Using AI Agents to Debug Distributed Systems in Under a Minute
Using AI Agents to Debug Distributed Systems Faster At my company, we have a feature that allows customers to export large volumes of data to cloud providers. Under the hood, this export process is...

Source: DEV Community
Using AI Agents to Debug Distributed Systems Faster At my company, we have a feature that allows customers to export large volumes of data to cloud providers. Under the hood, this export process is split into multiple tasks, where each task is responsible for exporting a subset of objects. These tasks are executed by pods in a multi-tenant Kubernetes environment. From time to time, we receive alerts indicating that some tasks are taking too long to start and remain in the queue for an extended period. When that happens, an investigation begins. The challenge is that this analysis is usually slow, manual, and repetitive. A typical investigation involves: Checking the status of each task and validating key attributes Reviewing tenant configurations to identify values that may cause issues Inspecting overall cluster health Analyzing how many tasks each tenant has created Cross-checking configuration in Bitbucket Making multiple API calls across services This process can easily take severa