After the Kaggle notebook launch, verify that the SDK telemetry headers we added are being captured in production.
Context:
We published:
- Python SDK v1.0.2 with telemetry headers (
X-SDK-Language, X-SDK-Version, X-Client-Type)
- Node.js SDK v0.3.2 with same headers
What to Check (24-48 hours after Kaggle launch):
Query production database:
-- Check if SDK telemetry is being captured
SELECT
sdk_language,
sdk_version,
COUNT(*) as requests
FROM api_requests
WHERE created_at > NOW() - INTERVAL '24 hours'
AND sdk_language IS NOT NULL
GROUP BY sdk_language, sdk_version
ORDER BY requests DESC;
-- Identify Kaggle traffic
SELECT
COUNT(*) as kaggle_requests,
sdk_language,
user_agent
FROM api_requests
WHERE created_at > NOW() - INTERVAL '24 hours'
AND (
user_agent LIKE '%kaggle%'
OR user_agent LIKE '%OilPriceAPI-Python%'
)
GROUP BY sdk_language, user_agent;
Success Criteria:
- ✅ SDK telemetry headers appear in database
- ✅ Can distinguish SDK users from manual API calls
- ✅ Can identify Kaggle notebook traffic
- ✅ Download spike correlates with Kaggle views
Follow-up Actions:
- Track SDK adoption metrics weekly
- Create dashboard for SDK usage
- Identify power users for outreach
Related:
After the Kaggle notebook launch, verify that the SDK telemetry headers we added are being captured in production.
Context:
We published:
X-SDK-Language,X-SDK-Version,X-Client-Type)What to Check (24-48 hours after Kaggle launch):
Query production database:
Success Criteria:
Follow-up Actions:
Related: