Amazon Web Services MLA-C01 Exam Dumps - Actual Questions Answers

To minimize communication overhead during distributed training:

1. Same VPC Subnet: Ensures low-latency communication between training instances by keeping the network traffic within a single subnet.

2. Same AWS Region and Availability Zone: Reduces network latency further because cross-AZ communication incurs additional latency and costs.

3. Data in the Same Region and AZ: Ensures that the training data is accessed with minimal latency, improving performance during training.

This configuration optimizes communication efficiency and minimizes overhead.

This issue occurs because target tracking auto scaling allows the endpoint to scale down to zero, and scaling up only happens after traffic arrives. At the start of the business day, no instances are running, so the first requests experience cold-start delays.

AWS documentation for Amazon SageMaker recommends using scheduled or step scaling policies when predictable traffic patterns exist. In this case, business hours are predictable, so the best practice is to proactively scale the endpoint before traffic arrives.

Option D correctly uses Amazon CloudWatch alarms with step scaling to increase the minimum instance count from zero to one at the start of the business day. This ensures at least one warm instance is ready to handle requests immediately, eliminating startup latency.

Options A, B, and C do not guarantee instance availability before traffic begins. Cooldown tuning and metric changes only react after load is detected.

Therefore, scheduled step scaling using CloudWatch alarms is the correct solution.

Amazon Data Firehose supports near real-time delivery by configuring the buffer interval and buffer size. AWS documentation states that setting the buffer interval to the minimum (as low as 1 second) enables low-latency ingestion.

By using zero or minimal buffering and tuning PutRecordBatch, data is delivered to OpenSearch almost immediately, enabling sub-second dashboard updates.

DataSync and SQS are not designed for real-time streaming analytics. Increasing the buffer interval worsens latency.

AWS explicitly recommends Firehose with minimal buffering for real-time OpenSearch ingestion.

Therefore, Option A is the correct and AWS-verified solution.