Processing Headline Metrics with Cloudflare Queues

This article is a follow-up to our previous post on Data Fetching and Storing with Cloudflare. While our previous implementation used a scheduled worker, we’ve since improved our headline metrics processing by implementing Cloudflare’s Queue system. This update has made our system more robust and scalable, while maintaining reliability and performance.

System Architecture

Our system consists of four main components working together:

1. Queue Producer: A scheduled worker that runs daily to initiate the data processing
2. Queue Consumer: Processes batches of headlines and stores their metrics
3. D1 Database: Stores headline performance data with advanced metrics calculations
4. Error Handling: Includes retries and dead letter queue for failed processing

Queue Implementation

Producer (Scheduled Worker)

The process begins with a worker that runs daily at midnight UTC:

[triggers]
crons = ["0 0 * * *"]  # Run daily at midnight UTC

Instead of processing data directly, the scheduled worker now sends a message to the queue:

async scheduled(controller…