Guide for implementing HolmesGPT - an AI agent for troubleshooting cloud-native environments. Use when investigating Kubernetes issues, analyzing alerts from Prometheus/AlertManager/PagerDuty, performing root cause analysis, configuring HolmesGPT installations (CLI/Helm/Docker), setting up AI providers (OpenAI/Anthropic/Azure), creating custom toolsets, or integrating with observability platforms (Grafana, Loki, Tempo, DataDog).
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---
name: holmesgpt-skill
description: Guide for implementing HolmesGPT - an AI agent for troubleshooting cloud-native environments. Use when investigating Kubernetes issues, analyzing alerts from Prometheus/AlertManager/PagerDuty, performing root cause analysis, configuring HolmesGPT installations (CLI/Helm/Docker), setting up AI providers (OpenAI/Anthropic/Azure), creating custom toolsets, or integrating with observability platforms (Grafana, Loki, Tempo, DataDog).
---
# HolmesGPT Skill
AI-powered troubleshooting for Kubernetes and cloud-native environments.
## Overview
HolmesGPT is a CNCF Sandbox project that connects AI models with live
observability data to investigate infrastructure problems, find root
causes, and suggest remediations. It operates with **read-only access**
and respects RBAC permissions, making it safe for production environments.
## Quick Reference
| Topic | Reference |
|-------|-----------|
| **Installation** | `references/installation.md` |
| **Configuration** | `references/configuration.md` |
| **Data Sources** | `references/data-sources.md` |
| **Commands** | `references/commands.md` |
| **Troubleshooting** | `references/troubleshooting.md` |
| **HTTP API** | `references/http-api.md` |
| **Integrations** | `references/integrations.md` |
## Key Features
- **Root Cause Analysis**: Investigates alerts and cluster issues
- **Multi-Source Integration**: 30+ toolsets (K8s, Prometheus, Grafana)
- **Alert Integration**: AlertManager, PagerDuty, OpsGenie, Jira, Slack
- **Interactive Mode**: Troubleshooting with `/run`, `/show`, `/clear`
- **Custom Toolsets**: Extend with proprietary tools via YAML configuration
- **CI/CD Integration**: Automated deployment failure investigation
## Installation Quick Start
### CLI (Homebrew)
```bash
brew tap robusta-dev/homebrew-holmesgpt
brew install holmesgpt
export ANTHROPIC_API_KEY="your-key" # or OPENAI_API_KEY
holmes ask "what pods are unhealthy?"
```
### Kubernetes (Helm)
```bash
helm repo add robusta https://robusta-charts.storage.googleapis.com
helm repo update
helm install holmesgpt robusta/holmes -f values.yaml
```
### Docker
```bash
docker run -it --net=host \
-e OPENAI_API_KEY="your-key" \
-v ~/.kube/config:/root/.kube/config \
us-central1-docker.pkg.dev/genuine-flight-317411/devel/holmes \
ask "what pods are crashing?"
```
## Essential Commands
```bash
# Basic investigation
holmes ask "what pods are unhealthy and why?"
holmes ask "why is my deployment failing?"
# Interactive mode
holmes ask "investigate issue" --interactive
# Alert investigation
holmes investigate alertmanager --alertmanager-url http://localhost:9093
holmes investigate pagerduty --pagerduty-api-key <KEY> --update
# With file context
holmes ask "summarize the key points" -f ./logs.txt
# CI/CD integration
holmes ask "why did deployment fail?" --destination slack --slack-token <TOKEN>
```
## Supported AI Providers
| Provider | Environment Variable | Models |
|----------|---------------------|--------|
| **Anthropic** | `ANTHROPIC_API_KEY` | Sonnet 4, Opus 4.5 |
| **OpenAI** | `OPENAI_API_KEY` | GPT-4.1, GPT-4o |
| **Azure OpenAI** | `AZURE_API_KEY` | GPT-4.1 |
| **AWS Bedrock** | AWS credentials | Claude 3.5 Sonnet |
| **Google Gemini** | `GEMINI_API_KEY` | Gemini 1.5 Pro |
| **Vertex AI** | `VERTEXAI_PROJECT` | Gemini 1.5 Pro |
| **Ollama** | Local install | Llama 3.1, Mistral |
## Basic Helm Values Structure
```yaml
# values.yaml for Kubernetes deployment
image:
repository: robustadev/holmes
tag: latest
env:
- name: ANTHROPIC_API_KEY
valueFrom:
secretKeyRef:
name: holmesgpt-secrets
key: anthropic-api-key
# Model configuration
modelList:
sonnet:
api_key: "{{ env.ANTHROPIC_API_KEY }}"
model: anthropic/claude-sonnet-4-20250514
temperature: 0
# Toolsets to enable
toolsets:
kubernetes/core:
enabled: true
kubernetes/logs:
enabled: true
prometheus/metrics:
enabled: true
# Resources
resources:
requests:
memory: "1024Mi"
cpu: "100m"
limits:
memory: "1024Mi"
# RBAC (read-only by default)
createServiceAccount: true
```
## Interactive Mode Commands
| Command | Description |
|---------|-------------|
| `/clear` | Reset context when changing topics |
| `/run` | Execute custom commands and share output with AI |
| `/show` | Display complete tool outputs |
| `/context` | Review accumulated investigation information |
## Custom Toolset Example
```yaml
# custom-toolset.yaml
toolsets:
my-custom-tool:
description: "Custom diagnostic tool"
tools:
- name: check_service_health
description: "Check health of a specific service"
command: |
curl -s http://{{ service_name }}.{{ namespace }}.svc.cluster.local/health
parameters:
- name: service_name
description: "Name of the service"
- name: namespace
description: "Kubernetes namespace"
```
Use with: `holmes ask "check health" -t custom-toolset.yaml`
## Kubernetes Annotations for Integration
```yaml
# Add to Services/Deployments for HolmesGPT context
metadata:
annotations:
holmesgpt.dev/runbook: |
This service handles payment processing.
Common issues: database connectivity, API rate limits.
Check: kubectl logs -l app=payment-service
```
## Environment Variables Reference
| Variable | Description | Default |
|----------|-------------|---------|
| `HOLMES_CONFIG_PATH` | Config file path | `~/.holmes/config.yaml` |
| `HOLMES_LOG_LEVEL` | Log verbosity | `INFO` |
| `PROMETHEUS_URL` | Prometheus server URL | - |
| `GITHUB_TOKEN` | GitHub API token | - |
| `DATADOG_API_KEY` | DataDog API key | - |
| `CONFLUENCE_BASE_URL` | Confluence URL | - |
## Best Practices
1. **Use Specific Queries**: Include namespace, deployment name, symptoms
2. **Start with Claude Sonnet 4.0/4.5**: Best accuracy for complex investigations
3. **Enable Relevant Toolsets**: Only enable what you need to reduce noise
4. **Use Interactive Mode**: For complex multi-step investigations
5. **Set Up Runbooks**: Provide context for known alert types
6. **CI/CD Integration**: Automate deployment failure analysis
## Security Considerations
- HolmesGPT uses **read-only access** (`get`, `list`, `watch` only)
- Respects existing RBAC permissions
- Never modifies, creates, or deletes resources
- API keys stored in Kubernetes Secrets
- Data not used for model training
## Official Resources
- Documentation: <https://holmesgpt.dev/>
- GitHub: <https://github.com/robusta-dev/holmesgpt>
- Helm Chart: <https://github.com/robusta-dev/holmesgpt/tree/master/helm/holmes>
- Slack Community: Cloud Native Slack
Scanned 2/12/2026
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