> ## Documentation Index
> Fetch the complete documentation index at: https://docs.usekestrel.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Kestrel documentation - AI Agents for Platform Engineering

Kestrel is the agentic platform for platform engineering. Build workflows that automate incident response, cloud provisioning, CI/CD pipelines, and developer requests — using natural language, a drag-and-drop canvas, CLI, SDK, or MCP. Connect 30+ integrations, describe what you want, and let AI agents build the automation for you.

## What Kestrel Does

> [card] [Workflows](https://docs.usekestrel.ai/quickstart/workflows.md)
>
> Build workflows with natural language or a drag-and-drop canvas that automate incident response, cloud resource provisioning, CI/CD pipelines, and on-demand developer requests. Chain actions across Kubernetes, AWS, Slack, GitHub, PagerDuty, Datadog, Vercel, and more. Trigger from K8s signals, cloud events, Slack requests, custom webhooks, or any integration — with built-in observability.

> [card] [Incident Response](https://docs.usekestrel.ai/quickstart/incident-response.md)
>
> AI agents that monitor 24/7 for Kubernetes and cloud incidents. Automatic root cause analysis; YAML, Terraform, and code fix generation, causal PR detection, and postmortem creation — with optional auto-remediation.

> [card] [Cloud AI Copilot](https://docs.usekestrel.ai/quickstart/copilot.md)
>
> Ask questions about your infrastructure and applications in plain English. Investigate K8s clusters, cloud resources, metrics, network traffic, costs and more through a chat interface or the Slack `/kestrel` command.

## How It Works

**1. Connect your integrations**

Link Kubernetes clusters, cloud accounts, PaaS and deployment platforms, databases, CI/CD pipelines, observability tools, notification channels, code repositories, and knowledge sources from the Kestrel platform. Each integration takes less than two minutes to setup. Once connected, Kestrel automatically starts monitoring for Kubernetes and cloud incidents across both infrastructure and application layers. The Cloud AI Copilot also becomes available immediately — ask any question about your infrastructure through the dashboard chat or the Slack `/kestrel` command.

**2. Build workflows**

Describe what you want in natural language to the Workflow Agent — or drag and drop actions on the canvas, configuring triggers and actions using template variables. Kestrel's AI assembles and validates the workflow for you.

**3. AI handles the rest**

Workflows run automatically when triggered. AI agents execute each step, route notifications, generate fixes, create tickets, and escalate when needed — with full audit logs and observability.

## Integrations

Kestrel connects to your clouds, clusters, PaaS and deployment platforms, AI compute and sandbox providers, databases, CI/CD pipelines, IaC platforms, observability tools, notification channels, and knowledge sources.

### Clouds & Infrastructure

| Integration | Purpose |
| - | - |
| [Kubernetes](https://docs.usekestrel.ai/integrations/kubernetes.md) | Cluster monitoring, incident detection, resource inventory. **Workflows:** trigger on pod crashes, node failures, rollout issues; actions include RCA, fix generation, manifest creation, kubectl investigations |
| [Karpenter](https://docs.usekestrel.ai/integrations/karpenter.md) | Node autoscaling. **Workflows:** trigger on provisioning failures, node interruptions, NodePool limit exhaustion; actions include scaling NodePool limits, tuning disruption policy, applying NodePools, recycling nodes |
| [AWS](https://docs.usekestrel.ai/integrations/aws.md) | Cloud resource inventory, incident detection, VPC Flow Logs. **Workflows:** trigger on IAM, S3, EC2, RDS, Lambda events; actions include cloud RCA, Terraform/CLI generation, cost queries, anomaly detection, forecasting |
| [Google Cloud](https://docs.usekestrel.ai/integrations/gcp.md) | GCP project automation via Workload Identity Federation. **Workflows:** trigger on cost anomalies, budget overruns, preempted instances, unhealthy MIGs and node pools, Cloud Run failures, SCC findings, public buckets, BigQuery/Cloud SQL/Pub/Sub/Dataflow issues; actions include cost insights and remediation, instance and node pool lifecycle, Cloud Run rollback, IAM and bucket hardening, and data pipeline recovery |
| [OCI](https://docs.usekestrel.ai/integrations/oci.md) | Oracle Cloud resource inventory, incident detection, VCN Flow Logs |
| [Cloudflare](https://docs.usekestrel.ai/integrations/cloudflare.md) | Edge, DNS, and security automation. **Workflows:** trigger on security events, health check failures, Worker failures, SSL expiration; actions include DNS records, WAF/firewall rules, cache purges, Worker deploys/rollbacks, load balancer pools, tunnels |

