Key Requirements:
Handle traffic spikes efficiently and reduce latency caused by cold starts.
Optimize costs during low traffic periods.
Analysis of Options:
Option A:
Provisioned Concurrency:Reduces cold start latency by pre-warming Lambda environments for the required number of concurrent executions.
AWS Application Auto Scaling:Automatically adjusts provisioned concurrency based on demand, ensuring cost optimization by scaling down during low traffic.
Correct Approach:Provides a balance between performance during traffic spikes and cost optimization during idle periods.
Option B:
Using EC2 instances with Auto Scaling introduces unnecessary complexity for a serverless architecture. It requires additional management and does not address the issue of cold starts for Lambda.
Incorrect Approach:Contradicts the serverless design philosophy and increases operational overhead.
Option C:
Setting a fixed concurrency level ensures performance during spikes but does not optimize costs during low traffic. This approach would maintain provisioned instances unnecessarily.
Incorrect Approach:Lacks cost optimization.
Option D:
Using EventBridge Scheduler for periodic invocations may reduce cold starts but does not dynamically scale based on traffic demand. It also leads to unnecessary invocations during idle times.
Incorrect Approach:Suboptimal for high traffic fluctuations and cost control.
AWS Solution Architect References:
AWS Lambda Provisioned Concurrency
AWS Application Auto Scaling with Lambda
