OpsWorker Documentation
Explore how you can use OpsWorker to resolve production incidents and development issues with AI that understands your code, infrastructure, and telemetry.
🚀 Get Started
Learn what OpsWorker is, understand core concepts, and get your first AI-powered investigation running in minutes.
Start here →🔧 Setup & Onboarding
Connect your Kubernetes clusters, link your alerting systems, and configure OpsWorker for your environment.
Setup guide →💡 Use Cases
Discover how OpsWorker helps investigate incidents, debug production issues, reduce alert noise, and measure engineering efficiency.
Explore use cases →⚡ Platform Capabilities
Deep-dive into AI Investigations, AI Chat, Alert Intelligence, Recommendations, AI Memory, Knowledge Sources, and Operational Insights.
Explore capabilities →🧠 AI Memory
Layered persistent context — personal, cluster, and organization scopes — that the AI uses in every investigation and chat session.
Learn about memory →📚 Knowledge Sources
Feed internal runbooks, postmortems, and best-practice rules so OpsWorker references your operational knowledge.
Learn about knowledge sources →🔗 Integrations
Connect with Kubernetes (EKS, AKS, GKE), Prometheus, Grafana (Alerting and MCP), Datadog, Slack, GitHub, GitLab, and your own LLM.
Browse integrations →⚙️ Configuration
Manage workspaces, users & access control, SSO, clusters, alert rules, and notification routing.
Configure →🏗️ Architecture & Deployment
Understand the system design, data flow, security model, and available deployment options including SaaS and private cloud.
Learn architecture →🤖 Kubernetes Agent
Install and configure the OpsWorker Kubernetes Agent that powers cluster-level intelligence, RBAC, and data collection.
Agent docs →🛠️ Operations
Upgrade, troubleshoot, and maintain your OpsWorker deployment. Includes version compatibility and health checks.
Operations →❓ FAQ
Answers to common questions about getting started, security, billing, troubleshooting, and integrations.
Read FAQ →