Grey Haven Observability Monitoring

Grey Haven Observability and Monitoring

Implement comprehensive monitoring for Grey Haven applications using Cloudflare Workers built-in observability tools.

Observability Stack

Grey Haven Monitoring Architecture

• Logging: Cloudflare Workers logs + wrangler tail
• Metrics: Cloudflare Workers Analytics dashboard
• Custom Events: Cloudflare Analytics Engine
• Health Checks: Cloudflare Health Checks for endpoint availability
• Error Tracking: Console errors visible in Cloudflare dashboard

Cloudflare Workers Logging

Console Logging in Workers

// app/utils/logger.ts
export interface LogEvent {
  level: "debug" | "info" | "warn" | "error";
  message: string;
  context?: Record<string, unknown>;
  userId?: string;
  tenantId?: string;
  requestId?: string;
  duration?: number;
}

export function log(event: LogEvent) {
  const logData = {
    timestamp: new Date().toISOString(),
    level: event.level,
    message: event.message,
    environment: process.env.ENVIRONMENT,
    user_id: event.userId,
    tenant_id: event.tenantId,
    request_id: event.requestId,
    duration_ms: event.duration,
    ...event.context,
  };

  // Structured console logging (visible in Cloudflare dashboard)
  console[event.level](JSON.stringify(logData));
}

// Convenience methods
export const logger = {
  debug: (message: string, context?: Record<string, unknown>) =>
    log({ level: "debug", message, context }),
  info: (message: string, context?: Record<string, unknown>) =>
    log({ level: "info", message, context }),
  warn: (message: string, context?: Record<string, unknown>) =>
    log({ level: "warn", message, context }),
  error: (message: string, context?: Record<string, unknown>) =>
    log({ level: "error", message, context }),
};

Logging Middleware

// app/middleware/logging.ts
import { logger } from "~/utils/logger";
import { v4 as uuidv4 } from "uuid";

export async function loggingMiddleware(
  request: Request,
  next: () => Promise<Response>
) {
  const requestId = uuidv4();
  const startTime = Date.now();

  try {
    const response = await next();
    const duration = Date.now() - startTime;

    logger.info("Request completed", {
      request_id: requestId,
      method: request.method,
      url: request.url,
      status: response.status,
      duration_ms: duration,
    });

    return response;
  } catch (error) {
    const duration = Date.now() - startTime;

    logger.error("Request failed", {
      request_id: requestId,
      method: request.method,
      url: request.url,
      error: error.message,
      stack: error.stack,
      duration_ms: duration,
    });

    throw error;
  }
}

Cloudflare Workers Analytics

Workers Analytics Dashboard

Access metrics at: https://dash.cloudflare.com → Workers → Analytics

Key Metrics:

• Request rate (requests/second)
• CPU time (milliseconds)
• Error rate (%)
• Success rate (%)
• Response time (P50, P95, P99)
• Invocations per day
• GB-seconds (compute usage)

Wrangler Tail (Real-time Logs)

# Stream production logs
npx wrangler tail --config wrangler.production.toml

# Filter by status code
npx wrangler tail --status error --config wrangler.production.toml

# Filter by method
npx wrangler tail --method POST --config wrangler.production.toml

# Filter by IP address
npx wrangler tail --ip 1.2.3.4 --config wrangler.production.toml

# Output to file
npx wrangler tail --config wrangler.production.toml > logs.txt

Accessing Logs in Cloudflare Dashboard

1. Go to https://dash.cloudflare.com
2. Navigate to Workers & Pages
3. Select your Worker
4. Click "Logs" tab
5. View real-time logs with filtering

Log Features:

• Real-time streaming
• Filter by status code
• Filter by request method
• Search log content
• Export logs (JSON)

Analytics Engine (Custom Events)

Setup Analytics Engine

wrangler.toml:

[[analytics_engine_datasets]]
binding = "ANALYTICS"

Track Custom Events

// app/utils/analytics.ts
export async function trackEvent(
  env: Env,
  eventName: string,
  data: {
    user_id?: string;
    tenant_id?: string;
    duration_ms?: number;
    [key: string]: string | number | undefined;
  }
) {
  try {
    await env.ANALYTICS.writeDataPoint({
      blobs: [eventName],
      doubles: [data.duration_ms || 0],
      indexes: [data.user_id || "", data.tenant_id || ""],
    });
  } catch (error) {
    console.error("Failed to track event:", error);
  }
}

// Usage in server function
export const loginUser = createServerFn({ method: "POST" }).handler(
  async ({ data, context }) => {
    const startTime = Date.now();
    const user = await authenticateUser(data);
    const duration = Date.now() - startTime;

    // Track login event
    await trackEvent(context.env, "user_login", {
      user_id: user.id,
      tenant_id: user.tenantId,
      duration_ms: duration,
    });

    return user;
  }
);

