Introduction to Grafana Machine Learning
Grafana Machine Learning offers an expanding range of data analysis and generative AI capabilities, including creating alerts, forecasting capacity requirements, and identifying anomalous activities. Explore how Grafana ML can help you learn patterns in your data, investigate your infrastructure telemetry, and gain predictive insights.
Forecast with confidence Grafana ML learns patterns in your data so you can go beyond traditional monitoring. Whether your data resides in Prometheus, Postgres, Grafana Loki, or any other supported source, you can forecast with confidence and anticipate future states of your systems.
Embrace open-source collaboration The open-source LLM app facilitates large language model-based extensions to Grafana, allowing developers to tap into public datasets, connect their LLM and vector databases, and collaboratively build LLM-powered experiences within the Grafana community.
AI/ML-powered experiences Grafana Labs is at the forefront of integrating AI/ML into feature development, aimed at reducing toil and solving real-world problems for admins and developers. New AI-driven developments include:
- Sift: A diagnostic assistant in Grafana Cloud designed to automatically discover contributing causes to incidents across metrics, logs, and tracing data.
- Grafana Incident auto-summary: A tool summarizing key details from your incident timelines with a single click.
- Generative AI features that simplify creating dashboard metadata and streamline writing PromQL queries.
Key features and benefits
Predictive analytics At the core of Grafana Machine Learning is learning patterns from historical data, allowing users to accurately predict their systems’ future states. This allows your team to foresee potential issues, optimize resources, and enhance system performance.
Confidence in predictions Beyond predictions, Grafana Machine Learning provides confidence bounds, giving users a clear understanding of the reliability of the forecasted values. This ensures that you can make informed decisions and set appropriate thresholds for alerts.
Versatile applications The predictive insights generated by Grafana Machine Learning can be applied in various scenarios. Utilize these forecasts to create alerts, anticipate capacity requirements, or identify outliers and anomalies, enhancing your system monitoring and incident response capabilities.
Broad data source support Grafana Machine Learning integrates with a variety of data sources, including Prometheus, Graphite, Loki (metric queries only), Postgres, InfluxDB, Snowflake, Splunk, Elasticsearch, BigQuery, MongoDB, and Datadog.
Was this page helpful?
Related resources from Grafana Labs
![Getting started with the Grafana LGTM Stack](/static/assets/featured/getting-started-with-grafana-lgtm-stack-amer_featured.png?w=200 200w, /static/assets/featured/getting-started-with-grafana-lgtm-stack-amer_featured.png?w=400 400w)
![Intro to Kubernetes monitoring in Grafana Cloud](/media/webinar/Screenshot-2024-02-12-at-4.09.30-PM.png?w=200 200w, /media/webinar/Screenshot-2024-02-12-at-4.09.30-PM.png?w=400 400w)
![Building advanced Grafana dashboards](/media/webinar/AMER_buildadv_notxt.png?w=200 200w, /media/webinar/AMER_buildadv_notxt.png?w=400 400w)