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Infrastructure · llms.txt file breakdown
Grafana llms.txt
Grafana documentation organizes Grafana documentation around Our core stack, Observability, AI, testing, and Incident Response Management (IRM), Connect and visualize data, Grafana Cloud and 5 more sections.
The actual file
Source Markdown
The saved llms.txt text, displayed as source. The file belongs to its publisher; the live endpoint may change.
Complete saved Markdown shown below.
# Grafana documentation
> Grafana Labs builds open and composable observability software, including Grafana, Grafana Cloud, Loki, Mimir, Tempo, Pyroscope, Alloy, Beyla, Faro, and k6.
This file is a curated documentation index for AI agents and other automated consumers.
Use this file for discovery. The links below point directly to machine-readable Markdown pages on `https://grafana.com`.
For a larger exhaustive index, use [llms-full.txt](/llms-full.txt).
All Grafana documentation pages support a machine-readable Markdown form:
- Append `.md` to the canonical docs URL.
- Or request the canonical docs URL with `Accept: text/markdown`.
## Our core stack
Unlock the full potential of your data with our platform, where you can query and visualize metrics, logs, and traces to gain a deeper understanding of your system's performance and behavior.
### Grafana
Query, visualize, and understand your data.
- [Grafana Cloud](https://grafana.com/docs/grafana-cloud/learn-and-build/visualizations.md)
- [Grafana OSS](https://grafana.com/docs/grafana/latest.md)
- [Grafana Enterprise](https://grafana.com/docs/grafana/latest/introduction/grafana-enterprise.md)
### Metrics
Store and query raw, unsampled metrics for all your applications and infrastructure.
- [Grafana Cloud](https://grafana.com/docs/grafana-cloud/send-data/metrics.md#ways-to-connect-your-data-to-grafana-cloud)
- [Grafana OSS](https://grafana.com/docs/mimir/latest.md)
- [Grafana Enterprise](https://grafana.com/docs/enterprise-metrics/latest.md)
### Logs
Store and query logs from all your applications and infrastructure.
- [Grafana Cloud](https://grafana.com/docs/grafana-cloud/send-data/logs.md)
- [Grafana OSS](https://grafana.com/docs/loki/latest.md)
- [Grafana Enterprise](https://grafana.com/docs/enterprise-logs/latest.md)
### Traces
Visualize the lifecycle of a request as it passes through a set of applications.
- [Grafana Cloud](https://grafana.com/docs/grafana-cloud/send-data/traces.md)
- [Grafana OSS](https://grafana.com/docs/tempo/latest.md)
- [Grafana Enterprise](https://grafana.com/docs/enterprise-traces/latest.md)
## Observability, AI, testing, and Incident Response Management (IRM)
Comprehensive documentation that covers the entire lifecycle, from testing and instrumentation to AI-powered observability and incident response management, aimed to help you minimize mean time to resolution.
### Observability
Docs that support your infrastructure and application observability needs.
- [OpenTelemetry](https://grafana.com/docs/opentelemetry.md)
- [Kubernetes (k8s) Monitoring](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/kubernetes-monitoring.md)
- [Cloud Provider Observability](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/monitor-cloud-provider.md)
- [Frontend Observability](https://grafana.com/docs/grafana-cloud/monitor-applications/frontend-observability.md)
- [Application Observability](https://grafana.com/docs/grafana-cloud/monitor-applications/application-observability.md)
- [Database Observability](https://grafana.com/docs/grafana-cloud/monitor-applications/database-observability.md)
- [Knowledge graph](https://grafana.com/docs/grafana-cloud/knowledge-graph.md)
- [AI Observability](https://grafana.com/docs/grafana-cloud/monitor-applications/ai-observability.md)
- [Profiles](https://grafana.com/docs/grafana-cloud/monitor-applications/profiles.md)
### AI and Machine Learning
Built-in AI and machine learning features that help you get more out of your observability data.
- [Grafana Assistant](https://grafana.com/docs/grafana-cloud/platform/grafana-assistant.md)
- [Machine learning](https://grafana.com/docs/grafana-cloud/machine-learning/dynamic-alerting.md)
- [LLM plugin](https://grafana.com/docs/grafana-cloud/machine-learning/llm.md)
- [Sift](https://grafana.com/docs/grafana-cloud/machine-learning/sift.md)
### Alerting and Incident Response (IRM)
Enable your teams to detect, respond to, and learn from incidents.
- [Alerting](https://grafana.com/docs/grafana-cloud/alerting-and-irm/alerting.md)
- [IRM](https://grafana.com/docs/grafana-cloud/alerting-and-irm/irm.md)
- [Service Center](https://grafana.com/docs/grafana-cloud/alerting-and-irm/service-center.md)
- [SLO](https://grafana.com/docs/grafana-cloud/alerting-and-irm/slo.md)
### Performance and Testing
Our load testing tools make performance testing easy and productive for engineering teams.
