Analytics Engine Logs Adapter

Write authentication logs to Cloudflare Workers Analytics Engine for low-latency writes and SQL-based querying.

Architecture

This adapter uses Cloudflare's Workers Analytics Engine:

Write: Fire-and-forget writes using writeDataPoint() (no HTTP latency)
Query: SQL API for analyzing logs stored in Analytics Engine

When to Use Analytics Engine vs R2 SQL

Feature	Analytics Engine	R2 SQL + Pipelines
Write Latency	~0ms (fire-and-forget)	~50-100ms (HTTP)
Data Retention	90 days (free), configurable	Unlimited
Query Language	SQL (ClickHouse-like)	SQL (Iceberg)
Best For	Real-time analytics, recent logs	Long-term storage, compliance
Pricing	Free tier available	Pay per storage + queries

Prerequisites

1. Create an Analytics Engine Dataset

Configure in wrangler.toml:

toml

[[analytics_engine_datasets]]
binding = "AUTH_LOGS"
dataset = "authhero_logs"

Then deploy your Worker to create the dataset:

bash

npx wrangler deploy

Note: The Analytics Engine dataset is automatically created when you first deploy a Worker with the binding configured. The binding provides write access via writeDataPoint().

2. Create an API Token (For Queries)

To query logs via the SQL API, you need to create a Cloudflare API token:

Go to Cloudflare Dashboard API Tokens
Click "Create Token"
Select "Create Custom Token"
Configure:
- Token name: Analytics Engine Read
- Permissions:
  - Account → Analytics → Read
Click "Continue to summary" then "Create Token"
Save the token value - you won't be able to see it again

3. Get Your Account ID

Find your Cloudflare Account ID:

Go to Cloudflare Dashboard
Select any domain or go to Workers & Pages
Your Account ID is displayed in the right sidebar

Configuration

typescript

interface AnalyticsEngineLogsAdapterConfig {
  // Analytics Engine dataset binding (for Workers)
  analyticsEngineBinding?: AnalyticsEngineDataset;

  // Cloudflare account ID (required for SQL queries)
  accountId: string;

  // API token with Analytics Engine read permission
  apiToken: string;

  // Dataset name (default: "authhero_logs")
  dataset?: string;

  // HTTP timeout in ms (default: 30000)
  timeout?: number;
}

Methods

create(tenantId, log) - Create a log entry (writes to Analytics Engine)
get(tenantId, logId) - Get a specific log entry (queries SQL API)
list(tenantId, params) - List logs with pagination and filtering (queries SQL API)

Usage Example

typescript

import createAdapters from "@authhero/cloudflare-adapter";

// In a Cloudflare Worker
interface Env {
  AUTH_LOGS: AnalyticsEngineDataset;
  CLOUDFLARE_ACCOUNT_ID: string;
  ANALYTICS_ENGINE_API_TOKEN: string;
}

export default {
  async fetch(request: Request, env: Env) {
    const adapters = createAdapters({
      zoneId: "your-zone-id",
      authKey: "your-api-key",
      authEmail: "your-email",
      customDomainAdapter: yourDbAdapter,

      analyticsEngineLogs: {
        analyticsEngineBinding: env.AUTH_LOGS,
        accountId: env.CLOUDFLARE_ACCOUNT_ID,
        apiToken: env.ANALYTICS_ENGINE_API_TOKEN,
      },
    });

    const { logs } = adapters;

    // Write a log (fire-and-forget, no await needed but recommended)
    await logs.create("tenant-123", {
      type: "s",
      date: new Date().toISOString(),
      ip: request.headers.get("cf-connecting-ip") || "",
      user_agent: request.headers.get("user-agent") || "",
      isMobile: false,
      user_id: "user-456",
      description: "User logged in",
    });

    // Query logs
    const recentLogs = await logs.list("tenant-123", {
      per_page: 50,
      q: "type:s",
    });

    return new Response("OK");
  },
};

Querying Logs with SQL API

You can query Analytics Engine directly using the SQL API. The adapter's get() and list() methods use this API internally, but you can also query it directly.

Using cURL

bash

# Replace with your account ID and API token
export ACCOUNT_ID="your_account_id"
export API_TOKEN="your_api_token"

# List recent logs for a tenant
curl "https://api.cloudflare.com/client/v4/accounts/${ACCOUNT_ID}/analytics_engine/sql" \
  -H "Authorization: Bearer ${API_TOKEN}" \
  -H "Content-Type: text/plain" \
  -d "SELECT * FROM authhero_logs WHERE index1 = 'tenant-123' ORDER BY timestamp DESC LIMIT 50"

# Count logins by type
curl "https://api.cloudflare.com/client/v4/accounts/${ACCOUNT_ID}/analytics_engine/sql" \
  -H "Authorization: Bearer ${API_TOKEN}" \
  -H "Content-Type: text/plain" \
  -d "SELECT blob3 as type, count() as count FROM authhero_logs WHERE index1 = 'tenant-123' GROUP BY blob3"

# Get logs for specific user
curl "https://api.cloudflare.com/client/v4/accounts/${ACCOUNT_ID}/analytics_engine/sql" \
  -H "Authorization: Bearer ${API_TOKEN}" \
  -H "Content-Type: text/plain" \
  -d "SELECT * FROM authhero_logs WHERE index1 = 'tenant-123' AND blob8 = 'user-456' ORDER BY timestamp DESC"

# Example with all fields
curl "https://api.cloudflare.com/client/v4/accounts/${ACCOUNT_ID}/analytics_engine/sql" \
  -H "Authorization: Bearer ${API_TOKEN}" \
  -H "Content-Type: text/plain" \
  -d "SELECT * FROM auth_logs LIMIT 10;"

