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Documentation Index

Fetch the complete documentation index at: https://docs.lumiqtrace.com/llms.txt

Use this file to discover all available pages before exploring further.

Run through this checklist before deploying LumiqTrace to a production environment. Each item addresses a common failure mode found in production integrations.

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SDK configuration

1

API key is in a secret manager, not hardcoded

Your lqt_ API key should never appear in source code or committed to version control. Set it as an environment variable and read it at runtime:
lumiqtrace.init({ apiKey: process.env.LUMIQTRACE_API_KEY! });
Verify with: grep -r "lqt_" src/ — this should return no matches.
2

environment is set to 'production'

Explicitly set the environment tag so your data is filtered correctly in the dashboard and anomaly detection runs on the right baseline:
lumiqtrace.init({
  apiKey: process.env.LUMIQTRACE_API_KEY!,
  environment: "production",
});
3

storePrompts policy is decided

storePrompts defaults to false — prompt text is never stored. If you enable it, you are storing user inputs and model outputs. Review your:
  • Privacy policy (does it cover LLM input storage?)
  • Data retention window (matches your plan’s setting)
  • Any regulatory requirements (GDPR, HIPAA, SOC 2)
If in doubt, leave it false and use tags for structured metadata instead.
4

sampleRate is tuned for your traffic volume

At high traffic, 100% tracing generates a lot of events and cost. Consider sampling:
Monthly LLM callsRecommended sampleRate
< 50K1.0 (trace everything)
50K – 500K0.5 – 1.0
500K – 5M0.1 – 0.25
> 5M0.05 – 0.1
lumiqtrace.init({ apiKey: "lqt_...", sampleRate: 0.25 });
5

Flush is called before process exit (serverless only)

If you deploy to Lambda, Vercel Functions, Netlify, or similar short-lived environments, verify flush() is called at the end of every handler. See the Serverless guide.
6

redactKeys covers all PII fields in your tags

Review every tags key your application sends. Add any fields that contain sensitive data to redactKeys:
lumiqtrace.init({
  apiKey: "lqt_...",
  redactKeys: ["email", "phone", "ip", "address"],
});
7

userId and sessionId are set on user-facing calls

These enable per-user cost breakdown and session replay. Make sure they are set in withLumiqtraceContext for all requests that involve authenticated users:
return withLumiqtraceContext({ userId: req.user.id, sessionId: req.session.id }, async () => {
  return callLLM(userMessage);
});

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Dashboard setup

1

At least one alert rule is configured

Before going live, create a baseline error-rate alert so you get notified if something breaks immediately after deployment:
  • Metric: error_rate
  • Condition: > 0.05 (5%)
  • Window: 15 minutes
  • Notify: your on-call email or Slack webhook
2

Cost alert is configured

Unexpected LLM code paths can cost hundreds of dollars in minutes. Create a cost alert:
  • Metric: cost_usd
  • Condition: > your daily budget
  • Window: 60 minutes
3

Run the Cost Optimizer once before launch

Navigate to AI Hub → Cost Optimizer and review the recommendations before launch. Model-switching opportunities are easiest to implement before traffic hits the feature.
4

Verify traces are appearing in the right project

After deploying, make a test LLM call and verify it appears in the Traces view of your production project — not staging. Confirm the environment tag shows production.

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Security

1

One API key per service

Avoid sharing a single API key across multiple services or environments. Use separate keys so you can rotate or revoke one without affecting others. See API Keys.
2

API key rotation schedule is documented

Add API key rotation to your team’s security calendar — every 90 days is a reasonable cadence for most teams. Document the rotation process so the next person doesn’t have to figure it out from scratch.
3

Team members have the right roles

Review Settings → Team and confirm that engineers who only need to view the dashboard have the Member role, not Admin. Admins can modify alert rules, guardrails, and SDK config.

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Quick verification after deployment

After deploying, run this end-to-end check:
  1. Make one LLM call through your application
  2. Wait 10–15 seconds
  3. Open the LumiqTrace dashboard and navigate to Traces
  4. Confirm the trace appears with environment: production, the correct model, non-zero token counts, and a non-zero cost
If the trace is missing, enable debug: true in your SDK and redeploy — the console output will show whether events are being created and whether flushes are succeeding.
All items checked? Your LumiqTrace integration is production-ready.