WaterCrawl provides a complete visualization solution for distributed crawler operation and maintenance by integrating the real-time monitoring system built by Celery task queue. The system can accurately track the status flow of each crawling task (Pending→Running→Success/Failed) and return 23 key indicators in real time via REST API, including the number of crawled pages, the list of failed URLs, and bandwidth usage.
The technical implementation uses Django Channels to establish a long WebSocket connection, and the front-end console can dynamically display task progress histograms and network topology diagrams. When abnormal conditions are triggered (e.g., 5 consecutive URLs timeout), the system automatically sends alert emails and generates error diagnostic reports. Practical data shows that the monitoring system shortens the average time for operation and maintenance personnel to locate problems from 47 minutes to 8 minutes.
In the e-commerce price monitoring scenario, enterprise users can use this function to grasp the progress of competitor data collection in real time, and when it is found that the completion rate of crawling a certain category of commodities reaches 95%, it immediately triggers the data analysis pipeline and realizes the minute-level response to the market situation.
This answer comes from the articleWaterCrawl: transforming web content into data usable for large modelsThe
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