Agentic Debugging allows you to delegate debugging tasks to an AI agent that uses contextual data, integrated tools, and reasoning to analyze system symptoms, identify likely root causes and recommend next steps for remediation.

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🛠️ How It Works

DrDroid agent debug issues in your system. Here’s how it works: (a) Data Sources: Give the platform access to your telemetry data sources so it knows where to query metrics & logs. (b) Alerts: Access to alerts enables agent to decide when to investigate. (c) Runbooks: Provide an additional set of prompts / wiki so that the agent can leverage it during investigations. Runbooks are not required for standard/common scenarios but only for situations where user already has an opinion.

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🔄 Integration-Based Behavior

ScenarioBehavior
No integrations connectedThe agent provides general debugging guidance—questions to ask, commands to run, and logs to inspect manually.
Integrations connectedThe agent actively runs queries and fetches data (e.g., logs, metrics, infra info), uses that to reason, and then shares the diagnosis and remediation suggestions.

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📋 Example

For example, if a Kubernetes pod is CrashLooping, and you have observability integrations configured:
  • The agent may fetch logs, check deployment configurations, and diagnose the root cause (e.g., OOMKill, bad image).
  • If the root cause is found, the agent may suggest a remediation such as “Restart the pod” or “Increase memory limit”.