HolmesGPT is an SRE agent that automates incident investigation and root cause analysis across any infrastructure stack using large language models.
The tool addresses the challenge of manually investigating production incidents by running an agentic loop that queries live observability data from multiple sources to identify root causes. It handles petabyte-scale data through server-side filtering and JSON tree traversal, keeps memory usage safe with per-tool limits and streaming to disk, and integrates deeply with platforms like Prometheus, Grafana, Datadog, Kubernetes, AlertManager, PagerDuty, and OpsGenie. The agent works with any LLM provider including OpenAI, Anthropic, Azure, Bedrock, and Gemini, and does not require Kubernetes—it runs on VMs, bare metal, or cloud services.
Teams should adopt this tool if they need automated incident response across heterogeneous infrastructure. It suits organizations running Kubernetes alongside VMs, cloud providers, and SaaS platforms who want a single agent to investigate across all of them. The operator mode distinguishes it from typical troubleshooting agents by running continuously in the background to spot problems before customers notice, automatically messaging Slack with findings, and even opening pull requests to fix issues when connected to GitHub.
The project shows active development with regular feature additions, including the recent operator mode capability for proactive monitoring and the deployment verification and scheduled health checks features. The codebase receives ongoing maintenance and refinement of core functionality around memory safety and data handling at scale.
