Lambda Layers and Dependencies Essentials Quiz Quiz

Explore foundational concepts of Lambda Layers and dependency management with these multiple-choice questions. Perfect for anyone aiming to enhance their understanding of deploying and updating reusable code in serverless computing environments.

1. Purpose of Lambda Layers

   What is the primary purpose of using a Lambda Layer in a serverless function setup?

   1. To provide additional CPU resources to a function
   2. To store reusable code and dependencies separately from the main function package
   3. To enable direct public access to environment variables
   4. To increase the memory allocation of a function

   Explanation: Lambda Layers allow you to package and manage code and dependencies separately from the main function, making updates and reusability easier. Increasing memory or CPU resources is handled through function configuration, not layers. Allowing public access to environment variables is unrelated and not a layer feature.

2. Maximum Number of Layers

   How many Lambda Layers can you include in a single function at one time?

   1. 5
   2. 50
   3. 20
   4. 10

   Explanation: You can attach up to 5 Lambda Layers to a single function. Options 10, 20, and 50 are incorrect, as they exceed the supported limit. This limitation encourages efficient organization and management of shared resources.

3. Layer Versioning

   Why is versioning important when updating a Lambda Layer used by multiple functions?

   1. It combines all previous versions into a single update
   2. It ensures existing functions continue using their current dependency version until updated
   3. It automatically forces all functions to use the latest layer version
   4. It prevents any layer changes from taking effect

   Explanation: Layer versioning lets functions remain on a stable version until explicitly updated, providing safety and predictability. It does not force automatic updates to all functions or combine previous versions. Preventing all changes is not the intent of versioning.

4. Dependency Placement in Layer Zip

   When preparing a Lambda Layer to include Python dependencies, which directory should the libraries be placed in within the zip file?

   1. src/dependencies/
   2. layer/python_packages/
   3. lambda/dependency_folder/
   4. python/lib/python3.x/site-packages/

   Explanation: Python dependencies for Lambda Layers must be in the python/lib/python3.x/site-packages/ directory for proper import. The other folder paths do not match the expected directory structure for Python's import system in Lambda, which could prevent your dependencies from loading.

5. Sharing Layers Across Functions

   What is one benefit of using Lambda Layers to share dependencies between multiple serverless functions?

   1. It reduces duplicate code and simplifies updates
   2. It encrypts all function data by default
   3. It eliminates the need for any code packaging
   4. It automatically merges all function logs

   Explanation: By centralizing shared code or dependencies in Layers, different functions can access the same components, avoiding redundancy. Log merging and data encryption are unrelated to layer sharing, and packaging code is still necessary, though streamlined by using layers.

6. Managing Layer Dependencies

   If your serverless function requires multiple external libraries, what is the recommended way to make them available using Lambda Layers?

   1. List the dependencies in a README file included with the function
   2. Reference the libraries in a requirements.txt inside the function code only
   3. Bundle the required libraries into a layer and attach it to the function
   4. Add library references directly in the function's environment variables

   Explanation: Packaging libraries into a layer and attaching it ensures the function can access and use them at runtime. Environment variables and README files do not install or provide dependencies. Only including requirements.txt without packaging does not deploy the necessary libraries.

7. Updating Layer Dependencies

   Which step is necessary after you update a Lambda Layer to a new version to ensure your function uses the latest dependencies?

   1. Rename your Lambda function
   2. Edit the environment variables
   3. Restart the serverless infrastructure
   4. Update your function to reference the new layer version

   Explanation: After publishing a new layer version, you must explicitly update your function's configuration to use the new version. Restarting infrastructure, renaming functions, or changing environment variables doesn't update the layer reference.

8. Layer Size Limit

   What is the maximum compressed size allowed for a single Lambda Layer when uploading it?

   1. 50 MB
   2. 150 MB
   3. 250 MB
   4. 100 MB

   Explanation: The compressed archive for a Lambda Layer must not exceed 50 MB. The higher options of 100 MB, 150 MB, and 250 MB do not reflect the current limit, and exceeding this size prevents upload and deployment of the layer.

9. Language Support in Layers

   Which programming languages can Lambda Layers support for shared code and dependencies?

   1. Only Python
   2. Multiple languages such as Python, Node.js, and Java
   3. Only compiled languages
   4. Only JavaScript

   Explanation: Lambda Layers can contain libraries or shared code for various supported languages, including Python, JavaScript, and Java. Restricting them to only Python, only JavaScript, or only compiled languages is inaccurate, as layers are flexible to different runtimes.

10. Public vs Private Layers

    What is a key consideration when publishing a Lambda Layer as public?

    1. Anyone can access and attach your layer to their own function
    2. It increases the size limit of the layer
    3. Only your own functions can use the layer
    4. It automatically encrypts the layer contents

    Explanation: Publishing a layer as public means it is accessible by any user who wishes to attach it to their own functions. Private layers are restricted to your own usage. Public layers are not automatically encrypted, nor do they gain an increased size limit.