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Kestrel monitors your Kubernetes clusters and cloud infrastructure 24/7, detecting incidents as they happen. When something goes wrong, AI agents automatically investigate the root cause, generate production-ready YAML or Terraform fixes, identify the causal PR, and create postmortems — with optional auto-remediation.

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What You Get

  • 24/7 Monitoring — continuous detection across K8s and cloud resources
  • Automatic Root Cause Analysis — AI traces the full causal chain, not just symptoms
  • Production-Ready Fixes — YAML manifests and Terraform changes you can apply directly or merge as PRs
  • Causal PR Detection — identifies the code change that introduced the issue
  • Postmortem Generation — structured incident summaries for your team
  • Auto-Remediation — optionally apply fixes automatically (disabled by default)

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Setup

1

Connect a Kubernetes cluster or cloud account

Kestrel needs visibility into your infrastructure to detect incidents.For Kubernetes: Install the Kestrel Operator via Helm. See the Kubernetes integration guide for full instructions.
For AWS: Connect your account with a read-only IAM role. See the AWS integration guide.For OCI: Connect your Oracle Cloud tenancy. See the OCI integration guide.
You can connect multiple clusters and cloud accounts. Kestrel monitors all of them from a single dashboard.
2

(Optional) Connect observability tools

Adding observability context improves root cause analysis by giving Kestrel access to metrics, traces, and monitor alerts.
  • Datadog — pull metrics, monitors, and APM traces into incident investigations
  • OpenTelemetry — ingest traces and metrics from your OTel pipeline
Observability integrations are optional. Kestrel performs RCA using Kubernetes and cloud signals alone, but metrics context produces more precise root causes.
3

Connect notification channels

Route incident alerts to the tools your team already uses.
  • Slack — receive incident notifications in a channel, ask follow-up questions in threads, and get @mentioned as a namespace owner
  • PagerDuty — trigger on-call alerts with full RCA context and automatic resolution when the incident clears
4

Connect code repositories

Linking your repositories enables causal PR detection and GitOps-based remediation.
  • GitHub — detect which PR introduced the issue; create fix PRs automatically
  • GitLab — same capabilities via merge requests
When Kestrel generates a fix, it can open a PR against your repository so the change goes through your existing review and deployment pipeline.
5

Add knowledge sources

Knowledge sources give Kestrel historical and organizational context to produce better root cause analysis and more relevant fixes.
  • Confluence — runbooks, architecture docs, past incident writeups
  • Jira — related tickets and known issues
  • Glean — enterprise knowledge search across all your tools
  • Slack history — past conversations and tribal knowledge
See Knowledge Sources for setup details.

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Your First Incident

Once your integrations are connected, Kestrel begins monitoring immediately. Here’s what happens when an incident is detected:
  1. Detection — Kestrel identifies an anomaly (pod crash, deployment failure, cloud resource issue, etc.)
  2. Investigation — AI agents gather context from your cluster, cloud APIs, metrics, logs, and knowledge sources
  3. Root Cause Analysis — a structured RCA is generated with the full causal chain
  4. Fix Generation — production-ready YAML or Terraform changes are proposed
  5. Causal PR — if a recent code change caused the issue, the specific PR is identified
  6. Notification — alerts are sent to Slack, PagerDuty, or both — with the RCA, fix, and causal PR attached
  7. Remediation — apply the fix from the dashboard, merge the generated PR, or let auto-remediation handle it
Auto-remediation is disabled by default. Enable it per-cluster from Settings → Incident Response only after you’ve reviewed and trusted Kestrel’s fixes in your environment.

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Build Custom Incident Response Workflows

For more complex incident response scenarios — escalation chains, multi-step remediation, cross-team coordination — use Workflows to build custom automation that triggers on Kestrel incidents. Example: When a critical incident is detected in production, run RCA, post to Slack, page the on-call engineer via PagerDuty, create a Jira ticket, and if unacknowledged after 15 minutes, escalate to the engineering manager.