Grafana: One Investigation Surface, Many Backends
Source: Observability Platform source — section 14, “Grafana: The Investigation Surface”
The enterprise problem and today’s slice
Enterprise problem: Responders lose time and context when dashboards, logs, traces, and profiles live in separate tools with inconsistent permissions, time ranges, and service identities.
Whole-course context: The incoming artifacts are independently proven Mimir, Loki, Tempo, and Pyroscope paths; today makes them usable through one governed investigation surface without pretending Grafana owns their telemetry.
Today’s slice: Provision data sources, folders, dashboards, Explore access, and query evidence while preserving each backend’s tenant, retention, and query-language responsibility.
End-of-day evidence: Produce a shareable fixed-time investigation that opens authorized metrics, logs, traces, and profiles with matching service/environment context.
Still unsolved: Automated cross-signal identity contracts and the final end-to-end platform architecture remain deferred.
The smallest complete model
Four healthy backends do not give responders one reproducible investigation. Without stable data-source identity and a fixed time window, the same Grafana link can show different evidence after handoff.
Thesis: Grafana should turn one bounded symptom into a reproducible query context and an owned action without becoming the authority for telemetry or access. Why this matters: responders can share exactly what they observed while each backend keeps its data and authorization boundary.
The smallest model has a symptom, a fixed investigation context, and an action. It is complete enough to test handoff reproducibility before adding multiple data sources, dashboards, or correlations.
Relative “last hour” links change after handoff, so incident evidence must preserve an absolute time window. Dashboards provide curated views; Explore supports iterative query work, side-by-side sources, query inspection, and fixed-time sharing.
A panel is a data source, query, optional transformation, and visualization. Record the data-source UID and inspect the actual request when results surprise you. Mixed-source panels can be useful, but independent panels often make ownership and partial failure clearer.
Expand the model one boundary at a time
Expand the same symptom–context–action model in dependency order: provision stable data-source identities, encode a curated dashboard, move into Explore for hypothesis testing, freeze absolute time and queries for handoff, then attach permissions and ownership. Every backend remains independently authorized.
| Boundary | Purpose, inputs, and transformation | Output or interface | Scaling constraint and failure mode | Alternative guidance |
|---|---|---|---|---|
| Data source | Map a stable UID to one backend endpoint and secret reference | Backend query interface and health result | Query concurrency, credential expiry, or backend latency | Use separate data sources for distinct tenant/access scopes; avoid inline credentials |
| Dashboard | Turn known service indicators and bounded variables into curated panels | Repeatable symptom overview | Expensive variables, broad queries, or stale revisions | Use dashboards for known questions; avoid treating them as proof of root cause |
| Explore | Transform a panel result into iterative, inspectable queries | Query history, raw request, side-by-side evidence | Unbounded lookback or scanned data | Use Explore for active hypotheses; avoid relative-time-only incident handoff |
| Permission and handoff | Evaluate folder/data-source access and freeze context | Authorized absolute-time link plus investigation record | Role drift, accidental backend exposure, or partial-source denial | Use least-privilege folders and backend credentials; avoid assuming Grafana membership grants backend authority |
Manual UI changes drift and are hard to recover, so provision stable UIDs and reviewable configuration where practical. Store credentials in an external secret mechanism and scope each data source to the required tenant and API.
Test two identities: an authorized responder and a restricted user. The restricted user must be denied the protected folder or data source without inheriting backend access merely through Grafana membership. Also test direct backend exposure; Grafana role-based access control (RBAC) cannot protect an independently reachable backend endpoint.
Run the model through one incident
The general rule is to begin with one bounded symptom, keep service, environment, tenant, and absolute time through every query, and end with a recorded decision. A simple example opens a checkout latency panel, inspects its exact Mimir query, and shares the fixed window with a second responder. A realistic recurring checkout incident expands through the telemetry pipeline to logs, a payment trace, and a same-window profile while recording partial-source failures instead of hiding them.
A dashboard that shows four green panels does not prove cross-signal usefulness. Seed one checkout degradation and capture:
- Mimir p99 latency and error-rate panels for a fixed time.
- Loki timeout logs for the same service/environment window.
- A Tempo trace whose payment span dominates.
- A Pyroscope profile that names a hot function or falsifies local CPU.
- A shared absolute-time Explore/dashboard link opened by a second authorized user.
- A denied attempt from the restricted identity.
Observed evidence includes the data-source UIDs, exact queries, absolute time, result digests, shared link, second-user reproduction, and restricted-user denial. This separates “no matching telemetry” from a broken data source, an over-broad query, or an authorization failure.
Failure modes, trade-offs, and decision rules
The characteristic failure mode is a plausible dashboard that cannot be reproduced because it depends on relative time, mutable UI state, or hidden credentials. The main trade-off is a mixed-source overview’s convenience versus the clearer ownership and partial-failure behavior of independent panels and Explore queries.
use a dashboard for stable recurring questions and Explore for active hypothesis testing; preserve the exact data-source UID, query, tenant, and absolute window whenever evidence influences an action. Use mixed panels only when the combined view materially shortens the workflow and each source’s errors remain visible. Avoid shared admin credentials, embedded secrets, broad variables, and links that imply authorization across backends.
When a panel is empty, first test data-source health, direct bounded query, permission, and time scope. Scale Grafana or a backend only when the matching concurrency, latency, or scanned-data evidence identifies capacity as the constraint.
Close the loop
The investigation loop is Observe → Interpret → Decide → Act → Measure. Observe the bounded symptom and source health; interpret evidence across exact queries; decide on one owned remediation; act within that service boundary; then measure the original panel and underlying query in the same fixed scope.
For the next bounded action, seed one checkout degradation, create an absolute-time investigation link, and hand it to one authorized and one restricted test identity. The falsifiable probe succeeds only if the authorized user reproduces all four signal results and query context, the restricted user is denied, no browser or data-source error is hidden, and the post-action checkout metric improves in the recorded window.
Key takeaways
Grafana unifies investigation interaction, not storage ownership. Preserve these rules:
- Mimir, Loki, Tempo, and Pyroscope remain specialized authoritative telemetry backends.
- Stable data-source and dashboard UIDs make provisioning and links recoverable.
- Absolute time, query text, variables, and data-source identity make evidence reproducible.
- Grafana permissions and backend permissions are distinct boundaries.
- Partial data-source failure should remain visible while unaffected signals continue working.
Checklist
A polished dashboard can conceal unsafe credentials or irreproducible evidence. Complete these checks:
- [ ] Provisioned stable data-source, folder, and dashboard UIDs.
- [ ] Kept credentials outside dashboard and provisioning source.
- [ ] Used least-privilege identities for each backend.
- [ ] Reproduced a four-signal investigation with absolute time.
- [ ] Injected one data-source failure and proved unaffected controls.
- [ ] Proved restricted-user denial at Grafana and backend boundaries.
Sources
Grafana roles and correlation features evolve, so use current primary documentation. These sources support the surface and provisioning model: