A developer has created a large AWS Lambda function. Deployment of the function is failing because of an InvalidParameterValueException error. The error message indicates that the unzipped size of the function exceeds the maximum supported value. Which actions can the developer take to resolve this error? (Choose two.)
Select an option, then click Submit answer.
Reference / correct answer:
Move common libraries, function dependencies, and custom runtimes into Lambda layers.
Most accepted answer: E. Move common libraries, function dependencies, and custom runtimes into Lambda layers.
Community votes: A=2, C=4, D=1, E=5
Selected Answer: CE CE is the correct answer. upvoted 3 times
Selected Answer: CE in this case quota cannot be increased https://docs.aws.amazon.com/lambda/latest/dg/gettingstarted-limits.html#:~:text=The%20following%20quotas%20apply%20to%20function%20configuration%2C%20deployment%2C%20and%20execution.%20Except%20as%20noted%2C%20they%20can%27t%20be%20changed. upvoted 2 times
Selected Answer: CE C. Break up the function into multiple smaller functions. If the size of the Lambda function is too large, breaking it into smaller, more modular functions can help. Each function can be responsible for a specific part of the application's logic. This approach not only helps with deployment but also aligns with microservices best practices, potentially improving the maintainability and scalability of the application. E. Move common libraries, function dependencies, and custom runtimes into Lambda layers. Lambda layers are a way to manage and share common components across multiple Lambda functions. By moving libraries, dependencies, and runtimes into layers, you reduce the size of the Lambda function's deployment package. Layers can be shared across multiple functions, leading to more efficient use of storage and easier management of common code. upvoted 4 times
Selected Answer: CE C and E upvoted 2 times
A E no discussion upvoted 2 times