Being good neighbors - Rate limiting in a serverless world
summary
Explains why rate limiting matters for serverless applications that interact with other services and resources, focusing on preventing overloads and unintended DDoS-like behavior. Covers design and operational approaches to implement rate limiting in cloud serverless environments so your functions behave as a “good neighbor” when integrating with non-serverless systems.
AI-written summary · about
chapters (15)
- 0:00Intro
- 1:44Nielsen: Processing 55TB of Data Per Day with AWS Lambda
- 3:10Serverless benefits
- 3:35Automatic scaling
- 6:10Non-serverless scaling might be hard
- 7:12Serverless functions are isolated and egoistic
- 8:16What can possibly go wrong?
- 12:36The basics-Set function concurency
- 14:22Think asynchronously
- 15:13Use Asynchronous invocations and buffers
- 17:25Handling RDS connections
- 19:44Reduce number of calls to legacy systems - Cache layer
- 21:06Custom rate limit by file processing size
- 23:19Set the timeout!
- 24:51Retries and backing off between retries
related talks
44mApplying principles of chaos engineering to serverless
55mConfusion In The Land Of The Serverless
27mSite Reliability in the Serverless Age
52mConfusion In The Land Of The Serverless
51mConfusion In The Land Of The Serverless
49mYou Don't Want Serverless
53mBottlenecks in Serverless Applications
43mApplying the Principles of Chaos to Serverless