SerOps in 2 minutes: from a broken deploy to the root cause

0:00Production is down. Four tools. Four tabs. No answer.

0:05This is SerOps. Know why production broke.

0:09Every 15 minutes, SerOps reads your logs, metrics, traces, deploys and code, and finds incidents even when no alert fired.

0:17When something breaks, the overview leads with it: why it is happening, and what to do.

0:23Every incident becomes an issue, ranked by severity, not a flood of alerts.

0:28One click: the root cause, the fix, and why the AI thinks so, step by step.

0:36The full analysis, in plain language: the v2.3.4 hotfix left a long query holding a row lock.

0:43How it got there, and the commit it traced the incident to.

0:48The correlated timeline draws the causal chain: the deploy, the failing trace, the errors.

0:54And the fix to apply, next to the exact commit and its author.

1:00Every finding comes with the traces, logs and metrics behind it.

1:05In the middle of an incident? Pick a window, say what you see, and investigate now.

1:15Ask follow-up questions in plain language. Answers come from your data.

1:20Answers name the deploy, the commit, and how confident the AI is.

1:27The root cause reaches your on-call in Slack, Teams, PagerDuty, OpsGenie or email.

1:33Routing rules decide who hears about what, with escalation and quiet hours.

1:39Sentinel skips quiet windows, so the AI only runs when something changed.

1:44Bring your own model: Gemini, Claude, OpenAI, DeepSeek, or Ollama, fully local.

1:51It connects to the stack you already run: Git, CI/CD, logs, metrics and traces.

2:00Open source, and self-hosted with Docker or Helm, in about ten minutes. Secrets are redacted before anything reaches the AI.

2:09SerOps. Know why production broke. Try the live demo, or star us on GitHub.