Overview

OpenSRE is the pioneering open-source framework designed to empower engineers in building and deploying AI-powered Site Reliability Engineering (SRE) agents. It provides a comprehensive toolkit and a sophisticated training and evaluation environment, enabling the creation of intelligent agents capable of autonomously investigating and resolving production incidents. By connecting with over 40 existing tools and services, OpenSRE streamlines incident response in the AI era, allowing you to define custom workflows and gain deep insights into your infrastructure.

Key Features

• AI-Powered Incident Response: Develop and deploy AI SRE agents for automated production incident investigation and resolution.
• Reinforcement Learning Environment: Offers a robust environment for training and evaluating AI agents with realistic synthetic incident simulations and end-to-end tests.
• Extensive Integrations: Seamlessly connects with a vast ecosystem of over 40 tools across observability, infrastructure, databases, incident management, and communication platforms.
• Customizable Workflows: Define and implement your own incident response workflows tailored to your specific infrastructure and operational needs.
• Evidence-Backed Analysis: Agents provide structured investigation reports with probable root causes, directly linking conclusions to supporting data from logs, metrics, and traces.
• Runbook-Aware Reasoning: OpenSRE agents can ingest and apply your existing runbooks for more informed and consistent incident handling.
• LLM Flexibility: Supports a wide range of LLM providers, including Anthropic, OpenAI, Ollama, Google Gemini, OpenRouter, and NVIDIA NIM, allowing you to choose the best model for your needs.
• Synthetic Incident Simulation: Facilitates rigorous testing and training through scored synthetic RCA suites that assess root-cause accuracy and resilience against adversarial inputs.
• Real-World End-to-End Testing: Conducts comprehensive tests across cloud-backed scenarios, including Kubernetes, AWS services, and more.

Typical Use Cases

• Automated Incident Triage and Root Cause Analysis: Deploy AI agents to automatically investigate alerts, correlate signals from various sources, and pinpoint the root cause of production issues.
• Proactive Failure Detection: Leverage predictive capabilities to identify emerging issues before they impact users.
• Runbook Automation: Enhance operational efficiency by enabling AI agents to execute steps from your existing runbooks.
• Building and Benchmarking AI SRE Agents: Utilize OpenSRE as the definitive platform for developing, training, and evaluating the performance of SRE AI agents against a growing library of failure scenarios.
• Onboarding and Training for SRE Teams: Provide a realistic environment for SREs to train and experiment with AI-driven incident response strategies.