AWS Certified Solutions Architect – Associate (SAA-C03)Design Resilient ArchitecturesMedium
A media streaming company is building a new video processing pipeline that needs to handle highly variable workloads, from a few hundred videos per hour to tens of thousands during peak events. The processing tasks are stateless and can be executed independently. The company wants to minimize operational overhead and only pay for the compute resources consumed during actual processing. Which AWS service is most suitable for this use case?
- AAWS Lambda functions triggered by S3 events.
- BAWS Batch with Fargate compute environment.
- CAmazon EMR clusters for big data processing.
- DAmazon EC2 instances in an Auto Scaling group.
Show answer & explanationAnswer & explanation
Correct answer: A. AWS Lambda functions triggered by S3 events.
AWS Lambda is a serverless compute service that automatically scales with demand, executing code only when triggered. This perfectly matches the requirement for highly variable, stateless workloads, minimizing operational overhead and ensuring payment only for actual compute time, which is ideal for event-driven video processing.
Why the other options are wrong
- B. AWS Batch is suitable for batch computing, but Lambda offers even finer-grained scaling and lower operational overhead for event-driven, stateless tasks.
- C. Amazon EMR is for big data analytics using frameworks like Hadoop, not typically for individual stateless video processing tasks.
- D. EC2 Auto Scaling groups manage instances but still incur costs for running instances and require more operational overhead than serverless.
AWS Lambda
A serverless compute service that runs code in response to events and automatically manages the underlying compute resources.
- Event-driven execution.
- Automatically scales from zero to meet demand.
- Pay-per-execution model (compute time and requests).
Memory trick: Lambda is like a tiny robot that wakes up only when it hears a doorbell.