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Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It is designed to manage complex computational workflows and data processing pipelines. Airflow's webserver component provides a user interface to monitor and manage these workflows.
The Prometheus alert AirflowWebserverHighCpuUsage indicates that the Airflow webserver is consuming an unusually high amount of CPU resources. This can lead to performance degradation, slow response times, and potential downtime if not addressed promptly.
When the Airflow webserver experiences high CPU usage, it often results from inefficient configurations, excessive load, or suboptimal resource allocation. This alert is triggered when the CPU usage exceeds a predefined threshold, signaling that the webserver is struggling to handle the current load efficiently.
To resolve the high CPU usage issue, follow these steps:
First, determine the load on the webserver. Use tools like Grafana to visualize CPU usage metrics and identify peak load times. This can help pinpoint whether the high usage is due to specific times or events.
Review and optimize the webserver configuration settings. Consider adjusting parameters such as:
workers
: Increase the number of worker processes if the server is under heavy load.worker_class
: Use a more efficient worker class like gevent
or eventlet
for handling concurrent requests.Refer to the Airflow Configuration Reference for detailed configuration options.
If the webserver consistently experiences high CPU usage, consider scaling up the resources. This can involve increasing the CPU allocation or moving to a more powerful instance type if running on cloud infrastructure.
For environments with high traffic, implementing a load balancer can distribute incoming requests across multiple webserver instances, reducing the load on any single server. Tools like NGINX or HAProxy can be used for this purpose.
After making changes, continue to monitor the CPU usage to ensure the issue is resolved. Adjust configurations and resources as necessary based on ongoing performance metrics.
By following these steps, you can effectively diagnose and resolve high CPU usage in the Apache Airflow webserver, ensuring smooth and efficient operation of your workflow management system. Regular monitoring and proactive resource management are key to preventing such issues in the future.
(Perfect for DevOps & SREs)
(Perfect for DevOps & SREs)