AWS Serverless Scaling Considerations for Lambda
Scaling Considerations for Lambda
Consider allocating account limit pool to a function's concurrency limitations.
You could use this to ensure a function's concurrency or to prevent overloading.
As an “emergency brake,” you can set a function concurrency limit to 0.
This would stop all function calls.
Beyond that, make sure you've tested all of your Lambda functions in an account.
Remember that AWS Organizations can help you manage multiple accounts.
Accounts can be grouped into logical groups, such as development vs. production.
You may nest organizations to create hierarchies and control access, resources, billing, and auditing.
Scaling Considerations for Lambda Video
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Lambda can scale to extremes.
It is called burst behavior, and it is included within concurrency.
When you receive a significant number of requests, Lambda will increase concurrency for your region.
An invocation burst is then added every minute until the function or account concurrency limit is reached.
Requests might be throttled if the account limit is larger than the burst.
Account for memory
It is also important to account for memory.
Memory is a parameter that affects performance.
Memory assignment affects how long your function runs and when it is throttled.
If your function takes 10 seconds and there are 25 requests per second, you need 250 concurrent calls to it.
More memory-intensive functions may be cheaper to operate due to their speed.
Related reads:Best Practices for Working with AWS Lambda Functions