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performance-budget

Define and document performance budgets for a web service or application. Use when asked to set performance targets, define SLOs for latency or thro…

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技能内容

Performance Budget Skill

Produce a complete, actionable performance budget document for a web service or application. A performance budget is not a wishlist — it is a set of measurable, enforced constraints that define what "acceptable performance" means and who is responsible when those constraints are violated.

A good performance budget answers: what are the targets, how are they measured, what triggers an investigation, and what happens when a budget is breached.

Required Inputs

Ask for these if not already provided:

  • Service name and type — web app, API service, mobile app, or combination
  • Key user journeys — the 3–5 most important flows users take (e.g. "search → product page → checkout")
  • Current baseline metrics — P50/P95/P99 latency, LCP, CLS, INP if available (state "no baseline" if not collected yet)
  • Tech stack — frontend framework, backend language/framework, CDN, database
  • Deployment environment — cloud provider, region(s), edge/CDN configuration
  • Cost constraints — any budget or infrastructure limits that affect headroom

Output Format


Performance Budget: [Service Name]

Service: [Name] | Team: [Team name]

Last updated: [Date] | Owner: [Name / role]

Environment: [Production / Staging baseline] | Review cadence: [Quarterly / per-sprint]


Overview

[2–3 sentences describing the service, its user-facing performance requirements, and why performance is a priority. Reference the business impact of latency — e.g. conversion rate, user retention, SLA obligations.]

Performance philosophy: [e.g. "Performance is a feature. Every engineer is responsible for keeping the service within budget. Regressions must be caught in CI before they reach production."]


Key User Journeys

Define the critical paths that the performance budget is designed to protect.

| Journey ID | Journey name | Entry point | Exit point | Criticality |

|---|---|---|---|---|

| UJ-1 | [e.g. New user sign-up] | [Landing page] | [Dashboard] | Critical |

| UJ-2 | [e.g. Core workflow task] | [e.g. /app/tasks] | [e.g. Task complete] | High |

| UJ-3 | [e.g. Search and select] | [e.g. /search] | [e.g. Detail page] | High |

| UJ-4 | [e.g. API data fetch] | [e.g. GET /api/items] | [e.g. 200 response] | Medium |


Frontend Performance Budget

Complete this section for web and mobile applications. Skip for API-only services.

Core Web Vitals Targets

Targets apply to the 75th percentile of real user sessions (field data), measured on a mid-range Android device on a 4G connection unless otherwise stated.

| Metric | Description | Good | Needs Improvement | Poor | Our Target | Current baseline |

|---|---|---|---|---|---|---|

| LCP | Largest Contentful Paint — perceived load speed | ≤2.5s | 2.5–4.0s | >4.0s | [≤X.Xs] | [Xs / not measured] |

| INP | Interaction to Next Paint — responsiveness | ≤200ms | 200–500ms | >500ms | [≤Xms] | [Xms / not measured] |

| CLS | Cumulative Layout Shift — visual stability | ≤0.1 | 0.1–0.25 | >0.25 | [≤0.X] | [X.XX / not measured] |

| FCP | First Contentful Paint | ≤1.8s | 1.8–3.0s | >3.0s | [≤X.Xs] | [Xs / not measured] |

| TTFB | Time to First Byte | ≤800ms | 800ms–1.8s | >1.8s | [≤Xms] | [Xms / not measured] |

Page Weight Budget

| Asset type | Max size (compressed) | Current | Status |

|---|---|---|---|

| Total page weight | [e.g. 500KB] | [XKB / unknown] | [Within / Over / Unknown] |

| JavaScript (initial load) | [e.g. 200KB] | [XKB / unknown] | [Within / Over / Unknown] |

| CSS | [e.g. 50KB] | [XKB / unknown] | [Within / Over / Unknown] |

| Images (above fold) | [e.g. 150KB] | [XKB / unknown] | [Within / Over / Unknown] |

| Web fonts | [e.g. 50KB] | [XKB / unknown] | [Within / Over / Unknown] |

| Third-party scripts | [e.g. 100KB] | [XKB / unknown] | [Within / Over / Unknown] |