Query Analytics Data

Use Cloudflare GraphQL API:

query GetLoginStats {
  viewer {
    accounts(filter: { accountTag: $accountId }) {
      workersAnalyticsEngineDataset(dataset: "my_analytics") {
        query(
          filter: {
            blob1: "user_login"
            datetime_gt: "2025-01-01T00:00:00Z"
          }
        ) {
          count
          dimensions {
            blob1  # event name
            index1 # user_id
            index2 # tenant_id
          }
        }
      }
    }
  }
}

Health Checks

Health Check Endpoint

// app/routes/api/health.ts
import { createServerFn } from "@tanstack/start";
import { db } from "~/lib/server/db";

export const GET = createServerFn({ method: "GET" }).handler(async ({ context }) => {
  const startTime = Date.now();
  const checks: Record<string, string> = {};

  // Check database
  let dbHealthy = false;
  try {
    await db.execute("SELECT 1");
    dbHealthy = true;
    checks.database = "ok";
  } catch (error) {
    console.error("Database health check failed:", error);
    checks.database = "failed";
  }

  // Check Redis (if using Upstash)
  let redisHealthy = false;
  if (context.env.REDIS) {
    try {
      await context.env.REDIS.ping();
      redisHealthy = true;
      checks.redis = "ok";
    } catch (error) {
      console.error("Redis health check failed:", error);
      checks.redis = "failed";
    }
  }

  const duration = Date.now() - startTime;
  const healthy = dbHealthy && (!context.env.REDIS || redisHealthy);

  return new Response(
    JSON.stringify({
      status: healthy ? "healthy" : "unhealthy",
      checks,
      duration_ms: duration,
      timestamp: new Date().toISOString(),
      environment: process.env.ENVIRONMENT,
    }),
    {
      status: healthy ? 200 : 503,
      headers: { "Content-Type": "application/json" },
    }
  );
});

Cloudflare Health Checks

Configure in Cloudflare dashboard:

1. Go to Traffic → Health Checks
2. Create health check for /api/health
3. Configure:
   • Interval: 60 seconds
   • Timeout: 5 seconds
   • Retries: 2
   • Expected status: 200
4. Set up notifications (email/webhook)

Error Tracking

Structured Error Logging

// app/utils/error-handler.ts
import { logger } from "~/utils/logger";

export function handleError(error: Error, context?: Record<string, unknown>) {
  // Log error with full context
  logger.error(error.message, {
    error_name: error.name,
    stack: error.stack,
    ...context,
  });

  // Also log to Analytics Engine for tracking
  if (context?.env) {
    trackEvent(context.env as Env, "error_occurred", {
      error_name: error.name,
      error_message: error.message,
    });
  }
}

// Usage in server function
export const updateUser = createServerFn({ method: "POST" }).handler(
  async ({ data, context }) => {
    try {
      return await userService.update(data);
    } catch (error) {
      handleError(error, {
        user_id: context.user?.id,
        tenant_id: context.tenant?.id,
        env: context.env,
      });
      throw error;
    }
  }
);

Viewing Errors in Cloudflare

1. Workers Dashboard: View errors in real-time
2. Wrangler Tail: npx wrangler tail --status error
3. Analytics: Check error rate metrics
4. Health Checks: Monitor endpoint failures

Supporting Documentation

All supporting files are under 500 lines per Anthropic best practices:

• examples/ - Complete monitoring examples

  • cloudflare-logging.md - Structured console logging
  • wrangler-tail.md - Real-time log streaming
  • analytics-engine.md - Custom event tracking
  • health-checks.md - Health check implementations
  • error-tracking.md - Error handling patterns
  • INDEX.md - Examples navigation

• reference/ - Monitoring references

  • cloudflare-metrics.md - Available metrics
  • wrangler-commands.md - Wrangler CLI reference
  • alert-configuration.md - Setting up alerts
  • INDEX.md - Reference navigation

• templates/ - Copy-paste ready templates

  • logger.ts - Cloudflare logger template
  • health-check.ts - Health check endpoint

• checklists/ - Monitoring checklists

  • observability-setup-checklist.md - Setup checklist

When to Apply This Skill

Use this skill when:

• Setting up monitoring for new Cloudflare Workers projects
• Implementing structured logging with console
• Debugging production issues with wrangler tail
• Setting up health checks
• Implementing custom metrics tracking with Analytics Engine
• Configuring Cloudflare alerts

Template Reference

These patterns are from Grey Haven's production monitoring:

• Cloudflare Workers Analytics: Request and performance metrics
• Wrangler tail: Real-time log streaming
• Console logging: Structured JSON logs
• Analytics Engine: Custom event tracking

Critical Reminders

1. Structured logging: Use JSON.stringify for console logs
2. Request IDs: Track requests with UUIDs for debugging
3. Error context: Include tenant_id, user_id in all error logs
4. Health checks: Monitor database and external service connections
5. Wrangler tail: Use filters to narrow down logs (--status, --method)
6. Performance: Track duration_ms for all operations
7. Environment: Log environment in all messages for filtering
8. Analytics Engine: Use for custom metrics and event tracking
9. Dashboard access: Logs available in Cloudflare Workers dashboard
10. Real-time debugging: Use wrangler tail for live production debugging