HolmesGPT describes itself as
“Your 24/7 On-Call AI Agent – Solve alerts faster with automatic correlations, investigations, and more.”
It’s built to help with incident investigation and troubleshooting in cloud / observability / SRE environments.
In short:
When something breaks or an alert fires, HolmesGPT tries to help figure out why and propose what to fix.
It integrates with a bunch of tools and data-sources:
* cloud providers
* monitoring
* observability systems
* ticket systems
* alerting systems
This way it can gather data and investigate.
It supports LLM (large-language-model) backends (we plug in our LLM or API key) so the reasoning and investigation is performed by the LLM plus data the tool collects.
It is open source and has been accepted as a sandbox project in the Cloud Native Computing Foundation (CNCF).
HolmesGPT connects to various data sources:
* monitoring metrics (via Prometheus)
* logs (via Loki, DataDog)
* traces (via Tempo)
* cloud infra (AWS RDS in example)
* kubernetes state
* runbooks/documentation (e.g., Confluence)
It uses the LLM to take the gathered data plus context and generate an investigation:
“Here’s what I found, these are probable root causes, here’s what you should do.”
From the docs:
“HolmesGPT connects AI models with live observability data and organisational knowledge. It uses an agentic loop to analyze data from multiple sources and identify possible root causes.”
It can:
* write results back
* comments on tickets and alerts
* Slack messages
* suggest actions
* open pull requests for fixes
It claims read-only access by design (so it won’t modify production infra unless we hook in something explicitly) and we can use our own LLM API key if we prefer.
Because it uses an LLM, the quality of investigations depends heavily on the model, prompt engineering, context window, quality of data.
Observability data (logs, traces, metrics) can be huge. We may hit limits.
Be careful to avoid this situation:
https://fortune.com/2025/07/23/ai-coding-tool-replit-wiped-database-called-it-a-catastrophic-failure/
Enjoy #linux 🐧
Project source code available on Github:
https://github.com/HolmesGPT/holmesgpt
Well, that was exciting. See you in the next one!