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Zorluk: KolayDebugging Lambda Execution and Configuration Issues

A developer designs an AWS Lambda function to process event logs. To track processed message IDs within a test execution, the developer declares a global list variable `processed_ids = []` outside the Lambda handler function. During testing, the developer observes that subsequent invocations of the function run slower, eventually timing out, and contain data from previous invocations. Which of the following explains why this issue is occurring?

  1. AWS Lambda reuses the execution context for subsequent invocations, causing the global list variable to persist and continuously grow in size, consuming memory and processing time.Cevap
  2. B
    AWS Lambda destroys and recreates the execution environment for every invocation, but the global variable is cached by the AWS Lambda service itself, requiring the developer to clear the cache via SDK.
  3. C
    The Lambda function is associated with a private VPC subnet without an active NAT Gateway, preventing the global scope from being re-initialized by the AWS Lambda service API.
  4. D
    The execution context is isolated per invocation, but the global variable undergoes memory leaks directly to the host operating system virtual machine, causing the execution to hang.

Cevap

AWS Lambda reuses the execution context for subsequent invocations, causing the global list variable to persist and continuously grow in size, consuming memory and processing time.
AWS Lambda optimizes performance by reusing the execution environment for subsequent invocations. Because the list is declared outside the handler, it is only initialized once (during the cold start). Warm invocations append items to the same list in memory, causing it to grow indefinitely, which leads to increased latency and timeouts.

Adım Adım Çözüm

1
Analyze the scope of the variable initialization.
The variable `processed_ids` is declared outside the handler function, making it global to the execution environment.
Variables declared outside the handler are initialized during the initialization phase (cold start) and remain in memory as long as the container is active.
2
Evaluate the behavior of AWS Lambda container reuse (warm starts).
Subsequent invocations use the same warm container to process events quickly without running the initialization code again.
Reusing the container means that the global state, including the `processed_ids` list, is preserved between executions.
3
Identify the cause of the performance degradation.
As new IDs are appended to the global list on every invocation, the list grows larger, leading to higher memory consumption and slower processing times.
Since the list is never cleared and keeps growing, the function eventually runs out of memory or times out.

Anahtar Kavram

AWS Lambda execution context reuse and its impact on global state management.
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Debugging Lambda Execution and Configuration Issues

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