CLF-C02 Cloud Technology and Services Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  AWS Lambda

  Why it's wrong here

  Standard AWS Lambda functions run in regional endpoints (e.g., us-east-1), not at CloudFront edge locations. While Lambda is serverless and can generate thumbnails, the latency for a user in Mumbai reaching a function in us-east-1 is significantly higher than running the same code at an edge location closer to that user. Lambda@Edge is specifically designed for this use case by running Lambda functions at the 400+ CloudFront points of presence, so plain Lambda misses the core requirement of low-latency, edge-based content processing.

  When this WOULD be correct

  A company needs to process uploaded images in a central S3 bucket, generating thumbnails asynchronously. The solution must run custom code without servers, triggered by S3 events. AWS Lambda would be correct because it can be triggered by S3 events and does not require edge processing.

• ✓

  AWS Lambda@Edge

  Why this is correct

  AWS Lambda@Edge is a feature of Amazon CloudFront that runs Lambda functions at AWS edge locations in response to CloudFront events. It is serverless, scales automatically, and is ideal for processing content close to users, such as on-the-fly thumbnail generation.

• ✗

  Amazon EC2 instances in an Auto Scaling group

  Why it's wrong here

  Amazon EC2 instances in an Auto Scaling group still run in specific AWS Regions, not at CloudFront edge locations, so requests from global viewers must traverse the internet back to that region, adding latency. Even with auto scaling, you must manage EC2 capacity, patch the operating system, and handle failover yourself, making it far more operational overhead than a serverless edge function. While it could generate thumbnails, it cannot do so with the same sub-100ms edge performance or pay-per-request cost profile as Lambda@Edge.

  When this WOULD be correct

  A company needs to run a custom video transcoding application that requires significant CPU and memory resources, and the processing must be scalable and fault-tolerant. The solution can provision EC2 instances in an Auto Scaling group behind an Application Load Balancer to handle the workload, and server management is acceptable.

• ✗

  Amazon ElastiCache

  Why it's wrong here

  Amazon ElastiCache is an in-memory data store (Redis or Memcached) that caches frequently accessed data like database query results or session state. It does not execute user-provided code, so it cannot generate thumbnail images or transform video content. Even if you cached pre-generated thumbnails, ElastiCache nodes run regionally, not at edge locations, and you would still need a separate compute service (like Lambda) to generate the thumbnails in the first place.

  When this WOULD be correct

  A company wants to reduce latency for frequently accessed database query results by caching them at edge locations. The solution must use a managed caching service that integrates with CloudFront without provisioning servers.

Option-by-option analysis

Why each answer is right or wrong

Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The CLF-C02 exam frequently reuses these exact scenarios with slightly different constraints.

Analysis generated from the official CLF-C02blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”

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