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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:
Last modified 3mo ago