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Platform Engineering

Developer Experience Metrics: Measuring What Matters in Platform Engineering

Luca Berton 1 min read
#developer-experience#metrics#dora#platform-engineering#devops

📏 Measuring What Matters

You can’t improve developer experience without measuring it. But most teams track the wrong things. Here’s a practical framework combining DORA, SPACE, and custom metrics.

DORA Metrics: The Foundation

The four key metrics from the DORA research program:

MetricEliteHighMediumLow
Deployment FrequencyMultiple/dayWeeklyMonthly< Monthly
Lead Time for Changes< 1 hour< 1 week< 1 month> 1 month
Change Failure Rate< 5%< 10%< 15%> 15%
Mean Time to Recovery< 1 hour< 1 day< 1 week> 1 week

Tracking DORA Automatically

# GitLab/GitHub webhook handler
@app.post("/webhook/deployment")
async def track_deployment(event: dict):
    metrics = {
        "deployment_frequency": count_deployments_today(),
        "lead_time": calculate_lead_time(
            first_commit=event["first_commit_at"],
            deployed_at=event["deployed_at"],
        ),
        "change_failure": was_rollback_needed(event["deployment_id"]),
    }
    
    prometheus_metrics.deployment_frequency.inc()
    prometheus_metrics.lead_time.observe(metrics["lead_time"].total_seconds())

SPACE Framework: Beyond Speed

DORA measures throughput. SPACE measures the human side:

  • Satisfaction and well-being → Developer surveys
  • Performance → Does the code do what it should?
  • Activity → Commits, PRs, deployments (use carefully)
  • Communication → PR review times, documentation quality
  • Efficiency → Time spent on productive vs. toil work

Developer Survey (Run Quarterly)

Rate 1-5:
1. I can deploy my changes to production easily
2. I can find the documentation I need
3. Our CI/CD pipeline is fast and reliable
4. I spend most of my time on meaningful work (not toil)
5. I feel productive with our current tools

Open-ended:
- What's the biggest blocker to your productivity?
- What would you change about our platform?

Custom Platform Metrics

Time to First Deployment

How long from “new developer joins” to “first production deploy”:

# Track onboarding funnel
onboarding_stages = {
    "account_created": timestamp_1,
    "first_commit": timestamp_2,
    "first_pr_merged": timestamp_3,
    "first_deploy": timestamp_4,
}

time_to_first_deploy = (
    onboarding_stages["first_deploy"] - onboarding_stages["account_created"]
)
# Target: < 1 week

Platform Adoption Rate

-- What percentage of teams use the golden path?
SELECT 
  COUNT(DISTINCT team) FILTER (WHERE uses_golden_path) * 100.0 / 
  COUNT(DISTINCT team) as adoption_rate
FROM service_catalog
WHERE lifecycle = 'production';

Toil Ratio

# Track time spent on operational tasks vs. feature development
toil_ratio = time_on_ops / (time_on_ops + time_on_features)
# Target: < 20%

Building Your Dashboard

Essential panels:

  1. DORA metrics — trend over 90 days
  2. CI/CD pipeline duration — P50 and P95
  3. Self-service success rate — % of requests that complete without manual intervention
  4. Developer satisfaction score — from quarterly surveys
  5. Time to first deploy — for new joiners

Key Insights

  1. Don’t gamify activity metrics — measuring commits incentivizes small commits, not better code
  2. Surveys matter more than logs — developer perception IS reality
  3. Trend matters more than absolute — are you improving quarter over quarter?
  4. Share metrics publicly — transparency drives improvement
  5. Act on feedback — metrics without action breed cynicism

Want to measure and improve your developer experience? I help teams build data-driven platform strategies. Get in touch.

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Luca Berton

AI & Cloud Advisor with 18+ years experience. Author of 8 technical books, creator of Ansible Pilot, and instructor at CopyPasteLearn Academy. Speaker at KubeCon EU & Red Hat Summit 2026.

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