content spends on the higher-cost EBS storage is minimized. • The EBS volume can be sized to match the workload needs for active processing, keeping costs lower. The volume does not need to store the entire video library long-term.

Send the outbound connection from EC2 to Network Firewall. In Network Firewall, create stateful outbound rules to allow certain domains for software patch download and deny all otherdomains.https://docs.aws.amazon.com/network-firewall/latest/developerguide/suricata-examples.html#suricata-example-domain-filtering

Amazon FSx for Windows File Server (Amazon FSx) is a fully managed, highly available, and scalable file storage solution built on Windows Server that uses the Server Message Block (SMB) protocol. It allows for Microsoft Active Directory integration, data deduplication, and fully managed backups, among other critical enterprise features.https://aws.amazon.com/blogs/storage/accessing-smb-file-shares-remotely-with-amazon-fsx-for-windows-file-server/

 Security groups are virtual firewalls that protect AWS instances and can be applied to EC2, ELB and RDS1. Security groups have rules for inbound and outbound traffic and are stateful, meaning that responses to allowed inbound traffic are allowed to flow out of the instance2. Network ACLs are different from security groups in several ways. They cover entire subnets, not individual instances, and are stateless, meaning that they require rules for both inbound and outbound traffic2. Network ACLs also support deny rules, while security groups only support allow rules2.

To meet the requirements of the scenario, the solutions architect should create two security groups: one for the DB instance and one for the web servers in the public subnet. The security group for the DB instance should allow traffic from the public subnet CIDR block on port 3306, which is the default port for MySQL3. This way, only the web servers in the public subnet can access the DB instance on that port. The security group for the web servers should allow traffic from 0 0 0 O’O on port 443, which is the default port forHTTPS4. This way, the web servers can accept secure connections from the internet on that port.

To encrypt data at rest in Amazon RDS, you can use the encryption feature of Amazon RDS, which uses AWS Key Management Service (AWS KMS). With this feature, Amazon RDS encrypts each database instance with a unique key. This key is stored securely by AWS KMS. You can manage your own keys or use the default AWS-managed keys. When you enable encryption for a DB instance, Amazon RDS encrypts the underlying storage, including the automated backups, read replicas, and snapshots.

To minimize development changes while moving the application to AWS and to ensure a high level of availability, the company can rehost the application in AWS Elastic Beanstalk with the .NET platform in a Multi-AZ deployment. This will allow the application to run in a highly available environment without requiring any changes to the application code.

The company can also use AWS Database Migration Service (AWS DMS) to migrate the Oracle database to Oracle on Amazon RDS in a Multi-AZ deployment. This will allow the company to maintain the existing database platform while still achieving a high level of availability.

Amazon Transcribe now supports speaker labeling for streaming transcription. Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for you to convert speech-to-text. In live audio transcription, each stream of audio may contain multiplespeakers. Now you can conveniently turn on the ability to label speakers, thus helping to identify who is saying what in the output transcript.https://aws.amazon.com/about-aws/whats-new/2020/08/amazon-transcribe-supports-speaker-labeling-streaming-transcription/

The most efficient solution for automatically starting and stopping EC2 instances and DB instances on a schedule while minimizing cost and infrastructure maintenance is to create an AWS Lambda function and configure Amazon EventBridge to invoke the function on a schedule.

Option A, scaling EC2 instances by using elastic resize and scaling DB instances to zero outside of business hours, is not feasible as DB instances cannot be scaled to zero.

Option B, exploring AWS Marketplace for partner solutions, may be an option, but it may not be the most efficient solution and could potentially add additional costs.

Option C, launching another EC2 instance and configuring a crontab schedule to run shell scripts that will start and stop the existing EC2 instances and DB instances on a schedule, adds unnecessary infrastructure and maintenance.

Understanding the Requirement: The company has petabytes of data in S3 Standard across multiple buckets with varying access frequencies. They do not know the access patterns and need a cost-optimized storage solution with minimal operational effort.

Analysis of Options:

S3 Intelligent-Tiering: This storage class automatically moves data between two access tiers (frequent and infrequent) based on changing access patterns. It incurs a small monitoring and automation charge but eliminates the need to manually move data between storage classes.

S3 Storage Class Analysis Tool: While useful for determining access patterns, this tool requires manual intervention to move objects to the appropriate storage class, which increases operational overhead.

S3 Glacier Instant Retrieval: This storage class is designed for data that is rarely accessed but requires instant retrieval when needed. It may not be suitable for data with unknown and varying access patterns.

S3 One Zone-IA: This is a lower-cost option for infrequently accessed data stored in a single availability zone. It does not provide the same level of durability and availability as other options and requires knowledge of access patterns.

Best Option for Operational Efficiency:

S3 Intelligent-Tiering provides the best balance of cost savings and operational efficiency. It dynamically adjusts to access patterns without manual intervention, ensuring the company is only paying for what they need without the risk of incurring high costs for infrequent access data.

RDS supported Storage > https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html GP2 max IOPS >https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/general-purpose.html#gp2-performance

Amazon RDS provides three storage types: General Purpose SSD (also known as gp2 and gp3), Provisioned IOPS SSD (also known as io1), and magnetic (also known as standard).They differ in performance characteristics and price, which means that you can tailor your storage performance and cost to the needs of your database workload. You can create MySQL,MariaDB, Oracle, and PostgreSQL RDS DB instances with up to 64 tebibytes (TiB) of storage. You can create SQL Server RDS DB instances with up to 16 TiB of storage. For this amount of storage, use the Provisioned IOPS SSD and General Purpose SSD storage types.https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html

To resize images dynamically and serve appropriate formats to clients, a Lambda@Edge function with an external image management library can be used. Lambda@Edge allows running custom code at the edge locations of CloudFront, which can process the images on the fly and optimize them for different devices and browsers. An external image management library can provide various image manipulation and optimization features.

https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/three-aws-glue-etl-job-types-for-converting-data-to-apache-parquet.html

https://medium.com/awesome-cloud/aws-difference-between-multi-az-and-read-replicas-in-amazon-rds-60fe848ef53a

The most suitable solution for the company’s requirements is to configure AWS Glue DataBrew to transform the data and share the transformation steps with employees by using DataBrew recipes. This solution will provide a prebuilt solution for data transformation that does not require code, and will also provide data lineage and data profiling. The company can easily share the data transformation steps with employees throughout the company by using DataBrew recipes.

AWS Glue DataBrew is a visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data for analytics or machine learning by up to 80% faster. Users can upload their data from various sources, such as Amazon S3, Amazon RDS, Amazon Redshift, Amazon Aurora, or Glue Data Catalog, and use a point-and-click interface to apply over 250 built-in transformations. Users can also preview the results of each transformation step and see how it affects the quality and distribution of the data1.

A DataBrew recipe is a reusable set of transformation steps that can be applied to one or more datasets. Users can create recipes from scratch or use existing ones from the DataBrew recipe library. Users can also export, import, or share recipes with other users or groups within their AWS account or organization2.

DataBrew also provides data lineage and data profiling features that help users understand and improve their data quality. Data lineage shows the source and destination of each dataset and how it is transformed by each recipe step. Data profiling shows various statistics and metrics about each dataset, such as column

Understanding the Requirement: The company needs to ensure clients use a TLS certificate when accessing the website and automate the creation and renewal of TLS certificates.

Analysis of Options:

CloudFront Security Policy: Not applicable for creating certificates.

CloudFront Origin Access Control (OAC): Controls access to origins, not relevant for TLS certificate creation.

AWS Certificate Manager (ACM) with DNS Validation: Provides automated certificate management, including creation and renewal, with minimal manual intervention. DNS validation is automated and does not require manual intervention as email validation does.

AWS Certificate Manager (ACM) with Email Validation: Requires manual intervention to approve validation emails, which increases operational effort.

Best Solution:

AWS Certificate Manager (ACM) with DNS Validation: Ensures automated and efficient certificate management with the least operational effort.

This answer is correct because it meets the requirements of transitioning to an event-driven architecture, using serverless concepts, and minimizing operational overhead. AWS Step Functions is a serverless service that lets you coordinate multiple AWS services into workflows using state machines. State machines are composed of tasks and transitions that define the logic and order of execution of the workflow steps. AWS Lambda is a serverless function-as-a-service platform that lets you run code without provisioning or managing servers. Lambda functions can be invoked by Step Functions as tasks in a state machine, and can perform different aspects of the data management workflow, such as data ingestion, transformation, validation, and analysis. By using Step Functions and Lambda, the company can benefit from the following advantages:

Event-driven: Step Functions can trigger Lambda functions based on events, such as timers, API calls, or other AWS service events. Lambda functions can also emit events to other services or state machines, creating an event-driven architecture.

Serverless: Step Functions and Lambda are fully managed by AWS, so the company does not need to provision or manage any servers or infrastructure. The company only pays for the resources consumed by the workflows and functions, and can scale up or down automatically based on demand.

