Setting the file. One moment.
Chapter 04 · Cloudflare Deploy
Subchapter 4.20
references/analytics-engine/patterns.mdMarkdown2 KBView on GitHub
| Use Case | Key Metrics | Index On |
|---|---|---|
| API Metering | requests, bytes, compute_units | api_key |
| Feature Usage | feature, action, duration | user_id |
| Error Tracking | error_type, endpoint, count | customer_id |
| Performance | latency_ms, cache_status | endpoint |
| A/B Testing | variant, conversions | user_id |
env.ANALYTICS.writeDataPoint({
blobs: [pathname, method, status, tier],
doubles: [1, computeUnits, bytes, latencyMs],
indexes: [apiKey]
});
// Query: Monthly usage by customer
// SELECT index1 AS api_key, SUM(double2) AS compute_units
// FROM usage WHERE timestamp >= DATE_TRUNC('month', NOW()) GROUP BY index1env.ANALYTICS.writeDataPoint({
blobs: [endpoint, method, errorName, errorMessage.slice(0, 1000)],
doubles: [1, timeToErrorMs],
indexes: [customerId]
});env.ANALYTICS.writeDataPoint({
blobs: [pathname, method, cacheStatus, status],
doubles: [latencyMs, 1],
indexes: [userId]
});
// Query: P95 latency by endpoint
// SELECT blob1, quantile(0.95)(double1) AS p95_ms FROM perf GROUP BY blob1| ❌ Wrong | ✅ Correct |
|---|---|
await writeDataPoint() | writeDataPoint() (fire-and-forget) |
indexes: [method] (low cardinality) | blobs: [method], indexes: [userId] |
blobs: [JSON.stringify(obj)] | Store ID in blob, full object in D1/KV |
| Write every request at 10M/min | Pre-aggregate per second |
| Query from Worker | Query from external service/API |
doubles: [latency, 1] for AVG calculationsStatus.SUCCESS/**
* Dataset: my_metrics
*
* Blobs:
* blob1: endpoint, blob2: method, blob3: status
*
* Doubles:
* double1: latency_ms, double2: count (always 1)
*
* Indexes:
* index1: customer_id (high cardinality)
*/