Grafana
Grafana is an open-source observability and visualization platform for querying, exploring, and displaying data from multiple sources and configuring alerts.
Learn Docker in a Month of Lunches, Second Edition
Grafana is an open-source observability and visualization platform for querying data sources and presenting interactive dashboards.
- How it is used
- Visualizes Prometheus metrics from containerized applications in dashboards for ongoing monitoring.
- How deep it goes
- Walks through running a dashboard and adding a query-driven panel; leaves metric selection and capture dependent on the application.
- Examples
- Uses an image-gallery dashboard, an HTTP 500 error panel, and a to-do list monitoring lab.
- What you can do after
- Operate/configure Grafana to display Prometheus metrics, add a query-driven panel, and package a provisioned dashboard.
Read how Learn Docker in a Month of Lunches, Second Edition explains Grafana →
Cloud Observability in Action
A Grafana dashboard is a Grafana interface that presents selected observability data and visualizations.
- How it is used
- Provides a uniform interface for visualizing, exploring, and alerting on observability data from multiple backends.
- How deep it goes
- Explains data sources, dashboards, variables, alerting, and setup, while deferring backend storage and ingestion to other systems.
- Examples
- Uses an instrumented Go echo service, Prometheus dashboards, Jaeger traces, Docker Compose, and parameterized PromQL queries.
- What you can do after
- Operate/configure Grafana with data sources, dashboards, variables, PromQL panels, and unified alerts across observability backends.
ScyllaDB in Action
Grafana is an open-source visualization and dashboard platform for querying and displaying data from monitoring and other data sources.
- How it is used
- Provides dashboards for observing ScyllaDB traffic, latency, availability, and operational performance.
- How deep it goes
- Explains data-source integration, dashboard categories, deployment scripts, and metric interpretation, but defers custom dashboard construction.
- Examples
- Uses Scylla CQL, Overview, Detailed, Keyspace, OS Metrics, Advanced, and Alternator dashboards with query-generated metric spikes.
- What you can do after
- Operate/configure Grafana with Prometheus as a data source and inspect database performance through dashboards.
Quarkus in Action
Grafana is an open-source observability and visualization platform for querying, displaying, and alerting on data such as time-series metrics.
- How it is used
- Visualizes Quarkus application metrics stored in Prometheus so operators can inspect behavior through dashboards instead of raw endpoint output.
- How deep it goes
- Works through extension setup, endpoint inspection, and a supplied Docker Compose deployment, but leaves Prometheus–Grafana configuration details unexplored.
- Examples
- Uses an Inventory service dashboard, JVM uptime and memory metrics, and a counted car-registration method.
- What you can do after
- Apply it via Grafana to view metrics from a Quarkus service using the supplied local Prometheus and Docker Compose setup.
Machine Learning Platform Engineering
Grafana is an open-source observability and dashboard platform for querying, visualizing, and exploring operational data.
- How it is used
- Visualizes application metrics queried from Prometheus in operational dashboards.
- How deep it goes
- Explains integration, PromQL querying, Helm installation, and data-source configuration, but not Grafana internals.
- Examples
- Uses FastAPI metrics, a PromQL request-rate query, Helm commands, and a Grafana time-series chart.
- What you can do after
- Operate/configure Grafana with Prometheus to query application metrics and build operational charts.
Read how Machine Learning Platform Engineering explains Grafana →
Data Pipelines with Apache Airflow, Second Edition
Grafana is an open-source observability platform for querying, visualizing, and monitoring data from multiple sources.
- How it is used
- Visualizes Airflow metrics in dashboards for operational monitoring.
- How deep it goes
- Demonstrates setup, data-source configuration, dashboard creation, querying, and monitoring delays, but not dashboard alerting configuration.
- Examples
- Uses a Docker launch command, a Prometheus data source, and the Airflow DAG parse-time metric.
- What you can do after
- Operate/configure Grafana to connect Prometheus and build a dashboard for Airflow metrics.
Read how Data Pipelines with Apache Airflow, Second Edition explains Grafana →
Digital Twins in Action
Grafana is an open-source observability and data visualization platform for querying, displaying, and monitoring data from multiple sources.
- How it is used
- Uses Grafana to present digital-twin sensor and event data as interactive operational dashboards.
- How deep it goes
- Shows container setup and a GraphQL-to-jq data-shaping path, while leaving specialized visualizations to custom development.
- Examples
- Uses a Docker launch command, a space-measurement query, nested-JSON transformation, and a voltage-over-time dashboard panel.
- What you can do after
- Operate/configure Grafana with an Infinity data source to turn API measurements into a time-series dashboard.
Spring AI in Action
Grafana is an open-source platform for querying, visualizing, and alerting on data from monitoring and observability systems.
- How it is used
- Builds dashboards that expose Spring AI application health, performance, and generative AI activity.
- How deep it goes
- Explains server startup, login, Prometheus connection, metric preparation, and dashboard construction.
- Examples
- Uses Spring AI metric panels, time-series graphs, and a dashboard displaying client operations.
- What you can do after
- Operate/configure Grafana to connect Prometheus and visualize metrics from a running Spring AI application.
Effective Platform Engineering
Grafana is an open-source observability and visualization platform for querying, displaying, and alerting on data from multiple sources.
- How it is used
- Unifies querying, visualization, and alerting across metrics, logs, and traces for operational monitoring and decision-making.
- How deep it goes
- Maps data sources, configuration storage, user access, and alerting, while leaving specific component choices dependent on scale.
- Examples
- Uses Prometheus, Loki, Tempo, Postgres, CI/CD pipelines, and payment-processing reliability monitoring as concrete examples.
- What you can do after
- Operate/configure Grafana to query telemetry, create dashboards, define alerts, and support proactive issue detection.
Related concepts
- observability systemkind of · An observability system is software that collects and analyzes telemetry to help users understand system behavior, performance, health, and problems.
- natural language interfacekind of · A natural language interface enables interaction with a system through human-language text or speech.
- Prometheususes · Prometheus is an open-source monitoring and alerting system that collects, stores, and queries time-series metrics.
- performanceuses · Performance is the measurable effectiveness or operational behavior of a system under specified conditions, assessed through relevant qualities such as task results, speed, responsiveness, throughput, or resource use.
- sequenceuses · A sequence is an ordered collection of elements whose positions determine their order of traversal or processing.
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