Lambda layers for shared code in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Lambda Layers Usage

What is the primary benefit of using Lambda layers for shared code in AWS Lambda functions?

A They allow multiple Lambda functions to share common code without duplicating it in each function's deployment package.

B They automatically scale Lambda functions based on the shared code size.

C They provide a graphical interface to edit Lambda function code directly in the AWS console.

D They enable Lambda functions to run in a dedicated virtual private cloud (VPC).

💡 Hint

Think about how to avoid repeating the same code in many places.

Lambda layers let you package libraries and code separately, so multiple functions can use them without copying the code into each function.

❓ Configuration

intermediate

Configuring a Lambda Function with a Layer

You have created a Lambda layer containing shared Python libraries. How do you configure your Lambda function to use this layer?

A Include the layer's code directly inside the Lambda function's deployment package.

B Add the layer's ARN to the Lambda function's Layers configuration in the AWS console or deployment template.

C Set an environment variable pointing to the layer's S3 bucket location.

D Create a new IAM role that grants access to the layer's code.

💡 Hint

Think about how AWS links layers to functions.

Lambda functions use layers by referencing the layer's ARN in their configuration, which tells AWS to include the layer's content at runtime.

❓ Architecture

advanced

Layer Versioning Impact on Lambda Deployment

You have a Lambda layer with multiple versions. Your Lambda function uses version 3 of this layer. You publish version 4 of the layer with updates. What happens to your Lambda function?

A AWS merges versions 3 and 4 and uses the combined code automatically.

B The Lambda function automatically switches to version 4 without redeployment.

C The Lambda function continues using version 3 until you explicitly update it to use version 4.

D The Lambda function fails to run until you update the layer version in its configuration.

💡 Hint

Consider how versioning controls what code a function uses.

Lambda functions use a specific version of a layer. They do not update automatically when new versions are published. You must update the function configuration to use the new version.

❓ security

advanced

Security Best Practices for Lambda Layers

Which practice improves security when using Lambda layers with shared code?

A Disable encryption on the layer's content to improve performance.

B Embed sensitive credentials directly inside the layer's code for easy access.

C Use layers only from public sources without reviewing their content.

D Limit permissions on the layer's S3 bucket and restrict who can publish or update layers.

💡 Hint

Think about controlling access and protecting code integrity.

Restricting access to layer storage and publishing prevents unauthorized changes and protects your Lambda functions from malicious code.

❓ service_behavior

expert

Lambda Layer Size Limits and Deployment Impact

You have a Lambda layer of 60 MB unzipped size. Your Lambda function deployment package is 50 MB unzipped. What is the maximum unzipped size of the combined deployment package and layers at runtime, and what happens if the limit is exceeded?

A The combined unzipped size limit is 250 MB; if exceeded, deployment fails with an error.

B The combined unzipped size limit is 100 MB; if exceeded, Lambda automatically compresses the package to fit.

C There is no size limit for layers combined with deployment packages.

D The combined unzipped size limit is 150 MB; if exceeded, Lambda truncates the package silently.

💡 Hint

Check AWS Lambda limits for deployment package sizes.

AWS Lambda limits the total unzipped size of deployment package plus layers to 250 MB. If this is exceeded, deployment fails and you must reduce size.