Operational overhead: Step Functions and Lambda simplify the development and deployment of workflows and functions, as they provide built-in features such as monitoring, logging, tracing, error handling, retry logic, and security. The company can focus on the business logic and data processing rather than the operational details.

https://aws.amazon.com/blogs/networking-and-content-delivery/deliver-your-apps-dynamic-content-using-amazon-cloudfront-getting-started-template/

A read replica is a copy of the primary database that supports read-only queries. By creating a read replica, you can offload the read workload from the primary database and improve its performance. The script can query the read replica without affecting the critical application that uses the primary database. This solution also has the least operational overhead, as you do not need to modify the script, export the data manually, or manage a cache cluster. References:

Working with PostgreSQL, MySQL, and MariaDB Read Replicas

Amazon RDS Performance Insights

Requirement Analysis: The goal is to migrate from Microsoft SQL Server to Amazon Aurora PostgreSQL with minimal application code changes.

Babelfish for Aurora PostgreSQL: Babelfish allows Aurora PostgreSQL to understand SQL Server queries natively, reducing the need for application code changes.

AWS Schema Conversion Tool (SCT): This tool helps in converting the database schema from SQL Server to PostgreSQL.

AWS Database Migration Service (DMS): DMS can be used to migrate data from SQL Server to Aurora PostgreSQL seamlessly.

Combined Approach: Enabling Babelfish addresses the SQL query compatibility, while SCT and DMS handle the schema and data migration.

References

Babelfish for Aurora PostgreSQL:Babelfish Documentation

AWS SCT and DMS:AWS Database Migration Service

Understanding the Requirement: The company needs to migrate applications to AWS, maintaining isolated networks while allowing communication with a shared services VPC and among the applications.

Analysis of Options:

Software VPN Tunnels: This approach involves high administrative overhead and complexity in managing multiple VPN connections.

VPC Peering: While suitable for smaller numbers of VPCs, it becomes complex and hard to manage at scale with over 100 applications.

Direct Connect: Primarily used for high-bandwidth, low-latency connections to on-premises networks, not inter-VPC communication.

Transit Gateway: Simplifies network management by acting as a central hub, allowing easy routing and scalability as more applications are migrated.

Best Solution:

Transit Gateway: This provides a scalable, efficient solution with minimal administrative overhead for managing network connections between multiple VPCs and the shared services VPC.

Understanding the Requirements: The company needs to optimize costs and has the flexibility to change EC2 instance types and families frequently (every 2-3 months).

Savings Plans Overview: Savings Plans offer significant savings over On-Demand pricing, with the flexibility to use any instance type and family within a region.

No Upfront Compute Savings Plan: This plan allows for cost optimization without any upfront payment, offering flexibility to change instance types and families.

Term Selection: A 1-year term is appropriate for balancing cost savings and flexibility given the frequent changes in instance types.

Conclusion: A No Upfront Compute Savings Plan for a 1-year term provides the needed flexibility and cost savings without the commitment and inflexibility of Reserved Instances.

References

AWS Savings Plans:AWS Savings Plans

AWS Cost Management Documentation:AWS Cost Management

AWS Outposts is a fully managed service that delivers AWS infrastructure and services to virtually any on-premises or edge location for a consistent hybrid experience. AWS Outposts supports Amazon EKS, which is a managed service that makes it easy to run Kubernetes on AWS and on-premises. By installing an AWS Outposts rack in the company’s data center, the company can run containers in a Kubernetes environment using Amazon EKS and other AWS managed services, while keeping the data locally in the company’s data center and meeting the compliance requirements. AWS Outposts also provides a seamless connection to the local AWS Region for access to a broad range of AWS services.

Option A is not a valid solution because AWS Local Zones are not deployed in the company’s data center, but in large metropolitan areas closer to end users. AWS Local Zones are owned, managed, and operated by AWS, and they provide low-latency access to the public internet and the local AWS Region. Option B is not a valid solution because AWS Snowmobile is a service that transports exabytes of data to AWS using a 45-foot long ruggedized shipping container pulled by a semi-trailer truck. AWS Snowmobile is not designed for running containers or AWS managed services on-premises, but for large-scale data migration. Option D is not a valid solution because AWS Snowball Edge Storage Optimized is a device that provides 80 TB of HDD or 210 TB of NVMe storage capacity for data transfer and edge computing. AWS Snowball Edge Storage Optimized does not support Amazon EKS or other AWS managed services, and it is not suitable for running containers in a Kubernetes environment.

Understanding the Requirement: The company anticipates a spike in traffic during a holiday and wants to ensure the Auto Scaling group can handle the increased load without impacting performance.

Analysis of Options:

CloudWatch Alarm: This reacts to spikes based on metrics like CPU utilization but does not proactively scale before the anticipated demand.

Recurring Scheduled Action: This allows the Auto Scaling group to scale up based on a known schedule, ensuring additional capacity is available before the expected spike.

Increase Min/Max Instances: This could result in unnecessary costs by maintaining higher capacity even when not needed.

SNS Notification: Alerts on scaling events but does not proactively manage scaling to prevent performance issues.

Best Solution for Proactive Scaling:

Create a recurring scheduled action: This approach ensures that the Auto Scaling group scales up before the peak demand, providing the necessary capacity proactively without manual intervention.

Understanding the Requirement: The company needs to automate inventory and updates of diverse OS versions on EC2 instances and summarize common vulnerabilities for monthly reviews.

Analysis of Options:

Systems Manager Patch Manager and Security Hub: Patch Manager automates patching, but Security Hub is more focused on compliance and security posture rather than inventory and vulnerability management.

Systems Manager Patch Manager and Amazon Inspector: Patch Manager automates OS updates, and Amazon Inspector provides vulnerability assessments, making this a comprehensive solution for the requirements.

AWS Shield Advanced and AWS Config: Shield Advanced is for DDoS protection, not suitable for OS patch management and vulnerability reporting.

Amazon GuardDuty and AWS Config: GuardDuty is for threat detection and monitoring, not specifically for patch management and vulnerability assessments.

Best Solution:

Systems Manager Patch Manager and Amazon Inspector: This combination automates OS updates and provides detailed vulnerability assessments, meeting both the inventory and security reporting needs effectively.

Understanding the Requirement: The company wants to restrict each application to its specific prefix in an S3 bucket and have granular control over the objects under each prefix.

Analysis of Options:

Dedicated S3 Access Points: Provides a scalable and flexible way to manage access to S3 buckets, allowing specific policies to be attached to each access point, thereby controlling access at the prefix level.

S3 Batch Operations: Suitable for large-scale changes but involves more operational overhead and does not dynamically control future access.

Replication to new S3 buckets: Involves unnecessary duplication of data and increased storage costs, and operational overhead for managing multiple buckets.

Combination of replication and access points: Adds unnecessary complexity and overhead compared to using access points directly.

Best Solution:

Dedicated S3 Access Points: This provides the least operational overhead while meeting the requirements for prefix-level access control and granular management.

Understanding the Requirement: The company wants to centrally collect security data with minimal development effort to assess and improve security across all workloads.

Analysis of Options:

Amazon Security Lake: This is a purpose-built service for centralizing security data from across AWS services and third-party sources into a data lake. It provides native integration and requires minimal development effort to set up.

AWS Lake Formation with AWS Glue: While this can be used to create a data lake, it requires more development effort to set up and configure Glue crawlers for ingestion.

AWS Lambda with S3: This approach involves custom development to collect and process security data before storing it in S3, which requires more effort.

AWS DMS to RDS: AWS Database Migration Service is typically used for database migrations and is not suited for collecting and analyzing security data.

Best Option for Minimal Development Effort:

Amazon Security Lake provides the least development effort for setting up a centralized repository for security data. It simplifies data ingestion and management, making it the most efficient solution for this use case.

Understanding the Requirement: The company wants to migrate an application to AWS, increase its availability, and use AWS WAF in the architecture.

Analysis of Options:

Auto Scaling group with ALB and WAF: This option provides high availability by distributing instances across multiple Availability Zones. The ALB ensures even traffic distribution, and AWS WAF provides security at the application layer.

Cluster placement group with ALB and WAF: Cluster placement groups are for low-latency networking within a single AZ, which does not provide the high availability across AZs.

Two EC2 instances with ALB and WAF: This setup provides some availability but does not scale automatically, missing the benefits of an Auto Scaling group.

Auto Scaling group with WAF directly: AWS WAF cannot be directly connected to an Auto Scaling group; it needs to be attached to an ALB, CloudFront distribution, or API Gateway.

Best Solution:

Auto Scaling group with ALB and WAF: This configuration ensures high availability, scalability, and security, meeting all the requirements effectively.

Understanding the Requirement: The company needs to automatically detect and respond to suspicious or unexpected behavior in its AWS environment, beyond the existing AWS WAF setup.

Analysis of Options:

Amazon GuardDuty: Provides continuous monitoring and threat detection across AWS accounts and resources, including integration with AWS WAF for automated response.

