Amazon Web Services Updated SAA-C03 Exam Questions and Answers by katie

An S3 Bucket Key reduces the cost of using AWS KMS for server-side encryption by decreasing the number of requests made to KMS. By enabling S3 Bucket Key, the company can meet its encryption requirements with KMS keys while optimizing costs by reducing the number of KMS API requests.

Key AWS features:

Cost Optimization: S3 Bucket Keys reduce the frequency of KMS calls, optimizing the cost associated with encryption while still using AWS KMS for key management.

Compliance with KMS Encryption: This solution continues to meet the strict encryption requirements of the company by using KMS managed keys.

AWS Documentation: Using an S3 Bucket Key is recommended for organizations looking to optimize encryption costs without compromising security​​.

Spot Instances can be interrupted when AWS needs the capacity back. To reduce interruptions and improve availability, AWS provides the capacity-optimized allocation strategy.

Capacity-optimized strategy launches Spot Instances from the most available Spot capacity pools instead of the lowest-priced ones, reducing interruption rates.

By adding multiple instance types (e.g., using Instance Type Flexibility), the Auto Scaling group can launch instances in a broader set of pools, improving the chance that capacity is available.

Scheduled scaling actions combined with a diverse set of instances under the capacity-optimized strategy ensure higher resilience and better timing for instance launches.

This approach directly supports the Resiliency design principle in the AWS Well-Architected Framework.

???? References:

Best Practices for EC2 Spot Instances

Capacity-Optimized Allocation Strategy

The requirements include:

Scalability: The solution must scale as video files are uploaded.

Long-running tasks: Processing tasks can take up to 30 minutes. AWS Lambda has a maximum execution time of 15 minutes, which rules out options that involve Lambda performing all the processing.

Serverless and event-driven architecture: Ensures cost-effectiveness and high availability.

Analysis of Options:

Option A:

AWS Lambda has a 15-minute timeout, which cannot support tasks that take up to 30 minutes.

EventBridge Scheduler is unnecessary for monitoring files when native event notifications are available.Not a valid choice.

Option B:

AWS Step Functions and AWS Fargate can handle long-running processes, but Amazon EFS is not the ideal storage for uploaded video files in a serverless architecture.

Processing tasks triggered by EFS events are not a common pattern and may introduce complexities.Not the best practice.

Option C:

Amazon S3 is used for storing uploaded files, which integrates natively with event-driven services like EventBridge and Step Functions.

Amazon S3 event notifications trigger a Step Functions workflow, which can orchestrate Fargate tasks to process large video files, meeting the scalability and execution time requirements.Correct choice.

Option D:

Similar to Option A, AWS Lambda cannot handle long-running processes due to its 15-minute timeout.

Invoking Lambda for processing directly is not feasible for tasks that take up to 30 minutes.Not a valid choice.

AWS References:

Amazon S3 Event Notifications:AWS Documentation - S3 Event Notifications

AWS Step Functions:AWS Documentation - Step Functions

AWS Fargate:AWS Documentation - Fargate

Comparison of Storage Services:AWS Storage Options

By leveragingAmazon S3,Step Functions, andFargate, this solution provides a scalable, efficient, and serverless approach to handling video processing tasks.

Option B: FSx for Lustre is designed for HPC workloads with high IOPS.

Option E: A cluster placement group ensures low-latency networking for HPC analytics workloads.

Option A: Amazon EFS is not optimized for HPC.

Option D: Mountpoint for S3 does not meet high IOPS needs.