Per-Journey Frontend Targets

| Journey | LCP | INP | CLS | FCP | TTFB |

|---|---|---|---|---|---|

| UJ-1: [Journey name] | [≤Xs] | [≤Xms] | [≤0.X] | [≤Xs] | [≤Xms] |

| UJ-2: [Journey name] | [≤Xs] | [≤Xms] | [≤0.X] | [≤Xs] | [≤Xms] |

| UJ-3: [Journey name] | [≤Xs] | [≤Xms] | [≤0.X] | [≤Xs] | [≤Xms] |


Backend Performance Budget

API Latency SLOs

Targets measured at the service boundary (not including client-side network latency).

| Endpoint / operation | Method | P50 | P95 | P99 | Max (hard limit) | Error rate |

|---|---|---|---|---|---|---|

| [e.g. /api/auth/login] | POST | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |

| [e.g. /api/items] | GET | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |

| [e.g. /api/items/:id] | GET | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |

| [e.g. /api/items] | POST | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |

| [e.g. Background job: sync] | — | [≤Xs] | [≤Xs] | [≤Xs] | [≤Xs] | [<X%] |

Overall service SLOs:

| SLO | Target | Measurement window |

|---|---|---|

| Availability | [99.X%] | 30-day rolling |

| P95 latency (all endpoints) | [≤Xms] | 30-day rolling |

| Error rate (5xx) | [<X%] | 30-day rolling |

| Throughput (sustained) | [≥X req/s] | Peak hour |

Database Query Budget

| Query / operation | P50 | P95 | Max | Notes |

|---|---|---|---|---|

| [e.g. User lookup by ID] | [≤Xms] | [≤Xms] | [≤Xms] | Index on user_id |

| [e.g. List items for user] | [≤Xms] | [≤Xms] | [≤Xms] | Paginated, max 100 rows |

| [e.g. Full-text search] | [≤Xms] | [≤Xms] | [≤Xms] | Elasticsearch / pg_trgm |


Measurement Methodology

Real User Monitoring (RUM)

Tool: [e.g. Google CrUX, SpeedCurve, Datadog RUM, Sentry Performance, custom]

Data source: [Field data from real users / Lab data from synthetic tests / Both]

Sample rate: [X% of sessions]

How to access: [Dashboard URL or tool access instructions]

What is measured:

  • [ ] Core Web Vitals (LCP, INP, CLS) per page and journey
  • [ ] Custom performance marks for business-critical interactions
  • [ ] Resource timing for key assets
  • [ ] Long tasks (>50ms on main thread)

Synthetic Monitoring

Tool: [e.g. Lighthouse CI, WebPageTest, k6, Artillery, Playwright with performance assertions]

Frequency: [Every X minutes / on every deploy / nightly]

Test location(s): [e.g. eu-west-1, us-east-1]

Device profile: [Desktop 10Mbps / Mobile 4G Moto G4 / both]

Synthetic test suite location: [Link to test files]

Backend Observability

APM tool: [e.g. Datadog, Grafana + Prometheus, New Relic, AWS X-Ray]

Metrics collected:

  • Request rate, error rate, duration (RED metrics) per endpoint
  • Database query duration and connection pool utilisation
  • Cache hit/miss rates
  • Background job queue depth and processing latency

Dashboard: [Link to primary performance dashboard]


CI/CD Performance Enforcement

Performance budgets are enforced at two gates:

Gate 1 — Build-time Bundle Analysis

Tool: [e.g. bundlesize, size-limit, webpack-bundle-analyzer with CI assertion]

Config file: [[.bundlesizerc / .size-limit.js / etc.]]