AWS Firewall Manager: Manages firewall rules across multiple accounts but is more focused on central management than threat detection.

Amazon Inspector: Focuses on security assessments and vulnerability management rather than real-time threat detection.

Amazon Macie: Primarily used for data security and privacy, not comprehensive threat detection.

Best Solution:

Amazon GuardDuty with EventBridge and Lambda: This combination ensures continuous threat detection and automated response by updating AWS WAF rules based on GuardDuty findings.

Understanding the Requirement: The company needs logs to be highly available for 30 days for frequent analysis, retained for an additional 60 days for backup, and deleted after 90 days.

Analysis of Options:

Transition to S3 Standard after 30 days: Keeps logs in the same high-availability storage, not cost-effective.

Transition to S3 Standard-IA, then Glacier Flexible Retrieval after 90 days: Adds unnecessary cost and complexity since objects need to be accessible for only 30 days and then retained for 60 days.

Transition to Glacier Flexible Retrieval after 30 days: Not suitable for frequent access required in the first 30 days.

Transition to S3 One Zone-IA after 30 days, then Glacier Flexible Retrieval: Provides cost-effective storage for infrequently accessed logs after the initial 30-day period, then moves to the cheapest long-term storage before deletion.

Best Solution:

Transition to S3 One Zone-IA after 30 days, then Glacier Flexible Retrieval: This solution meets the requirements for high availability, cost-effective storage for backup, and scheduled deletion with the least cost.

Understanding the Requirement: The job is stateful, cannot tolerate interruptions, and needs to run reliably for at least one hour each week.

Analysis of Options:

AWS Fargate with Amazon ECS and EventBridge: This option provides a serverless compute engine for containers that can run stateful tasks reliably. Using EventBridge Scheduler, the job can be triggered automatically at the specified time without manual intervention.

AWS Lambda with EventBridge: Lambda functions are not suitable for long-running stateful jobs since they have a maximum execution time of 15 minutes.

EC2 Spot Instances: Spot Instances can be interrupted, making them unsuitable for a stateful job that cannot tolerate interruptions.

AWS DataSync: This service is primarily for moving large amounts of data and is not designed to run stateful analysis jobs.

Best Option for Reliable, Scheduled Execution:

The Fargate task on ECS with EventBridge Scheduler meets all requirements, providing the necessary reliability and scheduling capabilities without interruption risks.

Requirement Analysis: The company needs highly available, scalable storage for a document management application without modifying the application during migration.

EFS Overview: Amazon EFS provides scalable file storage that can be mounted concurrently on multiple EC2 instances across different Availability Zones.

EFS Standard-IA: Using the Standard-IA storage class helps reduce costs for infrequently accessed data while maintaining high availability and scalability.

Implementation:

Create an EFS file system.

Configure mount targets in multiple Availability Zones to ensure high availability.

Mount the EFS file system on EC2 instances in the Auto Scaling group.

Conclusion: This solution meets the high availability, scalability, and cost-effectiveness requirements without needing application modifications.

References

Amazon EFS:Amazon EFS Documentation

EFS Storage Classes:Amazon EFS Storage Classes

Understanding the Requirement: The company needs programmatic access to its AWS usage costs for the current year and cost forecasts for the next 12 months, with minimal operational overhead.

Analysis of Options:

AWS Cost Explorer API: Provides programmatic access to detailed usage and cost data, including forecast costs. It supports pagination for handling large datasets, making it an efficient solution.

Downloadable AWS Cost Explorer report csv files: While useful, this method requires manual handling of files and does not provide real-time access.

AWS Budgets actions via FTP: This is less suitable as it involves setting up FTP transfers and does not provide the same level of detail and real-time access as the API.

AWS Budgets reports via SMTP: Similar to FTP, this method involves additional setup and lacks the real-time access and detail provided by the API.

Best Option for Minimal Operational Overhead:

AWS Cost Explorer API provides direct, programmatic access to cost data, including detailed usage and forecasting, with minimal setup and operational effort. It is the most efficient solution for integrating cost data into an operational cost dashboard.

EBS encryption by default is a feature that enables encryption for all new EBS volumes and snapshots created in a Region1. EBS encryption by default uses a service managed key or a customer managed key that is stored in AWS KMS1. EBS encryption by default is suitable for scenarios where data at rest must be encrypted by using a customer managed key, such as the digital media streaming application in the scenario1.

To meet the requirements of the scenario, the solutions architect should enable EBS encryption by default in the AWS Region where the EKS cluster will be created. The solutions architect should select the customer managed key as the default key for encryption1. This way, all newEBS volumes and snapshots created in that Region will be encrypted by using the customer managed key.

EKS encryption provider support is a feature that enables envelope encryption of Kubernetes secrets in EKS with a customer managed key that is stored in AWS KMS2. Envelope encryption means that data is encrypted by data encryption keys (DEKs) using AES-GCM; DEKs are encrypted by key encryption keys (KEKs) according to configuration in AWS KMS3. EKS encryption provider support is suitable for scenarios where secrets must be encrypted by using a customer managed key, such as the digital media streaming application in the scenario2.

To meet the requirements of the scenario, the solutions architect should create the EKS cluster and create an IAM role that has a policy that grants permission to the customer managed key. The solutions architect should associate the role with the EKS cluster2. This way, the EKS cluster can use envelope encryption of Kubernetes secrets with the customer managed key.

We recommend that you use On-Demand Instances for applications with short-term, irregular workloads that cannot be interrupted.https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-on-demand-instances.html

Understanding the Requirement: The company needs to collect transaction data in real time, avoid data duplication, and perform additional processing without managing infrastructure.

Analysis of Options:

SQS FIFO Queue with Lambda: Ensures data is processed in order and prevents duplication.Lambda handles processing without the need to manage servers.

SQS FIFO Queue with AWS Batch: While this ensures no duplicates, it introduces additional complexity and management overhead with AWS Batch.

Kinesis Data Streams with AWS Batch and EC2: Involves more components and infrastructure management, which is against the requirement of not wanting to manage infrastructure.

Step Functions with Lambda and EC2: Involves setting up multiple services and still requires managing EC2 instances, increasing complexity.

Best Solution:

SQS FIFO Queue with Lambda: This combination ensures real-time data processing, prevents duplication, and minimizes infrastructure management, meeting all requirements efficiently.

To make the application highly available across regions:

Deploy the application in a different region using a newECS clusterandALBto ensure regional redundancy.

UseRoute 53 failover routingto automatically direct traffic to the healthy region in case of failure.

UseDynamoDB Global Tablesto ensure the database is replicated and available across multiple regions, supporting read and write operations in each region.

Option D (EKS cluster in the same region): This does not provide regional redundancy.

Option E (Global Secondary Indexes): GSIs improve query performance but do not provide multi-region availability.

Option F (PrivateLink): PrivateLink is for secure communication, not for cross-region high availability.

AWS References:

DynamoDB Global Tables

Amazon ECS with ALB

The solution that will meet the requirements is to run the application on Amazon Elastic Container Service (Amazon ECS) as microservices with service auto scaling. This solution will allow the application to be flexible, scalable, and gradually improved, as well as minimize application downtime. By breaking down the monolithic application into microservices, the company can decouple the modules and update them independently, without affecting the whole application. By running the microservices on Amazon ECS, the company can leverage the benefits of containerization, such as portability, efficiency, and isolation. By enabling service auto scaling, the company can adjust the number of containers running for each microservice based on demand, ensuring optimal performance and cost. Amazon ECS also supports various deployment strategies, such as rolling update or blue/green deployment, that can reduce or eliminate downtime during updates.

The other solutions are not as effective as the first one because they either do not meet the requirements or introduce new challenges. Running the application on AWS Lambda as a single function with maximum provisioned concurrency will not meet the requirements, as it will not break down the monolith into microservices, nor will it reduce the complexity of maintenance. Lambda functions are also limited by execution time (15 minutes), memory size (10 GB), and concurrency quotas, which may not be sufficient for the report generation application. Running the application on Amazon EC2 Spot Instances as microservices with a Spot Fleet default allocation strategy will not meet the requirements, as it will introduce the risk of interruptions due to spot price fluctuations. Spot Instances are not guaranteed to be available or stable, and may be reclaimed by AWS at any time with a two-minute warning. This may cause report generation to fail or restart from scratch. Running the application on AWS Elastic Beanstalk as a single application environment with an all-at-once deployment strategy will not meet the requirements, as it will not break down the monolith into microservices, nor will it minimize application downtime. The all-at-once deployment strategy will deploy updates to all instances simultaneously, causing a brief outage for the application.

Requirement Analysis: The goal is to prevent accidental deletion of EBS snapshots while avoiding indefinite retention.

Recycle Bin for EBS Snapshots: AWS Recycle Bin allows for retention rules that prevent immediate deletion of snapshots, providing a safety net against accidental deletions.

Retention Rule: A 7-day retention rule ensures snapshots are not permanently deleted immediately, giving time to recover from accidental deletions.