### PaaS & Deployment Platforms

| Integration | Purpose |
| - | - |
| [Vercel](https://docs.usekestrel.ai/integrations/vercel.md) | Deployment events and build management. **Workflows:** trigger on deployment failures/successes, error anomalies; actions include getting deployments, build logs, rollbacks, promotions, AI investigation |
| [Railway](https://docs.usekestrel.ai/integrations/railway.md) | Deployment automation. **Workflows:** trigger on deployment events; actions include deployment logs, redeploys, restarts, rollbacks, environment variables, AI investigation |
| [Fly.io](https://docs.usekestrel.ai/integrations/flyio.md) | Machine lifecycle management. **Workflows:** trigger on machine start/stop/crash/create/destroy; actions include machine start/stop/restart, secrets, AI investigation |

### AI Compute & Sandboxes

| Integration | Purpose |
| - | - |
| [Nebius](https://docs.usekestrel.ai/integrations/nebius.md) | AI cloud GPU infrastructure. **Workflows:** trigger on GPU/node lifecycle events; actions include instance start/stop/restart, managed Kubernetes node-group scaling, AI investigation |
| [Beam](https://docs.usekestrel.ai/integrations/beam.md) | Serverless AI compute. **Workflows:** trigger on task, container, deployment, and machine events; actions include deployment scaling/start/stop, sandbox lifecycle, running commands, AI investigation |
| [Daytona](https://docs.usekestrel.ai/integrations/daytona.md) | Dev sandboxes. **Workflows:** trigger on sandbox, snapshot, and volume lifecycle events; actions include sandbox management, command execution, file transfer, AI investigation |

### Databases

| Integration | Purpose |
| - | - |
| [Supabase](https://docs.usekestrel.ai/integrations/supabase.md) | Project and branch automation. **Workflows:** actions include project/branch/backup/read-replica lifecycle, network restrictions, AI investigation |
| [Neon](https://docs.usekestrel.ai/integrations/neon.md) | Serverless Postgres. **Workflows:** actions include branch lifecycle, point-in-time restore, compute suspend/resume and autoscaling, reset-from-parent, credential rotation, AI investigation |
| [PlanetScale](https://docs.usekestrel.ai/integrations/planetscale.md) | MySQL branching and schema migrations. **Workflows:** trigger on branch/deploy-request events; actions include branch, deploy-request (schema migration), backup, and credential automation |
| [ClickHouse](https://docs.usekestrel.ai/integrations/clickhouse.md) | ClickHouse Cloud services. **Workflows:** trigger on error spikes; actions include service start/stop/scale, IP access lists, backups, ClickPipes ingestion, usage costs, AI investigation |
| [Databricks](https://docs.usekestrel.ai/integrations/databricks.md) | Databricks data platform. **Workflows:** trigger on failed/succeeded/long-running job runs, unexpected cluster terminations, and DLT pipeline failures (poll-based); actions include run/repair/cancel jobs, run output triage, cluster and SQL warehouse lifecycle, DLT pipeline updates, SQL data-quality checks, AI investigation |

