SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company runs a serverless image-processing pipeline. When an image is uploaded to an S3 bucket, an AWS Lambda function is invoked to resize it and write the output to another S3 bucket. The company wants to reduce the cost of Lambda invocations and improve performance for a new workload that processes large batches of images at scheduled intervals. The images are already stored in S3 and do not require immediate processing. What is the MOST cost-effective solution?
⚠ Common exam trap
The trap here is assuming that serverless options like Lambda or Fargate are always the most cost-effective for any workload, overlooking that batch processing with Spot Instances can be far cheaper for large, delay-tolerant jobs.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use AWS Batch with a managed compute environment that uses Spot Instances to process the images in parallel.
AWS Batch is purpose-built for batch computing, allowing the use of Spot Instances to reduce costs significantly. It can process large volumes of images in parallel and be scheduled to run at intervals, matching the requirement for non-urgent, cost-effective batch processing. Lambda and Fargate are more expensive for long-running, high-volume tasks, and Step Functions adds orchestration overhead without addressing the core compute cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use AWS Lambda with a larger memory allocation and increase the timeout to 15 minutes.
Why it's wrong here
Increasing memory and timeout may allow longer-running functions, but Lambda still charges per invocation and per GB-second. For large batches of images that do not need immediate processing, this approach remains more expensive than a batch-oriented service like AWS Batch, which can use Spot Instances. It also does not address the per-invocation overhead for many small files, and the 15-minute limit may still be insufficient for very large batches.
- ✗
Use an AWS Step Functions state machine with parallel branches to orchestrate Lambda functions for each image.
Why it's wrong here
Step Functions can coordinate parallel Lambda executions, but it still relies on Lambda for compute, incurring both Lambda and Step Functions costs. For large batches, this multiplies expenses and may hit concurrency limits. It is better suited for complex workflows with multiple steps and human approval, not for simple, high-volume batch processing where cost is the primary concern.
- ✗
Use Amazon ECS with Fargate tasks triggered by an Amazon EventBridge scheduled rule to process the images.
Why it's wrong here
ECS with Fargate provides serverless containers but is charged per vCPU and memory per second, which can be more expensive than Spot Instances for long-running batch jobs. While it can be scheduled via EventBridge, it lacks the native batch job queuing, dependency management, and automatic scaling to zero that AWS Batch offers. For large-scale, cost-sensitive batch processing, Fargate is not the most cost-effective choice.
- ✓
Use AWS Batch with a managed compute environment that uses Spot Instances to process the images in parallel.
Why this is correct
AWS Batch is designed for batch computing workloads and can automatically provision optimal quantities of compute resources, including Spot Instances, which can significantly reduce cost. It supports parallel processing of large numbers of images and can be scheduled to run at intervals. This aligns with the requirement for cost-effective, scheduled batch processing without immediate processing needs, and avoids Lambda's per-invocation pricing model.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This SAP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAP-C02 exam.