Implementation:

Enable Recycle Bin in your AWS account.

Create a retention rule that specifies a 7-day period for EBS snapshots.

Apply this rule to all EBS snapshots.

Conclusion: This solution provides an automated way to prevent data loss from accidental deletions with minimal development effort.

References

AWS Recycle Bin:AWS Recycle Bin Documentation

This option is the most cost-effective way to reduce the S3 storage costs in this situation. Incomplete multipart uploads are parts of objects that are not completed or aborted by the application. They consume storage space and incur charges until they are deleted. By enabling an S3 Lifecycle policy that deletes incomplete multipart uploads, you can automatically remove them after a specified period of time (such as one day) and free up the storage space. This will reduce the S3 storage costs and also improve the performance of the application by avoiding unnecessary retries or errors.

Option A is not correct because switching from multipart uploads to Amazon S3 Transfer Acceleration will not reduce the S3 storage costs. Amazon S3 Transfer Acceleration is a feature that enables faster data transfers to and from S3 by using the AWS edge network. It is useful for improving the upload speed of large objects over long distances, but it does not affect the storage space or charges. In fact, it may increase the costs by adding a data transfer fee for using the feature.

Option C is not correct because configuring S3 inventory to prevent objects from being archived too quickly will not reduce the S3 storage costs. Amazon S3 Inventory is a feature that provides a report of the objects and their metadata in an S3 bucket. It is useful for managing and auditingthe S3 objects, but it does not affect the storage space or charges. In fact, it may increase the costs by generating additional S3 objects for the inventory reports.

Option D is not correct because configuring Amazon CloudFront to reduce the number of objects stored in Amazon S3 will not reduce the S3 storage costs. Amazon CloudFront is a content delivery network (CDN) that distributes the S3 objects to edge locations for faster and lower latency access. It is useful for improving the download speed and availability of the S3 objects, but it does not affect the storage space or charges. In fact, it may increase the costs by adding a data transfer fee for using the service. References:

Managing your storage lifecycle

Using multipart upload

Amazon S3 Transfer Acceleration

Amazon S3 Inventory

What Is Amazon CloudFront?

The solution that will reduce the launch time of the application during the next testing phase is to launch the EC2 On-Demand Instances with hibernation turned on and configure EC2 Auto Scaling warm pools. This solution allows the application to resume from a hibernated state instead of starting from scratch, which can save time and resources. Hibernation preserves the memory (RAM) state of the EC2 instances to the root EBS volume and then stops the instances.When the instances are resumed, they restore theirmemory state from the EBS volume and become productive quickly. EC2 Auto Scaling warm pools can be used to maintain a pool of pre-initialized instances that are ready to scale out when needed. Warm pools can also support hibernated instances, which can further reduce the launch time and cost of scaling out.

The other solutions are not as effective as the first one because they either do not reduce the launch time, do not guarantee availability, or do not use On-Demand Instances as required. Launching two or more EC2 On-Demand Instances with auto scaling features does not reduce the launch time of the application, as each instance still has to go through the initialization process. Launching EC2 Spot Instances does not guarantee availability, as Spot Instances can be interrupted by AWS at any time when there is a higher demand for capacity. Launching EC2 On-Demand Instances with Capacity Reservations does not reduce the launch time of the application, as it only ensures that there is enough capacity available for the instances, but does not pre-initialize them.

Understanding the Requirement: The data must be encrypted at rest with automatic key rotation every year, with minimal operational overhead.

Analysis of Options:

SSE-S3: This option provides encryption with S3 managed keys and automatic key rotation but offers less control and flexibility compared to KMS keys.

AWS KMS with Customer Managed Key (automatic rotation): This option offers full control over encryption keys, with AWS KMS handling automatic key rotation, minimizing operational overhead.

AWS KMS with Customer Managed Key (manual rotation): This requires manual intervention for key rotation, increasing operational overhead.

Customer Key Material: This involves more complex management, including importing key material and setting up automatic rotation, which increases operational overhead.

Best Option for Minimal Operational Overhead:

AWS KMS with a customer managed key and automatic rotation provides the needed security and key rotation with minimal operational effort. Setting the S3 bucket’s default encryption to use this key ensures all data is encrypted as required.

Understanding the Requirement: The application running in a private subnet needs to store and retrieve data from S3 without data traveling over the public internet.

Analysis of Options:

NAT Gateway: Allows private subnets to access the internet but incurs additional costs and still routes traffic through the public internet.

AWS Storage Gateway: Provides hybrid cloud storage solutions but is not the most cost-effective for direct S3 access from within the VPC.

S3 Interface Endpoint: Provides private access to S3 but is generally used for specific use cases where more granular control is required, which might be overkill and more expensive.

S3 Gateway Endpoint: Provides private, cost-effective access to S3 from within the VPC without routing traffic through the public internet.

Best Solution:

S3 Gateway Endpoint: This option meets the requirements for secure, private access to S3 from a private subnet most cost-effectively.

Understanding the Requirement: The company needs to monitor and notify changes to the OU hierarchy with minimal operational overhead.

Analysis of Options:

AWS Control Tower with Account Drift Notifications: AWS Control Tower provides automated account provisioning and governance, including drift detection and notifications for changes in the OU hierarchy.

AWS Control Tower with AWS Config: AWS Config provides resource configuration tracking but is more complex compared to drift notifications directly available in Control Tower.

AWS Service Catalog with CloudTrail: While CloudTrail tracks changes, setting up notification mechanisms involves more operational overhead.

AWS CloudFormation with Drift Detection: Suitable for tracking configuration changes but less efficient for monitoring OU hierarchy changes compared to Control Tower's built-in features.

Best Solution:

AWS Control Tower with Account Drift Notifications: Provides a streamlined and efficient way to detect and notify changes in the OU hierarchy with minimal operational overhead.

Understanding the Requirement: The company needs all EC2 instances to share up-to-date website content with minimal lag time, running behind an Application Load Balancer.

Analysis of Options:

EC2 User Data with ALB: Complex and not scalable as it requires updating each instance manually.

Amazon EFS: Provides a scalable, shared file storage solution that can be mounted by multiple EC2 instances, ensuring all instances have access to the same up-to-date content.

Amazon S3 with EC2 Sync: Involves periodic synchronization which introduces lag and complexity.

Amazon EBS Snapshots: Not suitable for dynamic and frequent updates required by a content management system.

Best Solution:

Amazon EFS: Ensures all EC2 instances have access to a consistent and up-to-date set of website assets with minimal lag time, meeting the requirements effectively.

Requirement Analysis: The application needs near real-time access to data, persistence, and minimal operational overhead.

ElastiCache for Redis: Provides in-memory data storage with persistence, supporting fast access and durability.

Operational Overhead: Managed service reduces the burden of setup, maintenance, and scaling.

Implementation:

Deploy an ElastiCache for Redis cluster.

Configure Redis to persist data to disk using AOF (Append-Only File) or RDB (Redis Database Backup) snapshots.

Conclusion: ElastiCache for Redis meets the requirements for fast access, data persistence, and low operational overhead.

References

Amazon ElastiCache:ElastiCache for Redis Documentation

Understanding the Requirement: The order processing system requires multiple independent validation steps, each handled by separate Lambda functions, with each function accessing only the subset of order information it needs. The system should be loosely coupled to accommodate future changes.

Analysis of Options:

Amazon SQS with a new Lambda function for transformation: This involves additional complexity in creating and managing multiple SQS queues and an extra Lambda function for data transformation.

Amazon SNS with message filtering: While SNS supports message filtering, it is more suited for pub/sub messaging patterns rather than event-driven processing requiring fine-grained control over the data sent to each function.

Amazon EventBridge with input transformers: EventBridge is designed for event-driven architectures, allowing for fine-grained control with input transformers that can modify and filter the event data sent to each target Lambda function, ensuring each function receives only the necessary information.

SQS with synchronous Lambda invocations: This approach adds unnecessary complexity with synchronous invocations and is not ideal for an event-driven, loosely coupled architecture.

Best Solution:

Amazon EventBridge with input transformers: This option provides the most flexible, scalable, and loosely coupled architecture, enabling each Lambda function to receive only the required subset of data.

Understanding the Requirement: The company needs to map its IT infrastructure to identify and enforce security policies, with the ability to quickly query and identify security risks.

Analysis of Options:

Amazon RDS: While suitable for relational data, it is not optimized for handling complex relationships and querying those relationships, which is essential for an IT infrastructure map.

Amazon Neptune: A graph database service designed for handling highly connected data. It uses SPARQL to query graph data efficiently, making it ideal for mapping IT infrastructure and identifying relationships that pose security risks.

Amazon Redshift: A data warehouse solution optimized for complex queries on large datasets but not specifically for graph data.

Amazon DynamoDB: A NoSQL database that uses PartiQL for querying, but it is not optimized for complex relationships in graph data.