Query Tips

Important Notes:

Use index1 for filtering by tenant_id - it's indexed for efficient queries
The dataset name in queries is what you defined in wrangler.toml (e.g., authhero_logs or auth_logs)
Results are returned as JSON
Query language is ClickHouse-like SQL dialect

Common Query Patterns:

sql

-- Filter by time range
SELECT * FROM authhero_logs
WHERE index1 = 'tenant-123'
  AND timestamp >= NOW() - INTERVAL 1 DAY
ORDER BY timestamp DESC;

-- Aggregate by hour
SELECT
  toStartOfHour(timestamp) as hour,
  count() as login_count
FROM authhero_logs
WHERE index1 = 'tenant-123'
  AND blob3 = 's'
GROUP BY hour
ORDER BY hour DESC;

-- Failed login attempts by user
SELECT
  blob8 as user_id,
  blob9 as user_name,
  count() as failed_attempts
FROM authhero_logs
WHERE index1 = 'tenant-123'
  AND blob3 = 'f'
  AND timestamp >= NOW() - INTERVAL 7 DAY
GROUP BY blob8, blob9
ORDER BY failed_attempts DESC;

Data Schema

Analytics Engine stores logs using blob and double fields:

Field	Type	Description
blob1	string	log_id
blob2	string	tenant_id
blob3	string	type (e.g., "s", "f")
blob4	string	date (ISO string)
blob5	string	description
blob6	string	ip
blob7	string	user_agent
blob8	string	user_id
blob9	string	user_name
blob10	string	connection
blob11	string	connection_id
blob12	string	client_id
blob13	string	client_name
blob14	string	audience
blob15	string	scope
blob16	string	strategy
blob17	string	strategy_type
blob18	string	hostname
blob19	string	details (JSON stringified)
blob20	string	auth0_client (JSON stringified)
double1	number	isMobile (0 or 1)
double2	number	timestamp (epoch ms)
index1	string	tenant_id (for efficient filtering)

Passthrough Mode

Use the core createPassthroughAdapter utility to sync logs to multiple destinations:

typescript

import { createPassthroughAdapter } from "@authhero/adapter-interfaces";
import { createAnalyticsEngineLogsAdapter } from "@authhero/cloudflare-adapter";

// Primary adapter (e.g., database)
const databaseAdapter = createDatabaseLogsAdapter();

// Analytics Engine adapter for write syncing
const analyticsEngineAdapter = createAnalyticsEngineLogsAdapter({
  analyticsEngineBinding: env.AUTH_LOGS,
  accountId: env.CLOUDFLARE_ACCOUNT_ID,
  apiToken: env.ANALYTICS_ENGINE_API_TOKEN,
});

// Create passthrough adapter - writes to both, reads from primary
const logsAdapter = createPassthroughAdapter({
  primary: databaseAdapter,
  secondaries: [
    {
      adapter: { create: analyticsEngineAdapter.create },
      onError: (err) => console.error("Analytics sync failed:", err),
    },
  ],
});

// logs.create() writes to both adapters (database first, then Analytics Engine)
// logs.get() and logs.list() read from database only

Analytics Example

typescript

// Track login patterns
async function analyzeLoginPatterns(
  logsAdapter: LogsDataAdapter,
  tenantId: string,
) {
  const result = await logsAdapter.list(tenantId, {
    per_page: 1000,
    q: "type:s", // Successful logins only
  });

  const loginsByHour = {};
  result.logs.forEach((log) => {
    const hour = new Date(log.date).getHours();
    loginsByHour[hour] = (loginsByHour[hour] || 0) + 1;
  });

  return loginsByHour;
}

Environment Variables

env

# Analytics Engine Logs (optional)
CLOUDFLARE_ACCOUNT_ID=your_account_id
ANALYTICS_ENGINE_API_TOKEN=your_analytics_token
ANALYTICS_ENGINE_DATASET=authhero_logs

Error Handling

typescript

try {
  await logs.create(tenantId, logData);
} catch (error) {
  console.error("Failed to write log:", error);
  // Analytics Engine writes are fire-and-forget, so errors are rare
  // Consider implementing a fallback mechanism
}

UI Widget

Multi-Tenancy

Cloudflare

Analytics Engine Logs Adapter

Architecture

When to Use Analytics Engine vs R2 SQL

Prerequisites

1. Create an Analytics Engine Dataset

2. Create an API Token (For Queries)

3. Get Your Account ID

Configuration

Methods

Usage Example

Querying Logs with SQL API

Using cURL

Query Tips

Data Schema

Passthrough Mode

Analytics Example

Environment Variables

Error Handling

Analytics Engine Logs Adapter ​

Architecture ​

When to Use Analytics Engine vs R2 SQL ​

Prerequisites ​

1. Create an Analytics Engine Dataset ​

2. Create an API Token (For Queries) ​

3. Get Your Account ID ​

Configuration ​

Methods ​

Usage Example ​

Querying Logs with SQL API ​

Using cURL ​

Query Tips ​

Data Schema ​

Passthrough Mode ​

Analytics Example ​

Environment Variables ​

Error Handling ​

Related Documentation ​

Analytics Engine Logs Adapter

Architecture

When to Use Analytics Engine vs R2 SQL

Prerequisites

1. Create an Analytics Engine Dataset

2. Create an API Token (For Queries)

3. Get Your Account ID

Configuration

Methods

Usage Example

Querying Logs with SQL API

Using cURL

Query Tips

Data Schema

Passthrough Mode

Analytics Example

Environment Variables

Error Handling

Related Documentation