Practice serverless vocabulary: on-demand functions, cold starts, invocation-based pricing, timeouts, event-driven architecture, and serverless vs. containers trade-offs.
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Your team says 'The function runs on-demand.' What does on-demand execution mean in serverless?
Serverless functions are event-triggered and on-demand — infrastructure is provisioned when a trigger fires and de-provisioned (scales to zero) when not needed. You pay only when the function runs, not for idle capacity.
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A performance report notes 'cold start latency is 800ms on first invocation.' What is a cold start?
A cold start occurs when a serverless function is invoked after being idle (the container was de-provisioned). The platform must provision a new execution environment, which adds latency. Subsequent 'warm' invocations reuse the running container and are much faster.
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Your architecture notes say 'The function has a 15-minute timeout limit (AWS Lambda).' What happens if the function exceeds this limit?
AWS Lambda enforces a maximum execution timeout of 15 minutes. If a function runs longer, Lambda terminates it. This makes Lambda unsuitable for long-running tasks — those should use containers, Step Functions, or other compute options.
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A system diagram shows 'event-driven invocation' for a serverless function. What triggers this function?
Serverless functions are typically triggered by events: an S3 object upload, an SQS/Kafka message, an HTTP request via API Gateway, a database stream, or a scheduled timer. The event-driven model is fundamental to serverless architecture.
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A trade-off analysis compares 'serverless vs. containers.' Which statement best captures a key trade-off?
The core serverless vs. containers trade-off: serverless minimizes operational burden and scales automatically to zero (cost-efficient for sporadic workloads) but has cold starts, execution limits, and vendor lock-in. Containers give more control, predictable performance, and no execution limits but require orchestration and management.