Best Option for Mapping and Querying IT Infrastructure:

Amazon Neptune provides the most suitable solution with the least operational overhead. It is purpose-built for graph data and enables efficient querying of complex relationships to identify security risks.

Understanding the Requirement: The application running on EC2 instances in a private subnet needs to process sensitive information from an S3 bucket without using the internet.

Analysis of Options:

Internet Gateway: This would expose the application to the internet, which is not suitable for accessing sensitive information securely.

VPN Connection: VPN is primarily used for secure connections between on-premises networks and AWS VPCs, not for direct S3 access within the same VPC.

NAT Gateway: This allows instances in a private subnet to connect to the internet, but the goal is to avoid internet access.

VPC Endpoint: Provides a private connection between the VPC and S3 without using the internet, ensuring secure access to the S3 bucket.

Best Solution:

VPC Endpoint: Configuring a VPC endpoint allows secure, private communication between the EC2 instances and the S3 bucket without using the internet, ensuring data security and compliance.

Understanding the Requirement: The company needs to migrate sensitive and critical data from on-premises SQL Server databases to AWS, aiming to increase security and reduce operational overhead.

Analysis of Options:

EC2 Instances with KMS: Running SQL Server on EC2 provides control but requires significant operational overhead for management, backups, patching, and high availability.

Multi-AZ Amazon RDS for SQL Server with KMS: Amazon RDS for SQL Server offers managed database services, reducing operational overhead. Multi-AZ deployment provides high availability, and KMS encryption ensures data security.

Amazon S3 and Macie: S3 is not a suitable replacement for relational databases, and Macie is used for data security and compliance but not for database operations.

Amazon DynamoDB and CloudWatch Logs: DynamoDB is a NoSQL database and does not support SQL Server workloads directly. CloudWatch Logs are used for monitoring, not for ensuring database security.

Best Solution:

Multi-AZ Amazon RDS for SQL Server with KMS: This solution meets the requirements for security, high availability, and reduced operational overhead by using a managed database service with encryption.

Understanding the Requirement: Developers in the Development account need to push code changes to the Production account, with phased access control for different stages of the project.

Analysis of Options:

Policy Documents in Each Account: This approach increases complexity and is harder to manage compared to role-based access.

IAM Role in Development Account: Roles in the Development account cannot directly control access to resources in the Production account.

IAM Role in Production Account: Creating a role in the Production account with a trust policy that allows the Development account to assume it provides controlled, secure access.

IAM Group in Production Account: This approach does not provide the required cross-account access control.

Best Solution:

IAM Role in the Production Account: This method allows precise control over who can access the Production account from the Development account, with the ability to manage permissions and access levels effectively.

Understanding the Requirement: The company needs to copy files generated by an on-premises application to AWS without modifying the application code. The files are stored on an SMB file share and require a low-latency connection to the application servers.

Analysis of Options:

Amazon Elastic File System (EFS): EFS is designed for Linux-based workloads and does not natively support SMB file shares.

Amazon FSx for Windows File Server: FSx supports SMB file shares but would require changes to the application or additional infrastructure to connect on-premises systems.

AWS Snowball: Suitable for large data transfers but not for continuous, low-latency file copying.

AWS Storage Gateway: Provides a hybrid cloud storage solution, supporting SMB file shares and enabling seamless copying of files to AWS without requiring changes to the application.

Best Solution:

AWS Storage Gateway: This service meets the requirement for a low-latency, seamless file transfer solution from on-premises to AWS without modifying the application code.

Understanding the Requirement: The company needs to process images as they are uploaded to S3 in a cost-effective manner, currently using an EC2 Spot Fleet for nightly processing.

Analysis of Options:

S3 Event Notifications to SQS and Lambda: This setup allows for event-driven processing with Lambda, which scales automatically based on the number of messages in the queue. It is cost-effective as Lambda charges are based on the compute time used.

S3 Event Notifications to SQS and EC2 Reserved Instance: Involves managing EC2 instances, which adds operational overhead and is less cost-effective.

S3 Event Notifications to SNS and ECS: More complex and potentially less cost-effective compared to using Lambda for simple processing tasks.

S3 Event Notifications to SNS: Requires additional configuration and management to process messages.

Best Solution:

S3 Event Notifications to SQS and Lambda: This option is the most cost-effective and scalable, leveraging AWS managed services with minimal operational overhead.

Understanding the Requirement: The development team needs to prevent the launch of large EC2 instances across multiple AWS accounts used for development, staging, and production environments.

Analysis of Options:

IAM Policies: Would need to be applied individually to each user in every account, leading to significant operational overhead.

AWS Resource Access Manager: Used for sharing resources, not for enforcing restrictions on resource creation.

IAM Role in Each Account: Requires creating and managing roles in each account, leading to higher operational overhead compared to using a centralized approach.

Service Control Policy (SCP) with AWS Organizations: Provides a centralized way to enforce policies across multiple AWS accounts, ensuring that large EC2 instances cannot be launched in any account.

Best Solution:

Service Control Policy (SCP) with AWS Organizations: This solution offers the least operational overhead by allowing centralized management and enforcement of policies across all accounts, effectively preventing the launch of large EC2 instances.

Understanding the Requirement: The company needs a disaster recovery solution for FSx for NetApp ONTAP in a secondary region, accessible using the same protocols (CIFS and NFS).

Analysis of Options:

Lambda Function and S3: Involves copying data to S3, which changes the access protocols and increases operational overhead.

AWS Backup: Suitable for backup and restore but not for real-time or near-real-time replication for disaster recovery.

FSx for ONTAP with SnapMirror: SnapMirror provides efficient replication between ONTAP instances, maintaining access protocols and requiring minimal operational overhead.

Amazon EFS: Does not support CIFS and requires migrating data, increasing complexity and changing access protocols.

Best Solution:

FSx for ONTAP with SnapMirror: This solution ensures seamless disaster recovery with the same access protocols and minimal operational overhead.

Understanding the Requirement: The company needs to mitigate DDoS attacks on its website, which uses AWS Global Accelerator to route traffic to an Application Load Balancer (ALB).

Analysis of Options:

AWS WAF on Global Accelerator: Allows for centralized protection and can block traffic based on rate-based rules, effectively mitigating DDoS attacks with minimal implementation effort.

Lambda Function and VPC Network ACL: Requires custom implementation and ongoing management, increasing complexity and effort.

AWS WAF on ALB: Provides protection but involves additional configuration and management at the ALB level.

CloudFront Distribution in front of Global Accelerator: Adds unnecessary complexity and changes the current traffic flow setup.

Best Solution:

AWS WAF on Global Accelerator: This provides the required protection with the least implementation effort, ensuring effective DDoS mitigation and maintaining the existing architecture.

Understanding the Requirement: The company wants to optimize costs and reduce operational overhead for an RDS for PostgreSQL database that only needs to be active during business hours on weekdays.

Analysis of Options:

Instance Scheduler on AWS: Allows for automated start and stop schedules based on specified times, ideal for resources only needed during certain hours. This directly optimizes costs by running the database only when needed.

Turn off automatic backups and create weekly snapshots: Does not address the requirement of reducing operational overhead and optimizing runtime costs.

Custom Lambda function: This could work but adds unnecessary complexity compared to using the Instance Scheduler.

All Upfront Reserved DB Instances: While this reduces costs, it does not optimize for usage patterns that require the database only during specific hours.

Best Solution:

Instance Scheduler on AWS: This option effectively manages the database runtime based on the specified schedule, reducing costs and operational overhead.

Requirement Analysis: The product catalog search is causing high CPU utilization on the MySQL DB instance, slowing down the website.

ElastiCache Overview: Amazon ElastiCache for Redis can be used to cache frequently accessed data, reducing load on the database.

Lazy Loading: This caching strategy loads data into the cache only when it is requested, improving response times for repeated queries.

Implementation:

Set up an ElastiCache for Redis cluster.

Modify the application to check the cache before querying the database.

Use lazy loading to populate the cache on cache misses.

Conclusion: This approach reduces database load and improves website performance during product catalog searches.

References

Amazon ElastiCache:ElastiCache Documentation

Caching Strategies:ElastiCache Caching Strategies

Understanding the Requirement: The company wants to cost-optimize their workload that uses EC2, Lambda, Fargate, and SageMaker, covering the most services with the fewest savings plans.

Analysis of Options:

EC2 Instance Savings Plan: Limited to EC2 and SageMaker, missing coverage for Lambda and Fargate.

Compute Savings Plan: Provides the most flexibility, covering a broad range of compute services, including EC2, Lambda, Fargate, and SageMaker.

SageMaker Savings Plan: Specifically for SageMaker, missing coverage for EC2, Lambda, and Fargate.

Combination of plans: The Compute Savings Plan is versatile and can be combined to cover different services efficiently.

Best Solution:

Compute Savings Plan for EC2, Lambda, and SageMaker: Covers the primary compute services efficiently.

Compute Savings Plan for Lambda, Fargate, and EC2: Covers the remaining services, ensuring broad coverage with minimal plans.

