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Difficulty: MediumDebugging Lambda Execution and Configuration Issues

A developer is troubleshooting an AWS Lambda function that processes large CSV data exports uploaded to an Amazon S3 bucket. The function is currently configured with 256 MB256\text{ MB} of memory and a timeout of 10 seconds10\text{ seconds}. During initial testing with small files, the function executes successfully. However, when processing larger files, the function consistently fails, and Amazon CloudWatch Logs show a `Task timed out after 10.00 seconds` error. Which action should the developer take to resolve this execution timeout issue?

  1. Increase the Lambda function's timeout configuration to allow more execution time, and allocate more memory to proportionally scale the CPU performance.Answer
  2. B
    Deploy the Lambda function in a public VPC subnet and assign a public IP address to the function's network interface to speed up S3 data transfer.
  3. C
    Move the file download and buffer arrays to the global execution context outside the handler to automatically persist state and bypass the execution timeout on subsequent runs.
  4. D
    Enable Provisioned Concurrency for the Lambda function to keep warm execution environments active and prevent the execution from timing out.

Answer

Increase the Lambda function's timeout configuration to allow more execution time, and allocate more memory to proportionally scale the CPU performance.
The correct action is to increase the Lambda function's timeout setting and allocate additional memory. Increasing the timeout directly extends the allowed run time of the function. Additionally, since AWS Lambda allocates CPU power proportionally to the configured memory size, increasing the memory allocation will speed up CPU-bound tasks like file parsing, preventing the function from timing out.

Step-by-Step Solution

1
Analyze the error message from CloudWatch Logs.
The log message `Task timed out after 10.00 seconds` indicates the function is hitting its configured execution time limit before completing the CSV processing.
Identifying the root cause as a timeout configuration limit is necessary before selecting the correct remediation strategy.
2
Evaluate the resource demands of the processing logic.
Processing larger files requires both more time and more compute power. In AWS Lambda, CPU performance scales proportionally with the allocated memory.
Understanding that increasing memory provides more CPU resources helps optimize processing speed for CPU-bound tasks like parsing CSV files.
3
Adjust the Lambda configuration settings.
Increasing the timeout limit beyond 10 seconds10\text{ seconds} and increasing the memory configuration beyond 256 MB256\text{ MB} allows the function to complete successfully.
This dual adjustment ensures the execution environment has both the raw computing power and the time limit necessary to handle larger payloads.

Key Concept

AWS Lambda resource allocation and execution limits
Estimated Time:1m 30s
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Topics

Debugging Lambda Execution and Configuration Issues

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