Grafana is the viewing layer, not the telemetry store
Grafana gives an operations team a common screen for data that already lives elsewhere. Its README centers on querying, graphing, exploring, and alerting across metrics and logs. Dashboards can combine data sources in one view, and template variables turn a fixed board into something operators can filter without editing each panel. That is the appeal: one interface can sit over several systems without forcing every signal into one database.
The repository shows the cost of that breadth. Our commit 8c9a2eb checkout contained 23,662 files, roughly 3,222,031 lines of source, and occupied 219.6 MB before installation. This is a full product with a browser client, Go server, bundled plugins, packaging, and developer tooling. If your task is one chart over one SQL query, Grafana may bring far more surface area than the problem needs.
Dashboards and Explore solve different operator jobs
Dashboards are for shared, repeated questions: Is request latency rising? Which region is failing? Did the deployment change error volume? Grafana's panel plugins provide different views, while variables let one board cover several services or environments. Alert rules use the same visual system and can send notifications to external tools named in the README. Teams can keep a known operating picture on screen instead of rebuilding queries during an incident.
Explore is the less formal side. Operators can run ad hoc queries, compare time ranges, split the screen, and move between metrics and logs while retaining label filters. Mixed-source panels also let a graph draw from more than one backend. Grafana 13.2.3 shipped on September 29, 2026, so the current project is well beyond an early dashboard experiment. The practical question is whether your existing stores and labels are consistent enough for a shared interface to help.
What happened when we ran it
Our sandbox installed commit 8c9a2eb in 136 seconds. Yarn added 3,494 packages, and the installed checkout reached 2,725 MB on disk. The unprivileged Debian container had 3 CPUs, 8 GB of RAM, Node 22, and no secrets. Installation succeeded, which proves that the dependency graph resolved in that environment. It does not prove that a production server or any data-source integration worked.
The build failed after 200 seconds with exit code 1. The log tail shows the error passing through Nx's runTargetOnProject and nxExecCommand, then reports status 1 without the earlier message that triggered it. We cannot responsibly name a cause from that tail. The test command ran until the 900-second cap. Jest reported two manual mocks named fixtures, then said no tests matched files changed since the last commit.
Source work needs Go, Node, browsers, and service fixtures
Grafana's developer guide splits the product into a frontend and a Go backend. The checked package metadata requires Node 22 or newer but below 25, uses Yarn 4.18.0, and asks contributors to enable Corepack. Frontend startup generates themes, builds external plugins, and watches assets. The backend compiles and starts separately. A successful package install is therefore only the first gate in a working contributor setup.
Testing branches out as well. Jest covers the frontend, standard Go commands cover backend packages, and integration runs can start SQLite, PostgreSQL, or MySQL fixtures. Playwright needs its matching Chromium build. On Windows, the guide recommends WSL; native SQLite compilation needs GCC with binutils 2.37 or later. The documented production-style Go build disables CGO, while local defaults may use it for SQLite. These are explicit requirements, not guesses from our failed build.
AGPL covers the server, with named Apache exceptions
The default license is AGPL-3.0-only. Grafana's licensing file carves out Apache-2.0 terms for named directories such as packages/grafana-data, packages/grafana-ui, packaging code, schema registries, and selected assets. That distinction matters if you plan to modify the server or distribute a combined product. A permissive license on some packages does not change the default license on the rest of the repository.
Grafana also expects data-source credentials and service configuration once the code is running. The README's promise is access to metrics wherever they are stored, which means the storage systems remain your responsibility. With 2,725 MB used by our installed checkout before any external database or browser fixture, contributor machines and CI workers need deliberate sizing. Production deployment is a separate exercise from compiling this monorepo.
An October 5 push and 3,299 open items show active maintenance
GitHub recorded a push on October 5, 2026, and listed 3,299 combined open issues and pull requests. Search results separated that total into 2,667 issues and 632 pull requests. The volume is large enough that raw counts say little about response quality, but the same-day push and hundreds of open changes show an active codebase rather than a repository coasting on its name.
Release 13.2.3 arrived on September 29 with fixes for 3 named CVEs. That is useful evidence of security maintenance, and also a reminder that operators must keep current. Grafana deserves a shortlist when your metrics and logs already exist in supported systems and several teams need the same operational view. If you want one package to ingest, store, query, and display every signal, its viewing-layer design leaves major pieces for you to choose and run.