Learn how Sedai uniquely optimizes AWS serverless functions to achieve your performance and cost goals.

Sedai autonomously optimizes two key aspects of AWS Lambdas:

  • Memory Allocation: Identifies optimal configuration based on your performance and/or cost goals

  • Autonomous Concurrency: Eliminates or reduces cold starts with marginal cost impact

Autonomous Concurrency

Sedai autonomously eliminates cold starts with little-to-no impact on cloud costs. Using a combination of the following, Sedai informs its central control and learning unit to manage continuous autonomous concurrency:

  • Sedai AV Lambda Extension: External extension written in Go; analyzes Lambda behavior such as runtime events, cold start duration, and concurrency patterns (this allows close Lambda monitoring without any overhead)

  • Traffic Seasonality: Monitors and builds a seasonality model in order to understand local and global trends and anticipate traffic fluctuations

  • Provisioned Concurrency: Monitors concurrency events as well as concurrency scaling based on seasonality

To view optimization opportunities for AWS Lambda, go to Optimization > Opportunities and select the Serverless tab.

Supported Runtimes

  • NodeJS 12 and above on x86_64

  • Python 3.7 and above on x86_64

  • Java 8 and above on x86_64

The static and runtime characteristics of the extension are limited to:

  • Additional 12 MB size in deployed Lambda layer

  • 0.1 ms latency overhead per 1,000 invocations

  • 0.11 ms execution time overhead per 1,000 invocations


You can deploy the AV Lambda extension manually or via your preferred IaC tool:

pageAV Lambda Extension

Last updated