AWS Certified Solutions Architect - Associate
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A company is migrating an old application to AWS. The application runs a batch job every hour and is CPU intensive. The batch job takes 15 minutes on average with an on-premises server. The server has 64 virtual CPU (vCPU) and 512 GiB of memory.
Which solution will run the batch job within 15 minutes with the LEAST operational overhead?
Other
Community
UAnonymous
A
Use AWS Lambda with functional scaling.
B
Use Amazon Elastic Container Service (Amazon ECS) with AWS Fargate.
C
Use Amazon Lightsail with AWS Auto Scaling.
D
Use AWS Batch on Amazon EC2.
Explanation:
Explanation
Correct Answer: D - Use AWS Batch on Amazon EC2
AWS Batch is specifically designed for running batch computing workloads on AWS. Here's why this is the best choice:
Key Factors:
- CPU-intensive workload: The application requires 64 vCPU and 512 GiB memory, which is a substantial compute requirement.
- Batch job nature: Runs every hour for 15 minutes - this is a classic batch processing pattern.
- Least operational overhead: AWS Batch manages the provisioning, scheduling, and scaling of compute resources.
Why AWS Batch is optimal:
- Automatic resource provisioning: AWS Batch automatically provisions EC2 instances with the required specifications (64 vCPU, 512 GiB memory)
- Job scheduling: Handles job queuing and scheduling automatically
- Cost optimization: Only runs instances when jobs need to execute, then terminates them
- Minimal management: No need to manage clusters, scaling policies, or instance lifecycle
- Integration: Works seamlessly with other AWS services
Why other options are less optimal:
A. AWS Lambda:
- Lambda has limitations (15-minute timeout, memory up to 10GB, CPU scaling based on memory)
- Not suitable for 64 vCPU workloads
- Would require complex parallelization and coordination
B. Amazon ECS with Fargate:
- Fargate has resource limits (currently up to 16 vCPU and 120GB memory per task)
- Would require multiple tasks to achieve 64 vCPU
- More operational overhead for scheduling and coordination
C. Amazon Lightsail with Auto Scaling:
- Lightsail is designed for simpler workloads
- Auto Scaling adds operational complexity
- Not optimized for batch processing
D. AWS Batch on EC2:
- ✓ Specifically designed for batch workloads
- ✓ Can provision large EC2 instances (up to 448 vCPU, 24TB memory)
- ✓ Minimal operational overhead - AWS manages scheduling and provisioning
- ✓ Cost-effective - only pay for compute when jobs run
Additional Considerations:
- AWS Batch can use Spot Instances for additional cost savings
- Job dependencies and retries are built-in
- Monitoring and logging integration with CloudWatch
- Supports Docker containers for application packaging
This solution provides the required compute power while minimizing operational overhead, making it the most appropriate choice for this CPU-intensive batch workload.
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