DevOps/SRE Copilot

The Problem

Modern infrastructure generates an enormous volume of signals — logs, metrics, traces, alerts. The challenge isn't collecting data, it's making sense of it fast enough to matter. Alert fatigue is real. Incidents that span multiple services take too long to diagnose. Postmortems get written once and forgotten.

Your team's operational knowledge lives in runbooks (often outdated), Slack threads (impossible to search), and people's heads (not available at 3am).

What the Agent Does

• Multi-source monitoring: ingest signals from Datadog, PagerDuty, Sentry, CloudWatch, and your logging stack
• Incident correlation: connect alerts across services to identify root causes, not just symptoms
• Incident summaries: draft incident summaries, response notes, and postmortems as events unfold
• Runbook execution: suggest runbook steps and auto-execute safe remediations (restart a service, scale up a pool, toggle a feature flag)
• Deployment health: track the impact of every deploy — "last release increased error rate 3x on the checkout service"

What Makes This Different

Generic AI assistants can read logs. A connected Botyard agent can use your architecture, service ownership, incident history, and runbooks as context for the response.

When the payments service starts throwing 500s, the useful output is not just "payments is down." It is a reviewable summary of the signals, recent deploys, similar incidents, likely owners, and suggested next checks.

Getting Started

Connect your observability stack, feed the agent your service catalog and ownership map, and point it at your incident history. It starts correlating from day one and gets sharper as it sees more incidents.