- [Agentic testing](https://grafana.com/docs/grafana-cloud/testing/agentic-testing.md)
- [Performance testing](https://grafana.com/docs/grafana-cloud/testing/k6.md)
- [Synthetic Monitoring](https://grafana.com/docs/grafana-cloud/testing/synthetic-monitoring.md)
## Learning Hub
New to Grafana Cloud and unsure where to begin? Start with recommended learning journeys, then follow focused learning paths or dive into self-paced courses. [Go to the Learning Hub](/docs/learning-hub/).
### Learning paths
Short, focused paths you can follow independently or as part of a recommended journey.
- [Get started with Grafana Cloud](https://grafana.com/docs/learning-hub/is-grafana-cloud-right-for-me.md)
- [Monitor a Linux server in Grafana Cloud](https://grafana.com/docs/learning-paths/linux-server-integration.md)
- [Connect to a Prometheus data source in Grafana Cloud](https://grafana.com/docs/learning-paths/prometheus.md)
- [Explore data using Metrics Drilldown](https://grafana.com/docs/learning-paths/drilldown-metrics.md)
- [Visualize metrics in a Grafana Cloud dashboard](https://grafana.com/docs/learning-paths/visualization-metrics.md)
- [Browse all learning paths](https://grafana.com/docs/learning-hub.md#learning-paths)
### Learning journeys
Deepen your technical knowledge with self-paced sections.
- [Intro to Grafana Cloud](https://grafana.com/docs/learning-hub/intro-to-grafana-cloud.md)
- [Intro to integrations](https://grafana.com/docs/learning-hub/intro-to-integrations.md)
- [Intro to send data](https://grafana.com/docs/learning-hub/intro-to-send-data.md)
- [Intro to data sources](https://grafana.com/docs/learning-hub/intro-to-data-sources.md)
- [Intro to Cloud Provider Observability](https://grafana.com/docs/learning-hub/intro-to-cp-olly.md)
- [Browse all journeys](https://grafana.com/docs/learning-hub.md#journeys)
### Docs decision support
Unsure which docs you need? Answer a few questions, and Grot will guide you to the appropriate docs.
- [Which Grafana is right for me?](https://grafana.com/docs/grafana-cloud.md?guide=whichgrafana#guidance-and-help)
- [Traces and Profiles](https://grafana.com/docs/grafana-cloud/monitor-applications/profiles.md?guide=profiling#guidance-and-help)
- [Monitor infrastructure](https://grafana.com/docs/grafana-cloud/monitor-infrastructure.md?guide=monitor-infrastructure#guidance-and-help)
- [Kubernetes Monitoring](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/kubernetes-monitoring.md?guide=kubernetes#guidance-and-help)
## Connect and visualize data
Discover the various methods for sending or connecting data to Grafana Cloud. Once your data is in place, you can visualize it to gain valuable insights that help you tackle real-world challenges.
### Instrument and send data
Set up your infrastructure and applications to transmit telemetry data to Grafana Cloud.
- [Grafana Alloy](https://grafana.com/docs/grafana-cloud/send-data/alloy.md)
- [Grafana integrations](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/integrations.md)
- [Fleet Management](https://grafana.com/docs/grafana-cloud/send-data/fleet-management.md)
- [AWS PrivateLink](https://grafana.com/docs/grafana-cloud/send-data/private-connectivity/aws-privatelink.md)
- [Azure Private Link](https://grafana.com/docs/grafana-cloud/send-data/private-connectivity/azure-privatelink.md)
- [Google Private Service Connect](https://grafana.com/docs/grafana-cloud/send-data/private-connectivity/gcp-psc.md)
- [OTLP end point](https://grafana.com/docs/grafana-cloud/send-data/otlp.md)
- [Grafana Beyla](https://grafana.com/docs/beyla/latest.md)
### Visualize data
Use visualizations to gain actionable insight into your telemetry data.
- [Create a dashboard](https://grafana.com/docs/grafana-cloud/visualizations/dashboards/build-dashboards/create-dashboard.md)
- [Use a dashboard](https://grafana.com/docs/grafana-cloud/visualizations/dashboards/use-dashboards.md)
- [Query and transform data](https://grafana.com/docs/grafana-cloud/visualizations/panels-visualizations/query-transform-data.md)
- [Visualizations](https://grafana.com/docs/grafana-cloud/visualizations/panels-visualizations/visualizations.md)
## Open source projects from Grafana Labs
At Grafana Labs, open source continues to be our driving force as we work to develop and evolve our core OSS tools and technologies.
