grafana-dashboard-optimize

# Grafana Dashboard Content Optimization (Observability / SRE) Audit and optimize dashboard content for observability best practices. Apply RED/USE/Golden Signals methodology, improve diagnostic value, and reduce cognitive load for on-call teams. **Not suitable for**: Code structure refactoring (use `grafana-jsonnet-refactor`), initial JSON conversion (use `grafana-json-to-jsonnet`), or code style formatting. ## Workflow with progress tracking Copy this checklist and track your progress: ``` Optimization Progress: - [ ] Step 1: Understand context (purpose, audience, strategy) - [ ] Step 2: Run seven-dimensional content audit - [ ] Step 3: Produce prioritized recommendations report - [ ] Step 4: Apply changes (if requested) - [ ] Step 5: Validate improvements ``` **Step 1: Understand context** Before any edits, document: - Dashboard purpose and target audience (SRE/on-call/management) - Current monitoring strategy and key questions it should answer - Datasources, variables, time range settings - Row structure and panel organization - Annotations, dashboard metadata (`__inputs`, `__requires`, `schemaVersion`, `graphTooltip`, `version`), and pluginVersion See `references/full-optimization-playbook.md` for detailed context gathering. If optimizing dashboards in a specific repo or stack, review local Jsonnet defaults and docs in the working directory for current conventions. **Step 2: Run seven-dimensional content audit** Audit across these dimensions: 1. **Panel semantics**: Missing/duplicated views, diagnostic coverage 2. **Query optimization**: rate/increase usage, aggregation, cardinality 3. **Variable design**: Names, defaults, cascading relationships 4. **Visualization**: Panel types, units, thresholds, legends, table field pruning 5. **Layout**: Overview → symptoms → root cause flow 6. **Titles/descriptions**: Unified title style, clarity, context, troubleshooting hints, every panel has a description 7. **Proactive additions**: SLO/SLI, annotations, comparisons, runbooks, dashboard metadata parity For the full audit checklist and visualization/layout guidance, see `references/full-optimization-playbook.md`. For observability strategies (RED/USE/Golden Signals), see `references/observability-strategies.md`. For color, thresholds, and table styling aligned with local repo conventions, see `references/visual-style-guides.md`. **Step 3: Produce prioritized recommendations** Create structured assessment report with: - **Critical**: Missing essential metrics, broken queries, misleading visualizations - **Recommended**: Important improvements with clear ROI - **Optional**: Nice-to-have enhancements Include rationale and expected impact for each recommendation. Use template in `references/report-template.md`. **Step 4: Apply changes (if requested)** If user approves changes: - Use available unified libraries when present (commonly `panels`, `standards`, `themes`) - Keep code structure changes minimal (content-only optimization) - Include Jsonnet snippets for high-impact changes - Preserve datasource selection patterns and any `__inputs` / `__requires` blocks if present - Preserve `schemaVersion`, `graphTooltip`, `version`, and `pluginVersion` when present - Add or improve panel descriptions so every panel has a clear, actionable description - Match existing repo/dashboard structure (imports → config → constants → helpers → panels → rows → variables → dashboard) - For **table** panels, use the `panels` lib (no raw Grafonnet) and follow the detailed table guidance in `references/full-optimization-playbook.md`. For query optimization patterns, see `references/query-optimization.md`. **Step 5: Validate improvements** Run the quality checklist below against the improved dashboard. If any check fails, return to Step 4, fix, and verify again. ## Quality checklist - [ ] RED/USE/Golden Signals coverage is complete - [ ] Queries are efficient and bounded - [ ] Units and thresholds use `standards.*` - [ ] Panel titles are consistent and every panel has a clear, actionable description - [ ] Layout follows overview → symptoms → root cause - [ ] Table panels remove unused fields (overrides/thresholds, colors, widths, cell types applied) - [ ] Variables return values and have no duplicates/extras - [ ] Regex filters preserved or added where needed - [ ] Row membership is correct (panels align to row `gridPos.y`) - [ ] `__inputs` / `__requires`, annotations, and dashboard metadata remain valid and intentional ## Guardrails - Do not refactor code structure; use `grafana-jsonnet-refactor` for that. - Avoid broad rewrites; focus on content quality and observability value. - Keep deep guidance in `references/` instead of bloating this file. - Do not run `jsonnetfmt` / `jsonnet fmt` on generated Jsonnet files. ## References (load as needed) - `references/visual-style-guides.md` - `references/full-optimization-playbook.md` for the complete framework - `references/observability-strategies.md` for RED/USE/Golden Signals - `references/query-optimization.md` for PromQL/SQL guidance - `references/report-template.md` for the assessment report format