Current Backup Settings: By default, Amazon RDS creates automated backups with a retention period of 7 days.

Regulatory Requirements: The requirement is to retain daily backups for 30 days.

Adjusting Retention Period: You can modify the RDS instance settings to increase the automated backup retention period to 30 days.

Operational Overhead: This solution is the simplest as it leverages existing automated backups and requires minimal intervention.

Implementation: The change can be made via the AWS Management Console, AWS CLI, or AWS SDKs.

References

Amazon RDS Backups:Amazon RDS Documentation

Understanding the Requirement: The company wants to maximize cost savings for their application over the next three years, with the flexibility to change the instance family and sizes within the next six months based on application popularity and usage.

Analysis of Options:

Compute Savings Plan: This plan offers the most flexibility, allowing the company to change instance families, sizes, and regions. It applies to EC2, AWS Fargate, and AWS Lambda, offering significant cost savings with this flexibility.

EC2 Instance Savings Plan: This plan is less flexible than the Compute Savings Plan, as it only applies to EC2 instances and allows changes within a specific instance family.

Zonal Reserved Instances: These provide a discount on EC2 instances but are tied to a specific availability zone and instance type, offering the least flexibility.

Standard Reserved Instances: These offer discounts on EC2 instances but with more restrictions compared to Savings Plans, particularly when changing instance types and families.

Best Option for Flexibility and Savings:

The Compute Savings Plan is the most cost-effective solution because it allows the company to maintain flexibility while still achieving significant cost savings. This is critical for adapting to changing application demands without being locked into specific instance types or families.

AWS Secrets Manager helps you protect secrets needed to access your applications, services, and IT resources. The service enables you to easily rotate, manage, and retrieve database credentials, API keys, and other secrets throughout their lifecycle.

https://docs.aws.amazon.com/secretsmanager/latest/userguide/intro.html

Secrets Manager enables you to replace hardcoded credentials in your code, including passwords, with an API call to Secrets Manager to retrieve the secret programmatically. This helps ensure the secret can't be compromised by someone examining your code, because the secret no longer exists in the code. Also, you can configure Secrets Manager to automatically rotate the secret for you according to a specified schedule. This enables you to replace long-term secrets with short-term ones, significantly reducing the risk of compromise.

https://aws.amazon.com/premiumsupport/knowledge-center/acm-certificate-expiration/

To achieve high availability with minimum downtime and minimum loss of data, the Auto Scaling group should be configured to use multiple Availability Zones to ensure that there is no single point of failure. The database should be configured as Multi-AZ to enable automatic failover in case of an outage in the primary Availability Zone. Additionally, an Amazon RDSProxy instance can be used to improve the scalability and availability of the database by reducing connection failures and improving failover times.

as the policy prevents anyone from doing any EC2 action on any region except us-east-1 and allows only users with source ip 10.100.100.0/24 to terminate instances. So user with source ip 10.100.100.254 can terminate instances in us-east-1 region.

To ensure that the Lambda function ingests all data in the future despite occasional network connectivity issues, the following actions should be taken:

Create an Amazon Simple Queue Service (SQS) queue and subscribe it to the SNS topic. This allows for decoupling of the notification and processing, so that even if the processing Lambda function fails, the message remains in the queue for further processing later.

Modify the Lambda function to read from the SQS queue instead of directly from SNS. This decoupling allows for retries and fault tolerance and ensures that all messages are processed by the Lambda function.

The correct answer is Option D. Deploy an S3 VPC gateway endpoint into the VPC and attach an endpoint policy that allows access to the S3 buckets. By deploying an S3 VPC gateway endpoint, the application can access the S3 buckets over a private network connection within the VPC, eliminating the need for data transfer over the internet. This can help reduce data transfer fees as well as improve the performance of the application. The endpoint policy can be used to specify which S3 buckets the application has access to.

https://aws.amazon.com/premiumsupport/knowledge-center/s3-private-connection-no-authentication/

https://docs.aws.amazon.com/rekognition/latest/dg/moderation.html?pg=ln &sec=ft

https://docs.aws.amazon.com/rekognition/latest/dg/a2i-rekognition.html

"Create an Amazon SQS queue to hold the jobs that needs to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue"

In this case we need to find a durable and loosely coupled solution for storing jobs. Amazon SQS is ideal for this use case and can be configured to use dynamic scalingbased on the number of jobs waiting in the queue.To configure this scaling you can use the backlog per instance metric with the target value being the acceptable backlog per instance to maintain. You can calculate these numbers as follows: Backlog per instance: To calculate your backlog per instance, start with the ApproximateNumberOfMessages queue attribute to determine the length of the SQS queue

https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock-overview.html

https://docs.aws.amazon.com/kms/latest/developerguide/rotate-keys.html

When you enable automatic key rotation for a customer managed key, AWS KMS generates new cryptographic material for the KMS key every year. AWS KMS also savesthe KMS key's older cryptographic material in perpetuity so it can be used to decrypt data that the KMS key encrypted.

Key rotation in AWS KMS is a cryptographic best practice that is designed to be transparent and easy to use. AWS KMS supports optional automatic key rotation only for customer managed CMKs. Enable and disable key rotation. Automatic key rotation is disabled by default on customer managed CMKs. When you enable (or re-enable) key rotation, AWS KMS automatically rotates the CMK 365 days after the enable date and every 365 days thereafter.

https://aws.amazon.com/global-accelerator/faqs/

HTTP /HTTPS - ALB ; TCP and UDP - NLB; Lowest latency routing and more throughput. Also supports failover, uses Anycast Ip addressing - Global Accelerator Caching at Egde Locations – Cloutfront

WS Global Accelerator automatically checks the health of your applications and routes user traffic only to healthy application endpoints. If the health status changes or you make configuration updates, AWS Global Accelerator reacts instantaneously to route your users to the next available endpoint..

"Typically, you configure buckets to be Requester Pays buckets when you want to share data but not incur charges associated with others accessing the data. For example, you might use Requester Pays buckets when making available large datasets, such as zip code directories, reference data, geospatial information, or web crawling data."https://docs.aws.amazon.com/AmazonS3/latest/userguide/RequesterPaysBuckets.html

This is the purpose of bookmarks: "AWS Glue tracks data that has already been processed during a previous run of an ETL job by persisting state information from the job run. This persisted state information is called a job bookmark. Job bookmarks help AWS Glue maintain state information and prevent the reprocessing of old data."https://docs.aws.amazon.com/glue/latest/dg/monitor-continuations.html

https://aws.amazon.com/cn/blogs/security/how-to-connect-to-aws-secrets-manager-service-within-a-virtual-private-cloud/

https://aws.amazon.com/blogs/security/rotate-amazon-rds-database-credentials-automatically-with-aws-secrets-manager/

https://aws.amazon.com/s3/storage-classes/?trk=66264cd8-3b73-416c-9693-ea7cf4fe846a &sc_channel=ps&s_kwcid=AL!4422!3!536452716950!p!!g!!aws%20s3%20pricing&ef_id=Cj0KCQjwnbmaBhD-ARIsAGTPcfVHUZN5_BMrzl5zBcaC8KnqpnNZvjbZzqPkH6k7q4JcYO5KFLx0YYgaAm6nEALw_wcB:G:s&s_kwcid=AL!4422!3!536452716950!p!!g!!aws%20s3%20pricing

https://aws.amazon.com/blogs/security/control-access-to-aws-resources-by-using-the-aws-organization-of-iam-principals/

To ensure that orders are processed in the order that they are received, the best solution is to use an Amazon SQS FIFO (First-In-First-Out) queue. This type of queue maintains the exact order in which messages are sent and received. In this case, the application can send information about new orders to an Amazon API Gateway REST API, which can then use an API Gateway integration to send a message to an Amazon SQS FIFO queue for processing. The queue can then be configured to invoke an AWS Lambda function to perform the necessary processing on each order. This ensures that orders are processed in the exact order in which they are received.

https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/AmazonEFS.html Amazon FSx for Windows File Server provides fully managed Microsoft Windows file servers, backed by a fully native Windows file system.https://docs.aws.amazon.com/fsx/latest/WindowsGuide/what-is.html

https://docs.aws.amazon.com/systems-manager/latest/userguide/about-windows-app-patching.html

AWS Config is a fully managed service that allows the company to assess, audit, and evaluate the configurations of its AWS resources. It provides a detailed inventory of the resources in use and tracks changes to resource configurations. AWS Config can detect configuration changes and alert the company when changes occur. It also provides a historical view of changes, which is essential for compliance and governance purposes. AWS CloudTrail is a fully managed service that provides a detailed history of API calls made to the company's AWS resources. It records all API activity in the AWS account, including who made the API call, when the call was made, and what resources were affected by the call. This information is critical for security and auditing purposes, as it allows the company to investigate any suspicious activity that might occur on its AWS resources.

You might want to use Transfer Acceleration on a bucket for various reasons, including the following:

You have customers that upload to a centralized bucket from all over the world.

You transfer gigabytes to terabytes of data on a regular basis across continents.

You are unable to utilize all of your available bandwidth over the Internet when uploading to Amazon S3.

https://docs.aws.amazon.com/AmazonS3/latest/dev/transfer-acceleration.html

https://aws.amazon.com/s3/transfer-acceleration/#:~:text=S3%20Transfer%20Acceleration%20(S3TA)%20reduces,to%20S3%20for%20remote%20applications:

"Amazon S3 Transfer Acceleration can speed up content transfers to and from Amazon S3 by as much as 50-500% for long-distance transfer of larger objects. Customers who have either web or mobile applications with widespread users or applications hosted far away from their S3 bucket can experience long and variable upload and download speeds over the Internet"

https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html

"Improved throughput - You can upload parts in parallel to improve throughput."

https://aws.amazon.com/getting-started/hands-on/build-serverless-web-app-lambda-apigateway-s3-dynamodb-cognito/module-4/

Build a Serverless Web Application with AWS Lambda, Amazon API Gateway, AWS Amplify, Amazon DynamoDB, and Amazon Cognito. This example showed similar setup as question: Build a Serverless Web Application with AWS Lambda, Amazon API Gateway, AWS Amplify, Amazon DynamoDB, and Amazon Cognito

"Security groups create an outbound rule for every inbound rule." Not completely right. Statefull does NOT mean that if you create an inbound (or outbound) rule, it will create an outbound (or inbound) rule. What it does mean is: suppose you create an inbound rule on port 443 for the X ip. When a request enters on port 443 from X ip, it will allow traffic out for that request in the port 443. However, if you look at the outbound rules, there will not be any outbound rule on port 443 unless explicitly create it. In ACLs, which are stateless, you would have to create an inbound rule to allow incoming requests and an outbound rule to allow your application responds to those incoming requests.

https://docs.aws.amazon.com/vpc/latest/userguide/VPC_SecurityGroups.html#SecurityGroupRules

S3 Intelligent-Tiering - Perfect use case when you don't know the frequency of access or irregular patterns of usage.

Amazon S3 offers a range of storage classes designed for different use cases. These include S3 Standard for general-purpose storage of frequently accessed data; S3 Intelligent-Tiering for data with unknown or changing access patterns; S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA) for long-lived, but less frequently accessed data; and Amazon S3 Glacier (S3 Glacier) and Amazon S3 Glacier Deep Archive (S3 Glacier Deep Archive) for long-term archive and digital preservation. If you have data residency requirements that can’t be met by an existing AWS Region, you can use the S3 Outposts storage class to store your S3 data on-premises. Amazon S3 also offers capabilities to manage your data throughout its lifecycle. Once an S3 Lifecycle policy is set, your data will automatically transfer to a different storage class without any changes to your application.

https://aws.amazon.com/getting-started/hands-on/getting-started-using-amazon-s3-intelligent-tiering/?nc1=h_ls

https://aws.amazon.com/blogs/aws/amazon-aurora-fast-database-cloning/

To clone the production data into the test environment with high I/O performance and without affecting the production environment, the best option is to take EBS snapshots of the production EBS volumes and restore them onto new EBS volumes in the testenvironment. Then, attach the new EBS volumes to EC2 instances in the test environment. This option minimizes the time required to clone the data and ensures that modifications to the cloned data do not affect the production environment. Therefore, option C is the correct answer.

https://aws.amazon.com/premiumsupport/knowledge-center/ec2-instance-access-s3-bucket/

Moving the catalog to an Amazon Elastic File System (Amazon EFS) file system provides both high availability and durability. Amazon EFS is a fully-managed, highly-available, and durable file system that is built to scale on demand. With Amazon EFS, the catalog data can be storedand accessed from multiple EC2 instances in different availability zones, ensuring high availability. Also, Amazon EFS automatically stores files redundantly within and across multiple availability zones, making it a durable storage option.

Fromhttps://docs.aws.amazon.com/kms/latest/developerguide/custom-key-store-overview.html

For most users, the default AWS KMS key store, which is protected by FIPS 140-2 validated cryptographic modules, fulfills their security requirements. There is no need to add an extra layer of maintenance responsibility or a dependency on an additional service. However, you might consider creating a custom key store if your organization has any of the following requirements: Key material cannot be stored in a shared environment. Key material must be subject to a secondary, independent audit path. The HSMs that generate and store key material must be certified at FIPS 140-2 Level 3.https://docs.aws.amazon.com/kms/latest/developerguide/custom-key-store-overview.html

https://docs.aws.amazon.com/kms/latest/developerguide/multi-region-keys-overview.html

https://aws.amazon.com/blogs/security/how-to-replicate-secrets-aws-secrets-manager-multiple-regions/

AURORA is 5x performance improvement over MySQL on RDS and handles more read requests than write,; maintaining high availability = Multi-AZ deployment

To meet the requirements of immediately accessible records for 1 year and then archived for an additional 9 years with maximum resiliency, we can use S3 Lifecycle policy to transition records from S3 Standard to S3 Glacier Deep Archive after 1 year. And to ensure that the records cannot be deleted by anyone, including administrative and root users, we can use S3 Object Lock in compliance mode for a period of 10 years. Therefore, the correct answer is option C.

https://aws.amazon.com/sqs/features/

By routing incoming requests to Amazon SQS, the company can decouple the job requests from the processing instances. This allows them to scale the number of instances based on the size of the queue, providing more resources when needed. Additionally, using an Auto Scaling group based on the queue size will automatically scale the number of instances up or down depending on the workload. Updating the software to read from the queue will allow it to process the job requests in a more efficient manner, improving the performance of the system.

https://aws.amazon.com/kinesis/data-firehose/features/?nc=sn &loc=2#:~:text=into%20Amazon%20S3%2C%20Amazon%20Redshift%2C%20Amazon%20OpenSearch%20Service%2C%20Kinesis,Delivery%20streams

Amazon Athena can be used to query JSON in S3

https://aws.amazon.com/blogs/networking-and-content-delivery/scaling-network-traffic-inspection-using-aws-gateway-load-balancer/

https://docs.aws.amazon.com/eventbridge/latest/userguide/resource-based-policies-eventbridge.html#lambda-permissions

https://docs.aws.amazon.com/efs/latest/ug/how-it-works.html#how-it-works-ec2

"For archive data that needs immediate access, such as medical images, news media assets, or genomics data, choose the S3 Glacier Instant Retrieval storage class, an archive storage class that delivers the lowest cost storage with milliseconds retrieval. For archive data that does not require immediate access but needs the flexibility to retrieve large sets of data at no cost, such as backup or disaster recovery use cases, choose S3 Glacier Flexible Retrieval (formerly S3 Glacier), with retrieval in minutes or free bulk retrievals in 5-12 hours."https://aws.amazon.com/about-aws/whats-new/2021/11/amazon-s3-glacier-instant-retrieval-storage-class/

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_RestoreFromSnapshot.html#USER_RestoreFromSnapshot.CON

Under "Encrypt unencrypted resources" -https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSEncryption.html

Share the existing KMS key with the MSP external account because it has already been used to encrypt the AMI snapshot.https://docs.aws.amazon.com/kms/latest/developerguide/key-policy-modifying-external-accounts.html

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-ec2-placementgroup.html

"A cluster placement group is a logical grouping of instances within a single Availability Zone that benefit from low network latency, high network throughput"

The details are revealed in below url:https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/FIFO-queues.html

FIFO (First-In-First-Out) queues are designed to enhance messaging between applications when the order of operations and events is critical, or where duplicates can't be tolerated. Examples of situations where you might use FIFO queues include the following: To make sure that user-entered commands are run in the right order. To display the correct product price by sending price modifications in the right order. To prevent a student from enrolling in a course before registering for an account.

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-ecs-taskdefinition.html

https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps_examples_vpc.html#example_vpc_2

This approach ensures that the order creation and payment processing steps are separate and atomic. By sending the order information to an SQS FIFO queue, the payment service can process the order one at a time and in the order they were received. If the payment service is unable to process an order, it can be retried later, preventing the creation of multiple orders. The deletion of the message from the queue after it is processed will prevent the same message from being processed multiple times.

In a typical development environment, dev and test databases are mostly utilized for 8 hours a day and sit idle when not in use. However, the databases are billed for the compute and storage costs during this idle time. To reduce the overall cost, Amazon RDS allows instances to be stopped temporarily. While the instance is stopped, you’re charged for storage and backups, but not for the DB instance hours. Please note that a stopped instance will automatically be started after 7 days. This post presents a solution using AWS Lambda and Amazon EventBridge that allows you to schedule a Lambda function to stop and start the idle databases with specific tags to save on compute costs. The second post presents a solution that accomplishes stop and start of the idle Amazon RDS databases using AWS Systems Manager.

https://aws.amazon.com/blogs/compute/microservice-delivery-with-amazon-ecs-and-application-load-balancers/

https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/monitor-ami-events.html#:~:text=For%20example%2C%20you%20can%20create%20an%20EventBridge%20rule%20that%20detects%20when%20the%20AMI%20creation%20process%20has %20completed%20and%20then%20invokes%20an%20Amazon%20SNS%20topic%20to%20send%20an%20email%20notification%20to%20you.