- [Grafana](https://grafana.com/docs/grafana/latest.md)
- [Mimir](https://grafana.com/docs/mimir/latest.md)
- [Tempo](https://grafana.com/docs/tempo/latest.md)
- [Loki](https://grafana.com/docs/loki/latest.md)
- [Pyroscope](https://grafana.com/docs/pyroscope/latest.md)
- [Alloy](https://grafana.com/docs/alloy/latest.md)
- [Beyla](https://grafana.com/docs/beyla/latest.md)
- [Faro](https://grafana.com/docs/grafana-cloud/monitor-applications/frontend-observability.md)
- [Alerting](https://grafana.com/docs/grafana/latest/alerting.md)
- [k6](https://grafana.com/docs/k6/latest.md)
- [Prometheus](https://grafana.com/docs/grafana/latest/datasources/prometheus.md)
- [Writers’ Toolkit](https://grafana.com/docs/writers-toolkit.md)
- [OpenTelemetry](https://grafana.com/docs/opentelemetry.md)
## Grafana Cloud account management
At Grafana Labs, open source continues to be our driving force as we work to develop and evolve our core OSS tools and technologies.
- [Get started with Grafana Cloud](https://grafana.com/docs/grafana-cloud/get-started.md)
- [Account management](https://grafana.com/docs/grafana-cloud/account-management.md)
## Resources
Consult the following resources, as necessary.
- [Writers' Toolkit](https://grafana.com/docs/writers-toolkit.md)
- [Release life cycle for Grafana Labs](https://grafana.com/docs/release-life-cycle.md)
Measured from the saved file
Linked document
- UTF-8 text size
- 9.9 KB10163 bytes
- Token count
- 2465o200k_base encoding
- Markdown links
- 7971 distinct URLs
- Fenced code blocks
- 0190 lines in the file
Size measures the captured UTF-8 text, not compressed transfer size. Tokens are counted with a named tokenizer; other models can count differently. Neither measure establishes context compatibility or answer quality.
- Project H1
- Grafana documentation
Opening blockquote
Grafana Labs builds open and composable observability software, including Grafana, Grafana Cloud, Loki, Mimir, Tempo, Pyroscope, Alloy, Beyla, Faro, and k6.
Context architecture
How the content is divided
7 H2 sections organize 79 parsed Markdown links. 77 links point to .md or .markdown paths; 0 link occurrences use another hostname. Linked destinations have not been recursively validated.
| H2 section | Links | UTF-8 bytes | Tokens |
|---|---|---|---|
| Our core stackLine 15 | 12 | 1459 | 355 |
| Observability, AI, testing, and Incident Response Management (IRM)Line 52 | 20 | 2512 | 598 |
| Learning HubLine 97 | 17 | 2236 | 553 |
| Connect and visualize dataLine 133 | 12 | 1640 | 391 |
| Open source projects from Grafana LabsLine 160 | 13 | 929 | 262 |
| Grafana Cloud account managementLine 178 | 2 | 311 | 71 |
| ResourcesLine 185 | 2 | 203 | 50 |
Link counts exclude parsed fenced and inline code and resolve relative destinations against the final endpoint. Section sizes cover the text below each H2 until the next H2.
Embedded material
Code, installation and API examples
- Fenced blocks
- 0 closed
- Declared languages
- No fenced blocks detected
- Package-install commands
- 0 detected in fenced or inline code
- Authentication examples
- 0 fenced lines match API-key, Authorization, Bearer, OAuth or access-token patterns
- HTTP request examples
- 0 fenced lines match request-method patterns
- Authentication links
- 0 links have authentication-related labels
Embedded example text and links to further documentation are counted separately. A code block does not establish that a sample runs or that an authentication flow succeeds.
Publisher prioritization
The Optional section
No H2 section named “Optional” was detected in this file.
The community proposal uses Optional by convention for secondary links that can be skipped for a shorter context. This label does not establish that everything outside it is critical, or that the material inside it is deprecated.
Machine-readable routes
MCP references and configuration text
No MCP or Model Context Protocol term was detected in the captured file. 0 links have MCP-related labels or paths. 0 fenced lines match mcpServers, mcp_servers or an mcp add command.
These are text and link observations. No MCP server connection, authentication or tool call was tested.
Index and bundle
llms-full.txt companion
Not found at checked URLs
A verified text response establishes a companion at the checked URL. It does not prove the bundle contains all product documentation, that generation is automated, or that it fits an assistant’s context window.
Change evidence
What can be said about freshness
This capture establishes a baseline. Update frequency cannot be determined from one observation.
Linked release and migration material
1 links have release, changelog, deprecation or migration terms in their labels or paths. These provide places to investigate product changes separately.
File changes can reveal documentation edits or navigation changes. They do not by themselves measure product release velocity, accuracy, agent adoption or AI visibility.
Capture identity and measurement method
- Requested endpoint
- https://grafana.com/docs/llms.txt
- Final endpoint
- https://grafana.com/llms.txt
- HTTP status
- 200
- Content type
- text/plain
- Text retrieval
- Firecrawl literal text capture
- Tokenizer
- tiktoken 0.14.0 · o200k_base
- SHA-256 of saved UTF-8 text
8fe56741f0884703621270b963e3cb6e7baff750ffef43382940bfec31713e0f
Counts use a deterministic parser, not a spec-compliance grade. Unusual Markdown and indented code can fall outside its recognized patterns. See the llms.txt proposal and tokenizer implementation.