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What are Lambda layers, and when would you use them?

Difficulty: 5/10
code reuse, dependency management, deployment size

Lambda layers are a distribution mechanism for libraries, custom runtimes, and other dependencies that can be used by multiple Lambda functions. They help you avoid duplicating code across functions and keep your deployment packages smaller and more maintainable.

When to Use Lambda Layers
  1. 1

    Sharing common code or utility functions across multiple Lambda functions

  2. 2

    Including third-party libraries or frameworks (e.g., requests for Python or axios for Node.js)

  3. 3

    Packaging custom runtimes or binaries

  4. 4

    Reducing deployment package size by moving dependencies into a separate layer

  5. 5

    Enforcing standardized dependencies or configurations across teams or projects

Creating and Using a Lambda Layer via AWS CLI

Scenario Questions

0-2 years experience

  1. 1You need to add the same third‑party Python library to three Lambda functions. How would you use a Lambda layer to accomplish this?
  2. 2If you attach a layer that is 30 MB to a function whose own code is 25 MB, will the function deploy successfully? Why or why not?

2-5 years experience

  1. 1During a sprint you notice that a new version of a shared library breaks one of the functions that uses a layer. Walk me through how you would debug and fix the issue.
  2. 2We have a microservice that spins up many Lambdas, each needing a large native binary. Explain the trade‑offs of putting that binary in a layer versus bundling it with each function.

5-8 years experience

  1. 1Our team wants to standardize a security‑related SDK across dozens of Lambdas in multiple accounts. How would you design a layer strategy that handles versioning, cross‑account access, and minimal cold‑start impact?
  2. 2If a layer grows to 45 MB and you start seeing increased cold‑start latency, what steps would you take to investigate and mitigate the performance degradation?

8+ years experience

  1. 1We are migrating a legacy monolith to a serverless architecture and want to reuse existing shared libraries via layers. Describe the architectural considerations, including CI/CD pipeline changes, governance, and how you’d avoid layer sprawl over time.
  2. 2How would you approach a cross‑team policy for layer publishing that balances rapid iteration with stability, especially when multiple teams depend on the same layer in production?

Follow-up Questions

  • How do you version a layer and ensure functions pick up the right version?
  • What happens if a function's runtime is incompatible with a layer's content?
  • Can you describe a situation where using a layer could actually hurt performance?
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