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docs/configuration/holmesgpt/holmesgpt-docs.rst

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For comprehensive HolmesGPT documentation, please visit the official HolmesGPT documentation site at `holmesgpt.dev <https://holmesgpt.dev>`_.
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Configuring HolmesGPT with Robusta
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-----------------------------------
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When configuring HolmesGPT with Robusta, follow the **Robusta Helm Chart configuration method** described in the HolmesGPT documentation rather than standalone CLI installation.
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Key points:
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* Use the ``enableHolmesGPT: true`` setting in your Robusta Helm values
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* Configure data sources and advanced settings using the Helm chart configuration examples provided in the HolmesGPT docs
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* Refer to the `Helm Configuration Reference <https://holmesgpt.dev/reference/helm-configuration/>`_ for advanced HolmesGPT settings specific to Robusta deployments
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Quick Links
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-----------
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* `HolmesGPT Main Documentation <https://holmesgpt.dev>`_
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* `Data Sources Configuration <https://holmesgpt.dev/data-sources/builtin-toolsets/>`_
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* `Helm Chart Configuration Reference <https://holmesgpt.dev/reference/helm-configuration/>`_
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For Robusta-specific HolmesGPT setup instructions, see:
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* :doc:`getting-started` - Quick setup guide for HolmesGPT with Robusta
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* :doc:`main-features` - Overview of AI analysis features
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For Robusta-specific setup instructions, see :doc:`getting-started`.

docs/configuration/holmesgpt/main-features.rst

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Robusta integrates `HolmesGPT <https://github.com/robusta-dev/holmesgpt>`_ to provide AI-powered root cause analysis for Kubernetes alerts and issues.
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What HolmesGPT Does
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-------------------
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**Automatic Investigation**
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When alerts fire, HolmesGPT automatically:
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* Analyzes pod logs and events
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* Examines resource metrics and limits
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* Checks recent deployments and changes
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* Investigates related resources and dependencies
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* Provides actionable recommendations
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**Multi-Source Analysis**
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HolmesGPT pulls data from:
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* Kubernetes API (pods, nodes, events, logs)
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* Prometheus metrics
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* Cloud provider APIs (AWS, Azure, GCP)
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* Application monitoring (Datadog, New Relic)
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* Log aggregation systems (Loki, OpenSearch, Coralogix)
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* And more via `extensible toolsets <https://holmesgpt.dev/data-sources/builtin-toolsets/>`_
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See HolmesGPT in Action
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-----------------------
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.. tab-set::
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.. tab-item:: AWS Troubleshooting
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.. raw:: html
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<div style="position: relative; padding-bottom: 56.25%; height: 0;">
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<iframe src="https://www.loom.com/embed/2e5e3a259a5c41018914c9abd8429f00"
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frameborder="0"
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webkitallowfullscreen
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mozallowfullscreen
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allowfullscreen
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style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;">
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</iframe>
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</div>
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.. tab-item:: CPU Spike Investigation
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.. raw:: html
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<div style="position: relative; padding-bottom: 56.25%; height: 0;">
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<iframe src="https://www.loom.com/embed/b63f0eba0fd74750929f37c16b3fca3b"
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frameborder="0"
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webkitallowfullscreen
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mozallowfullscreen
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allowfullscreen
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style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;">
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</iframe>
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</div>
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How to Use It
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-------------
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**Via @holmes in Slack**
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Ask natural language questions about your clusters:
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* ``@holmes what apps are crashing in prod-cluster?``
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* ``@holmes why is my alert firing on staging?``
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* ``@holmes investigate high memory usage in dev-cluster``
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Example Investigation
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---------------------
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Here's what HolmesGPT found for a CrashLoopBackOff alert:
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.. image:: /images/AI_Analysis_demo2.png
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:width: 1000px
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The AI identified:
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- The exact error from pod logs
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- The root cause (missing environment variable)
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- Recommended fix with example YAML
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- Related configuration issues
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Why Use HolmesGPT?
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------------------
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**Save Time**
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Stop manually checking logs, metrics, and events across multiple tools. HolmesGPT does it in seconds.
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**Reduce MTTR**
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Get to root cause faster with AI that understands Kubernetes patterns and common issues.
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**Learn as You Go**
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Each investigation explains what was checked and why, helping your team learn Kubernetes troubleshooting.
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**24/7 Coverage**
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AI investigations run automatically on every alert, even at 3 AM.
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Next Steps
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