Speed meets scale: Load testing SageMakerAI endpoints with Observe.AI’s testing tool

This article demonstrates how to use OLAF (One Load Audit Framework), an open-source tool developed by Observe.ai, to load test Amazon SageMaker inference endpoints efficiently.

• OLAF integrates with SageMaker to identify performance bottlenecks and measure latency/throughput under various loads
• Reduces ML endpoint testing time from weeks to hours through automated load testing
• Provides real-time performance monitoring dashboard and downloadable CSV reports
• Supports multiple model types, serialization options, and concurrent user simulation
• Available as free open-source tool on GitHub under Apache 2.0 license
• Runs as Docker container with web UI for configuring and executing load tests
• Helps optimize GPU instance selection and ML pipeline performance without compromising accuracy

OLAF streamlines SageMaker endpoint optimization by eliminating the need for custom testing infrastructure, enabling teams to make data-driven decisions about scaling and resource allocation.