Push. Wait. Wait some more. Check Slack. Answer email. Try to remember what you were working on. Finally, CI finishes - 35 minutes later. One test failed. Fix the test. Push again. Wait another 35 minutes. This cycle repeats dozens of times per day, across every developer on your team.
Slow CI pipelines are a silent productivity killer. Each minute waiting is a minute not coding. Each context switch drains focus. Each long wait encourages developers to batch changes - larger PRs that are harder to review and riskier to merge. The pipeline meant to give fast feedback has become a bottleneck that slows everything down.
CI pipelines slow down gradually. A test here, a build step there, each addition reasonable in isolation. But the cumulative effect is death by a thousand cuts. Nobody optimizes the pipeline because nobody owns it, and each individual slowdown seems too small to matter. Meanwhile, developer productivity erodes sprint by sprint.
The Math of Slow CI
Understanding the time cost reveals the true impact.
Per-Developer Cost
Calculate your team's CI wait time:
Typical developer day:
- 5 CI runs per day
- 30 minutes average wait per run
- 150 minutes waiting per day
- 2.5 hours lost per developer per day
That's 12.5 hours per week per developer spent waiting.
Team Cost
Multiply across your team:
10-person team:
- 125 hours waiting per week
- 3+ full-time engineers worth of time
- Just watching CI run
You're paying salaries for people to watch progress bars.
Context Switching Cost
Wait time isn't just wait time:
25-minute CI run:
- 5 minutes: Stay focused, check progress
- 10 minutes: Switch to other task
- 25 minutes: CI finishes, forget about it
- 30 minutes: Remember, context switch back
- 10 minutes: Reload context
- Total: 45+ minutes for 25-minute CI run
Context switching multiplies the cost.
Opportunity Cost
What could you do with that time:
2.5 hours per developer per day could be:
- More features shipped
- Better code quality
- Documentation written
- Technical debt addressed
Slow CI isn't just a cost - it's an opportunity lost.
Why CI Slows Down
CI pipelines slow down for predictable reasons.
Test Suite Growth
Tests accumulate:
Year 1: 500 tests, 2 minutes
Year 2: 2000 tests, 8 minutes
Year 3: 5000 tests, 20 minutes
Year 4: 10000 tests, 40+ minutes
More code means more tests means more time.
Build Complexity
Builds get complicated:
Initial build: npm install && npm build (3 min)
Plus TypeScript: +2 min
Plus linting: +1 min
Plus code generation: +2 min
Plus asset optimization: +3 min
Total: 11+ minutes before tests even start
Each addition is reasonable. The total is painful.
Coverage Requirements
Quality gates add steps:
Pipeline steps added over time:
- Unit tests
- Integration tests
- E2E tests
- Security scanning
- License checking
- Code quality analysis
- Coverage verification
Each step adds value. Each step adds time.
Environment Setup
Setup costs accumulate:
Every CI run:
- Provision runner (30 seconds)
- Clone repository (30 seconds)
- Install dependencies (2+ minutes)
- Build artifacts (2+ minutes)
Setup overhead adds up across many runs.
Flaky Retries
Flaky tests add retries:
Flaky test detected → Retry whole suite
That's another 20 minutes
Times 3 retries = 60+ minutes for passing build
Flakiness compounds time costs.
Sequential Execution
Steps that could parallelize don't:
Sequential pipeline:
Build (5 min) → Test (20 min) → Scan (5 min)
Total: 30 minutes
Could be parallel:
Build (5 min) → [Tests | Scans] (20 min)
Total: 25 minutes
Sequential execution wastes time.
The Feedback Loop Problem
Slow CI breaks fast feedback.
Delayed Discovery
Problems found late:
Fast CI (5 min): Find problem while context is fresh
Slow CI (30 min): Find problem after moving on
Late discovery means longer fixes.
Batching Behavior
Developers batch to avoid waits:
Fast CI: Small commits, frequent pushes
Slow CI: Large commits, infrequent pushes
Batching makes problems harder to isolate.
Review Delays
PR reviews wait for CI:
PR submitted → CI runs (30 min) → Reviewer looks
→ Comments → Author fixes → CI runs (30 min)
→ Reviewer re-reviews → Merge
Each CI wait extends review cycle
Slow CI multiplies through the PR process.
Deployment Drag
Slow CI slows deployment:
Deploy frequency vs CI time:
- 5 min CI: Deploy many times per day
- 30 min CI: Deploy a few times per day
- 60 min CI: Deploy once per day at most
Slow CI reduces deployment frequency.
Optimizing CI Pipelines
Pipelines can be made faster.
Parallelization
Run independent steps simultaneously:
@devonair optimize CI parallelization:
- Identify independent steps
- Run in parallel
- Aggregate results
Parallelization reduces wall-clock time.
Caching
Don't redo work:
@devonair configure CI caching:
- Cache dependencies
- Cache build artifacts
- Cache test results for unchanged code
Caching eliminates redundant work.
Test Splitting
Distribute tests across runners:
@devonair configure test splitting:
- Split test suite across multiple runners
- Balance test distribution
- Run in parallel
Splitting converts time to parallelism.
