DVA-C02 Troubleshooting and Optimization 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.

• ✗

  Increase the function's memory allocation to 3008 MB.

  Why it's wrong here

  While increasing memory allocation does provide proportional CPU power, which can accelerate the *execution* phase of a Lambda function, it does not inherently prevent or reduce cold start latency. Cold starts are primarily caused by the time required to initialize a new execution environment, download code, and run global initialization logic, which still occurs regardless of the allocated memory. This action would only improve performance during the function's active processing, not during its initial setup.

• ✓

  Enable provisioned concurrency on the function.

  Why this is correct

  Provisioned concurrency pre-initializes a specified number of execution environments for a Lambda function, ensuring they are ready to process requests immediately. This effectively eliminates cold start latency for invocations routed to these pre-warmed instances, as the entire initialization phase (including code download, runtime bootstrapping, and `init` code execution) has already completed. It guarantees consistently low latency for critical, latency-sensitive applications by maintaining a pool of ready-to-go containers.

• ✗

  Move the large library to a Lambda layer.

  Why it's wrong here

  Moving a large library to a Lambda layer helps in code organization, reduces the primary deployment package size, and facilitates sharing common dependencies across multiple functions. However, during a cold start, the Lambda service still needs to download and extract the layer's contents along with the function's code into the execution environment. This process contributes to the overall initialization time, meaning layers do not inherently reduce cold start latency but rather manage dependencies more efficiently.

• ✗

  Replace the RDS database with Amazon DynamoDB.

  Why it's wrong here

  Replacing an RDS database with Amazon DynamoDB changes the backend data store technology and its access patterns. While DynamoDB might offer different performance characteristics for database operations, it has no direct impact on the Lambda function's cold start behavior. Cold starts are related to the Lambda execution environment's initialization process, not the type or performance of the external database it connects to. The time taken to establish a database connection might be part of the function's *execution* time, but not its *initialization* time.