Why Your Open Source Project Needs Telemetry (And how to do it right)

Many open source maintainers are allergic to telemetry, and for good reason. We’ve all seen how “anonymous usage data” becomes a euphemism for invasive tracking. But here’s the uncomfortable truth: without understanding how users actually interact with your software, you’re building in the dark.

The good news? You can collect meaningful data without betraying your users’ trust. Below I’ll show you how to build telemetry that respects privacy, improves your product, and actually strengthens your relationship with your community.

1. Start With the Product Case (Because Better Software Benefits Everyone)

While many maintainers focus on the privacy concerns around telemetry, experienced developers understand that metrics unlock three critical capabilities:

Data-Driven Development: Without usage data, you’re making product decisions based on assumptions. I’ve seen maintainers spend months optimizing features that 2% of users touch while ignoring pain points affecting 80% of their base.

Issue Prioritization: Knowing that 90% of your errors come from Python 3.8 on Windows helps you fix the right bugs first, improving the experience for the majority of your users.

User Experience Insights: Understanding where users get stuck, which workflows they abandon, and what features they discover helps you build more intuitive software.

2. Design for Privacy First (Not Privacy Eventually)

The biggest mistake I see is treating privacy as an afterthought. Here’s what well-designed telemetry actually collects:

Technical Environment (Anonymized)

{
  "os": "linux",  // Not "Ubuntu 22.04.3 LTS"
  "arch": "x64",
  "runtime": "node_18",  // Not "v18.17.1"
  "memory_tier": "high",  // Not "32768MB"
  "install_method": "npm"
}

Usage Patterns (What, Not Who)

{
  "event": "feature_used",
  "feature": "api_export",
  "duration_bucket": "1000-5000ms",  // Not exact timing
  "success": true,
  "session_hash": "a7b9c2"  // Don't reuse between sessions
}

What Never Gets Logged

• IP addresses
• Usernames, paths, or filenames
• User-generated content or queries
• Unique device identifiers
• Detailed system specifications

3. Make Opt-Out Obvious (Not Opt-In Impossible)

Conventional wisdom says make telemetry opt-in. But in practice, opt-in rates below 3% make the data statistically useless. Instead, make opt-out so easy that users feel in control:

The First-Run Experience

Welcome to ProjectName v2.0!

📊 We collect anonymous usage data to improve your experience.
   This includes: feature usage, performance metrics, and errors.
   We NEVER collect: personal data, file contents, or identifiers.

   👀 View exactly what we collect: projectname.dev/telemetry

   Continue with telemetry? [Y/n]
   (You can change this anytime with --no-telemetry)

Five Ways to Opt Out

1. Environment variable: PROJECTNAME_TELEMETRY=0
2. Config file: telemetry: false
3. Command flag: -no-telemetry
4. Settings UI: Clear checkbox in preferences

Status Transparency

$ projectname --version
ProjectName v2.0.0
Telemetry: enabled (run with --no-telemetry to disable)

$ projectname --no-telemetry status
✅ Running with telemetry disabled

4. Build Transparency Into Your Architecture

Open source maintainers often hide their telemetry implementation out of shame. This is backwards. Make transparency a feature:

Open Source Everything

Your telemetry code should be as open as the rest of your project:

// telemetry/events.js - Make collection obvious
export function trackFeatureUsage(featureName) {
  if (!isTelemetryEnabled()) return;

  const event = {
    name: 'feature_used',
    feature: sanitizeFeatureName(featureName),
    timestamp: roundToHour(Date.now()),
    session: getDailySessionId(),
    context: getAnonymousContext()
  };

  telemetryQueue.push(event);
}

Data Manifesto

Publish a clear data policy:

## Our Telemetry Promise

1. **We collect the minimum data necessary** to improve the software
2. **We never collect personal information** or correlate sessions
3. **We delete raw data after 90 days** and only keep aggregates
4. **We will never sell or share** individual-level data
5. **You can opt out anytime** without feature degradation

Verify our implementation: [Source Code]

5. Implementation Patterns That Build Trust

Use Differential Privacy

Add statistical noise to sensitive metrics:

function addNoise(value, sensitivity = 1) {
  const noise = gaussianRandom() * sensitivity;
  return Math.round(value + noise);
}

// Report "approximately 50 API calls" not "exactly 47"
const apiCalls = addNoise(actualCalls, 5);

Batch and Aggregate Locally

Don’t send every event immediately. Aggregate on the client:

// Bad: Sends every click
onClick(() => telemetry.track('button_clicked'));

// Good: Batches into daily summary
onDaily(() => {
  telemetry.track('daily_usage', {
    feature_clicks: clickCounts,
    total_sessions: sessionCount,
    active_minutes: Math.round(activeTime / 60)
  });
});

Fail Silently and Safely

Telemetry should NEVER impact user experience:

async function sendTelemetry(events) {
  try {
    const timeout = setTimeout(() => controller.abort(), 5000);
    await fetch(TELEMETRY_URL, {
      method: 'POST',
      body: JSON.stringify(events),
      signal: controller.signal
    });
    clearTimeout(timeout);
  } catch (e) {
    // Silently fail - never interrupt the user
    debug('Telemetry failed:', e.message);
  }
}

6. Turn Your Community Into Advocates

Most maintainers fear community backlash when adding telemetry. But when done right, your most privacy-conscious users become your biggest advocates:

The Announcement Template

## Introducing Telemetry Done Right in v2.0

We're adding anonymous telemetry to help us understand how you use the software and where we can improve your experience.

What we're collecting:
- ✅ Feature usage counts
- ✅ Performance metrics
- ✅ Anonymous error reports

What we're NOT collecting:
- ❌ Personal information
- ❌ IP addresses
- ❌ File contents
- ❌ Unique identifiers

You can opt out instantly:
- Set PROJECTNAME_TELEMETRY=0
- Use --no-telemetry flag
- Disable in settings

Inspect the source code: [link]
Read our data policy: [link]

We built this with privacy advocates in our community.

Address Concerns Head-On

“Why not make it opt-in?” “We considered opt-in, but with typical 3% participation, we wouldn’t get statistically meaningful data. Instead, we made opt-out trivial and transparency absolute.”

“How do I verify what you’re sending?” “Run with --debug-telemetry to see every event before transmission. You can also inspect network traffic or review our open source implementation.”

“Will you sell this data?” “We legally commit to never selling individual-level data. We may share aggregate statistics like ‘40% of users use feature X’ in our reports.”

7. Common Pitfalls to Avoid

1. Feature Creep: Start minimal. You can always add more metrics later (with announcement).
2. Third-Party Troubles: If using analytics services, ensure they support your privacy constraints.
3. Marketing Speak: Skip the “we value your privacy” platitudes. Show, don’t tell.

8. The Path Forward

Well-implemented telemetry isn’t just possible, it’s essential for building better software. When implemented correctly, it becomes a feature that respects users while providing the insights needed to create exceptional products.

Start with these steps:

1. Define your minimal viable metrics (aim for under 10 event types)
2. Build transparency features first (dashboard, documentation)
3. Get community feedback on your implementation plan
4. Launch with a beta group of privacy-conscious users
5. Iterate based on feedback and publish learnings

Remember: users want software that works well and respects their privacy. Telemetry done right delivers both by helping you understand their needs while protecting their data.

Next Steps: Check out our open source telemetry library that implements these principles