Creating an Amazon EventBridge (Amazon CloudWatch Events) rule for the CreateImage API call and configuring the target as an Amazon Simple Notification Service (Amazon SNS) topic to send an alert when a CreateImage API call is detected will meet the requirements with the least operational overhead. Amazon EventBridge is a serverless event bus that makes it easy to connect applications together using data from your own applications, integrated Software as a Service (SaaS) applications, and AWS services. By creating an EventBridge rule for the CreateImage API call, the company can set up alerts whenever this operation is called within their account. The alert can be sent to an SNS topic, which can then be configured to send notifications to the company's email or other desired destination.

https://docs.aws.amazon.com/lambda/latest/dg/configuration-vpc.html#vpc-managing-eni

In compliance mode, a protected object version can't be overwritten or deleted by any user, including the root user in your AWS account. When an object is locked in compliance mode, its retention mode can't be changed, and its retention period can't be shortened. Compliance mode helps ensure that an object version can't be overwritten or deleted for the duration of the retention period. In governance mode, users can't overwrite or delete an object version or alter its lock settings unless they have special permissions. With governance mode, you protect objects against being deleted by most users, but you can still grant some users permission to alter the retention settings or delete the object if necessary. In Governance mode, Objects can be deleted by some users with special permissions, this is against the requirement.

Compliance:

- Object versions can't be overwritten or deleted by any user, including the root user

- Objects retention modes can't be changed, and retention periods can't be shortened

Governance:

- Most users can't overwrite or delete an object version or alter its lock settings

- Some users have special permissions to change the retention or delete the object

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-custom.htmlandhttps://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/working-with-custom-oracle.html

https://docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-target-tracking.html

CloudFront uses a local cache to provide the response, AWS Global accelerator proxies requests and connects to the application all the time for the response.

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/private-content-restricting-access-to-s3.html#private-content-granting-permissions-to-oai

A -> We can configure CloudFront to require HTTPS from clients (enhanced security) https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/using-https-viewers-to-cloudfront.html D - > storing static website on S3 provides scalability and less operational overhead, then configuration of Application LB and EC2 instances (hence E is out)

You need S3 to be able to archive the logs after one month. Cannot do that with CloudWatch Logs.

AWS Shield Advanced provides expanded DDoS attack protection for your Amazon EC2 instances, Elastic Load Balancing load balancers, CloudFront distributions, Route 53 hosted zones, and AWS Global Accelerator standard accelerators.https://docs.aws.amazon.com/waf/latest/developerguide/what-is-aws-waf.html

For standard accelerators, Global Accelerator uses the AWS global network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure, which increases the availability of your applications. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses that are located in one AWS Region or multiple Regions.

https://docs.aws.amazon.com/global-accelerator/latest/dg/what-is-global-accelerator.html

https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles.htmlhttps://docs.aws.amazon.com/IAM/latest/UserGuide/id_users.html

https://docs.aws.amazon.com/whitepapers/latest/disaster-recovery-workloads-on-aws/disaster-recovery-options-in-the-cloud.html

https://aws.amazon.com/cn/blogs/compute/cost-optimization-and-resilience-eks-with-spot-instances/

AWS Fargate is a serverless experience for user applications, allowing the user to concentrate on building applications instead of configuring and managing servers. Fargate also automates resource management, allowing users to easily scale their applications in response to demand.

Amazon CloudFront is a content delivery network (CDN) that speeds up the delivery of static and dynamic web content, such as HTML pages, images, and videos. By using CloudFront, the HTML pages will be served to users from the edge location that is closest to them, resulting in faster delivery and a better user experience. CloudFront can also handle the high traffic and large number of requests expected for the global event, ensuring that the HTML pages are available and accessible to users around the world.

You can use CloudFront to deliver video on demand (VOD) or live streaming video using any HTTP origin. One way you can set up video workflows in the cloud is by using CloudFront together with AWS Media Services.https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/on-demand-streaming-video.html

This solution meets the requirement of migrating a Windows-based application that requires the use of a shared Windows file system attached to multiple Amazon EC2 Windows instances that are deployed across multiple Availability Zones. Amazon FSx for Windows File Server provides fully managed shared storage built on Windows Server, and delivers a wide range of data access, data management, and administrative capabilities. It supports the Server Message Block (SMB) protocol and can be mounted to EC2 Windows instances across multiple Availability Zones.

Option A is incorrect because AWS Storage Gateway in volume gateway mode provides cloud-backed storage volumes that can be mounted as iSCSI devices from on-premises application servers, but it does not support SMB protocol or EC2 Windows instances. Option C is incorrect because Amazon Elastic File System (Amazon EFS) provides a scalable and elastic NFS file system for Linux-based workloads, but it does not support SMB protocol or EC2 Windows instances. Option D is incorrect because Amazon Elastic Block Store (Amazon EBS) providespersistent block storage volumes for use with EC2 instances, but it does not support SMB protocol or attaching multiple instances to the same volume.

https://aws.amazon.com/premiumsupport/knowledge-center/cloudwatch-memory-metrics-ec2/

Migrate the database to Amazon Aurora MySQL - this will let the DB scale on it's own; it'll scale automatically without needing adjustment. Create AMI of the web app and using a launch template - this will make the creating of any future instances of the app seamless. They can then be added to the auto scaling group which will save them money as it will scale up and down based on demand. Using a spot fleet to launch instances- This solves the "MOST cost-effective" portion of the question as spot instances come at a huge discount at the cost of being terminated at any time Amazon deems fit. I think this is why there's a bit of disagreement on this. While it's the most cost effective, it would be a terrible choice if amazon were to terminate that spot instance during a busy period.

Amazon S3 is cheapest and can be accessed from anywhere.

AWS Database Migration Service supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle or Microsoft SQL Server to Amazon Aurora. With AWS Database Migration Service, you can also continuously replicate data with low latency from any supported source to any supported target. For example, you can replicate from multiple sources to Amazon Simple Storage Service (Amazon S3) to build a highly available and scalable data lake solution. You can also consolidate databases into a petabyte-scale data warehouse by streaming data to Amazon Redshift. Learn more about the supported source and target databases.https://aws.amazon.com/dms/

(https://aws.amazon.com/blogs/security/how-to-restrict-amazon-s3-bucket-access-to-a-specific-iam-role/)

AWS Global Accelerator and Amazon CloudFront are separate services that use the AWS global network and its edge locations around the world. CloudFront improves performance for both cacheable content (such as images and videos) and dynamic content (such as API acceleration and dynamic site delivery). Global Accelerator improves performance for a wide range of applications over TCP or UDP by proxying packets at the edge to applications running in one or more AWS Regions. Global Accelerator is a good fit for non-HTTP use cases, such as gaming (UDP), IoT (MQTT), or Voice over IP, as well as for HTTP use cases that specifically require static IP addresses or deterministic, fast regional failover. Both services integrate with AWS Shield for DDoS protection.

EC2 Spot Instances allow users to bid on spare Amazon EC2 computing capacity and can be a cost-effective solution for stateless, interruptible workloads that can be started and stopped at any time. Since the batch processing job is stateless, can be started and stopped at any time, and typically takes upwards of 60 minutes to complete, EC2 Spot Instances would be a good fit for this workload.

https://aws.amazon.com/certificate-manager/:

"With AWS Certificate Manager, you can quickly request a certificate, deploy it on ACM-integrated AWS resources, such as Elastic Load Balancers, Amazon CloudFront distributions, and APIs on API Gateway, and let AWS Certificate Manager handle certificate renewals. It also enables you to create private certificates for your internal resources and manage the certificate lifecycle centrally."

By using an SQS queue and Lambda, the solutions architect can decouple the API front end from the processing microservices and improve the overall scalability and availability of the system. The SQS queue acts as a buffer, allowing the API front end to continue accepting user requests even if the processing microservices are experiencing high workloads or are temporarilyunavailable. The Lambda function can then retrieve requests from the SQS queue and write them to DynamoDB, ensuring that all user requests are stored and processed. This approach allows the company to scale the processing microservices independently from the API front end, ensuring that the API remains available to users even during periods of high demand.

Using AWS WAF has several benefits. Additional protection against web attacks using criteria that you specify. You can define criteria using characteristics of web requests such as the following: Presence of SQL code that is likely to be malicious (known as SQL injection). Presence of a script that is likely to be malicious (known as cross-site scripting). AWS Firewall Manager simplifies your administration and maintenance tasks across multiple accounts and resources for a variety of protections.https://docs.aws.amazon.com/waf/latest/developerguide/what-is-aws-waf.html