First DynamoDB query slow in Lambda - SnapStart setup expiry

The DynamoDB client initialization in SnapStart is valid as long as the Lambda container is warm. If the container is recycled due to inactivity, a cold start will occur, and the client will need to be reinitialized, which may increase execution time.

Solutions: Keep the container warm: Use periodic invocations (with CloudWatch or EventBridge) to prevent the container from being recycled.

Lazy initialization: Initialize the client only when it is actually needed, not in the constructor.

Use AWS SDK V3: It is faster and optimized.

Increase memory: Higher memory allocation can improve initialization time.

Let me know if this helped! Feel free to ask if you need any further clarification.

When using Lambda SnapStart with DynamoDB, initializing your DynamoDB client in the constructor rather than in the handler is indeed a good practice to improve performance. However, you're right to be concerned about the longevity of this initialization.

The SnapStart feature creates a snapshot of your Lambda function's initialized state, including any AWS SDK clients you've set up. This snapshot is then used to quickly start new function instances. However, it's important to note that certain types of data, especially those related to authentication or temporary credentials, may become stale over time.

For AWS SDK clients like the DynamoDB client, the initialization itself (loading classes, setting up connection pools, etc.) remains valid and beneficial. However, any temporary credentials or session tokens associated with the client may expire.

AWS Lambda automatically patches SnapStart snapshots with the latest runtime and security updates, which helps maintain the overall health of the snapshot. However, for best practices and to ensure your function remains reliable over extended periods, you should consider the following:

1. Use IAM roles for authentication rather than hard-coded credentials.
2. Implement a mechanism to refresh or validate the client before use, especially for long-running snapshots.
3. Consider using the AWS SDK's built-in credential providers, which can automatically refresh credentials when needed.

While there isn't a specific expiration time for the SnapStart image itself, it's a good practice to periodically update your function by publishing new versions. This ensures you're working with the most up-to-date runtime and dependencies.

If you're concerned about potential issues with long-lived snapshots, you could implement a simple check in your handler to verify the client's validity and reinitialize if necessary. This way, you maintain the performance benefits of SnapStart while ensuring your function remains robust over time.

Remember, SnapStart is designed to improve startup performance, but it's also important to design your function to be resilient to potential staleness in the snapshot state.
Sources
Improving startup performance with Lambda SnapStart - AWS Lambda
Troubleshooting SnapStart errors for Lambda functions - AWS Lambda