Trigger: Every PR targeting main

Blocking: Yes — PR cannot merge if bundle size budget is exceeded

// Example .size-limit.js
[
  {
    "path": "dist/js/*.js",
    "limit": "200 KB"
  },
  {
    "path": "dist/css/*.css",
    "limit": "50 KB"
  }
]

Gate 2 — Synthetic Performance Tests in CI

Tool: [e.g. Lighthouse CI, k6, Artillery]

Trigger: On deploy to staging

Blocking: Yes — production deploy is blocked if thresholds fail

Thresholds checked:

  • LCP ≤ [Xs]
  • CLS ≤ [0.X]
  • P95 API latency ≤ [Xms]
  • Error rate < [X%]

CI config location: [[.github/workflows/perf.yml / ci/performance.yaml]]

How to run locally:

# Run Lighthouse CI against local build
[command — e.g. lhci autorun --config=lighthouserc.js]

# Run load test locally
[command — e.g. k6 run load-tests/api-smoke.js]

Budget Breach Response Process

A budget breach is when a measured metric exceeds its target for [X consecutive measurements / X minutes sustained / a single deploy].

Breach Severity Levels

| Severity | Condition | Response time | Who acts |

|---|---|---|---|

| P1 — Critical | >2× budget threshold in production | Immediate | On-call engineer + team lead |

| P2 — High | >1.5× budget threshold in production | Within 4 hours | On-call engineer |

| P3 — Medium | Threshold exceeded in production | Within 1 sprint | PR author + team |

| P4 — Low | Threshold exceeded in staging only | Before merge | PR author |

Breach Investigation Checklist

When a breach is detected, work through this checklist in order:

1. Identify the regression commit

# Compare performance across recent deploys
[command — e.g. datadog metrics query, lighthouse-ci compare, git bisect]

2. Classify the breach

  • [ ] Is this a code change? (new feature, refactor, dependency bump)
  • [ ] Is this an infrastructure change? (new instance type, config change)
  • [ ] Is this an external factor? (CDN issue, DNS, upstream dependency)
  • [ ] Is this a measurement anomaly? (test environment issue, sample size)

3. Immediate actions

  • If P1/P2 in production and a code cause is confirmed: roll back or disable the feature flag
  • If cause is unknown: do not roll back immediately — gather more data first
  • Notify [#performance / #incidents Slack channel] with: metric name, current value, budget target, suspected cause

4. Resolution

  • Fix the root cause — do not just adjust the budget threshold
  • Budget thresholds should only change after a team discussion and explicit approval from [tech lead / EM]
  • Document the breach in the [performance log / incident record]

Budget change policy: Budget thresholds may only be relaxed if: (a) the feature delivering the regression has measurable business value that outweighs the performance cost, and (b) the change is reviewed and approved by [tech lead].


Performance Review Cadence

| Trigger | Action |

|---|---|

| Every sprint | Review P95/P99 latency trends; flag any creeping degradation |

| Every quarter | Full performance budget review — update baselines, adjust targets, audit tooling |

| After major feature launch | Re-measure all Core Web Vitals and API SLOs; update baselines |

| After infrastructure change | Re-run full synthetic test suite; confirm no regression |

| After dependency upgrade | Run bundle size diff; confirm no unexpected size increase |

Next scheduled review: [Date]

Review owner: [Name / role]


Quality Checks

  • [ ] Every budget threshold is a specific number — not a range or "TBD"
  • [ ] Both frontend (if applicable) and backend targets are defined — not just one or the other
  • [ ] Measurement tooling is named with a link to the dashboard or config file
  • [ ] CI enforcement is configured for at least one gate (build-time or deploy-time)
  • [ ] Budget breach response process names specific Slack channels and owners
  • [ ] Budget thresholds are anchored to baseline measurements or a justified target — not pulled from thin air
  • [ ] Per-journey targets are defined for critical user journeys, not just global averages

Anti-Patterns

  • [ ] Do not set budget thresholds without measuring a current baseline first — targets must be anchored to reality
  • [ ] Do not define global averages only — critical user journeys need individual budgets as they may diverge significantly
  • [ ] Do not omit CI enforcement — a performance budget that is not enforced in the build pipeline will not be respected
  • [ ] Do not leave the breach response process without named owners and escalation channels
  • [ ] Do not set budgets that apply only to one environment — production and staging targets should be documented separately if they differ

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