Automating Common Diagnostics for Kubernetes, Linux, and other Common Components

Automated diagnostics, as part of the PagerDuty Process Automation portfolio, aims to enhance incident response by providing first responders with the tools to quickly identify and address issues without needing to escalate to specialists. Unlike alert correlation and monitoring, automated diagnostics focuses on determining the cause of an issue after an alert has been raised, using data from monitoring tools to aid in diagnosis. It offers out-of-the-box job templates that allow responders to perform common diagnostic tasks, such as querying logs or checking system statuses, thereby reducing the need for specialist intervention and lowering incident response times and costs. The implementation of automated diagnostics is particularly beneficial for repetitive investigative steps across various environments, enabling responders to efficiently manage incidents like high CPU usage or application errors. This approach allows for a more streamlined, self-sufficient incident response process, leveraging diagnostic data to provide deeper insights into the root causes of alerts.