Incremental Testing
Only run affected tests:
@devonair enable incremental testing:
- Detect what changed
- Run only affected tests
- Full suite on main branch
Incremental testing runs less when appropriate.
Build Optimization
Make builds faster:
@devonair optimize build:
- Incremental builds
- Optimized bundler configuration
- Parallel compilation
Faster builds reduce overall time.
Dependency Management
Speed up dependency installation:
@devonair optimize dependencies:
- Lock file caching
- Minimal installation (production only for tests)
- Dependency mirroring
Dependencies are often the slowest step.
Measuring CI Performance
What gets measured improves.
Pipeline Duration
Track total time:
@devonair track CI metrics:
- Average pipeline duration
- P50, P90, P99 durations
- Duration trends over time
Duration is the headline metric.
Time by Stage
Know where time goes:
@devonair track stage timing:
- Build stage duration
- Test stage duration
- Each step's contribution
Stage timing reveals optimization targets.
Wait Time
Track developer waiting:
@devonair track wait time:
- Time from push to result
- Queue time (waiting for runner)
- Execution time
Wait time includes queue time, not just execution.
Flake Rate
Track retries:
@devonair track flakiness:
- Retry rate
- Tests requiring retries
- Time lost to retries
Flakiness costs time through retries.
CI Architecture Choices
Architecture affects performance.
Monorepo vs Polyrepo
Each has CI implications:
Monorepo CI:
- Can be slow if testing everything
- Needs smart affected detection
- Shared build cache benefits
Polyrepo CI:
- Naturally scoped
- May duplicate setup
- Independent pipelines
Architecture choice affects CI strategy.
Runner Selection
Choose appropriate runners:
@devonair configure runners:
- Large runners for builds (more CPU/memory)
- Standard runners for simple tests
- Right-size for the job
Right-sized runners are faster.
Self-Hosted vs Cloud
Trade-offs in each approach:
Cloud runners:
- Always available
- Pay per use
- Cold starts
Self-hosted:
- Warm caches
- Fixed capacity
- Maintenance burden
Choose based on your patterns.
Maintenance Work and CI
Maintenance affects CI time.
CI Configuration as Code
Treat CI config as maintained code:
@devonair maintain CI configuration:
- Version controlled
- Reviewed like code
- Optimized regularly
CI configs need maintenance too.
Regular Optimization
Schedule CI optimization:
@devonair schedule CI optimization:
- Monthly review of CI performance
- Identify slowest stages
- Implement improvements
Regular optimization prevents gradual slowdown.
Test Suite Health
Maintain test performance:
@devonair maintain test performance:
- Track slowest tests
- Optimize or fix slow tests
- Remove redundant tests
Test health directly affects CI time.
Dependency Hygiene
Keep dependencies lean:
@devonair maintain dependencies:
- Remove unused dependencies
- Use lighter alternatives
- Audit dependency size
Fewer dependencies means faster installs.
Building Fast CI Culture
Culture affects CI speed.
Pipeline Ownership
Someone owns CI performance:
CI ownership:
- Designated owner or team
- Responsible for performance
- Authority to make changes
Owned things get maintained.
Performance Budget
Set expectations:
CI performance budget:
- Target: < 10 minutes for most builds
- Alert: When approaching budget
- Action: Required optimization
Budgets prevent unbounded growth.
Fast Feedback Priority
Value fast feedback:
Team values:
- Fast CI is important
- Slow additions are questioned
- Speed is a feature
Teams that value speed maintain speed.
Getting Started
Speed up your CI today.
Measure current state:
@devonair analyze CI performance:
- Current duration
- Time by stage
- Bottlenecks
Identify quick wins:
@devonair identify CI optimizations:
- Caching opportunities
- Parallelization opportunities
- Unnecessary steps
Implement improvements:
@devonair implement CI improvements:
- Add caching
- Parallelize stages
- Remove waste
Track improvement:
@devonair monitor CI performance:
- Before and after metrics
- Ongoing tracking
- Regression alerts
Slow CI pipelines are fixable. With systematic measurement, targeted optimization, and ongoing maintenance, pipelines can become fast feedback loops that help developers rather than hinder them. Your team deserves CI that finishes before they've forgotten what they were working on.
FAQ
How fast should CI be?
Fast enough that developers don't context-switch while waiting. For most teams, that's under 10 minutes for the feedback they need. Critical path should be under 5 minutes. Full comprehensive tests can run longer as long as fast feedback runs first.
Should we run all tests on every push?
For most teams, no. Run fast tests and affected tests on every push. Run the full suite on merge to main. Use smart affected detection to minimize test runs while maintaining confidence.
How do we balance speed with thoroughness?
Tiered testing. Fast tests on every push give quick feedback. Comprehensive tests on main branch catch what quick tests miss. The key is that developers get fast feedback while maintaining confidence in main.
What about security scanning slowing CI?
Security scanning is important but doesn't need to block every push. Consider running security scans in parallel with other steps, running on merge rather than every push, or using incremental scanning that only checks changed code.