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Run through this checklist before deploying Zespan 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 zsp_ API key should never appear in source code or committed to version control. Set it as an environment variable and read it at runtime:
Verify with: grep -r "zsp_" 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:
3

storePrompts is configured

storePrompts defaults to true — prompt and completion text are stored with PII redaction applied before transmission. If you don’t need prompt storage, set it to false to reduce data sent:
Ensure your redactKeys list covers any sensitive patterns your prompts may contain.
4

sampleRate is tuned for your traffic volume

At high traffic, 100% tracing generates a lot of events and cost. Consider sampling:
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:
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 withZespanContext for all requests that involve authenticated users:

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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 Features → 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 Zespan 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 Zespan integration is production-ready.