### CI/CD & GitOps

| Integration | Purpose |
| - | - |
| [GitHub](https://docs.usekestrel.ai/integrations/github.md) | GitOps deployments, causal PR detection, IaC remediation. **Workflows:** actions include creating PRs/issues, triggering Actions, waiting for runs, AI code investigation, AI code fix generation |
| [GitLab](https://docs.usekestrel.ai/integrations/gitlab.md) | GitOps deployments, merge request remediation. **Workflows:** actions include creating MRs/issues, triggering pipelines, waiting for pipeline completion |
| [Jenkins](https://docs.usekestrel.ai/integrations/jenkins.md) | Build automation. **Workflows:** trigger on build failures; actions include triggering builds (with parameters), monitoring builds, console logs, stopping runaway builds, AI investigation |
| [CircleCI](https://docs.usekestrel.ai/integrations/circleci.md) | Pipeline automation. **Workflows:** trigger on pipeline/workflow failures; actions include triggering pipelines, rerunning/canceling workflows, approving on-hold jobs, test results, AI investigation |
| [ArgoCD](https://docs.usekestrel.ai/integrations/argocd.md) | GitOps deployment management. **Workflows:** actions include triggering syncs, waiting for sync completion, checking application health status |
| [Argo Rollouts](https://docs.usekestrel.ai/integrations/argo-rollouts.md) | Progressive delivery. **Workflows:** actions include promoting, aborting, retrying, and rolling back canary and blue-green rollouts |
| [Flux CD](https://docs.usekestrel.ai/integrations/fluxcd.md) | GitOps reconciliation. **Workflows:** actions include reconciling, suspending, and resuming Kustomizations, HelmReleases, and sources |
| [Helm](https://docs.usekestrel.ai/integrations/helm.md) | Release management. **Workflows:** actions include installing, upgrading, rolling back, and uninstalling Helm releases |

### Infrastructure as Code

| Integration | Purpose |
| - | - |
| [Terraform Cloud](https://docs.usekestrel.ai/integrations/terraform.md) | Run lifecycle automation. **Workflows:** trigger on run events; actions include plan/apply/discard/cancel, workspace locking, variables, state outputs, drift detection, AI investigation |
| [Pulumi Cloud](https://docs.usekestrel.ai/integrations/pulumi.md) | Stack automation. **Workflows:** trigger on stack/deployment events; actions include stack updates, drift detection and remediation, deployment queue control, stack tags and outputs, AI investigation |

### Secret Management

| Integration | Purpose |
| - | - |
| [HashiCorp Vault](https://docs.usekestrel.ai/integrations/vault.md) | Secret lifecycle automation. **Workflows:** trigger on seal-status, secret-version, stale-secret, policy, and auth-method changes (poll-based, metadata only); actions include reading/writing KV secrets, rotating static roles, managing policies and leases, revoking tokens, AI investigation |
| [Infisical](https://docs.usekestrel.ai/integrations/infisical.md) | Secret management automation. **Workflows:** trigger on secret changes, approval requests, failed syncs, and new identities (poll-based via audit log); actions include managing secrets and folders, triggering syncs, reviewing approvals, querying audit logs, AI investigation |

### Platform Security

| Integration | Purpose |
| - | - |
| [SonarCloud](https://docs.usekestrel.ai/integrations/sonarcloud.md) | Code quality and security automation. **Workflows:** trigger on completed/failed analyses with quality gate results (webhook-delivered); actions include quality gate checks, listing issues and security hotspots, project metrics, and approval-gated triage (transition/assign/comment issues, review hotspots) |
| [Okta](https://docs.usekestrel.ai/integrations/okta.md) | Identity security automation. **Workflows:** trigger on lockouts, suspicious activity, admin grants, MFA changes, and group membership changes (poll-based via the System Log); actions include user lookups, System Log queries, suspensions, session revocation, password expiry, MFA resets, and group changes |
| [Kyverno](https://docs.usekestrel.ai/integrations/kyverno.md) | Policy-as-code enforcement. **Workflows:** trigger on policy violations and admission blocks (auto-detected in-cluster, streamed from PolicyReports); actions include listing policies and violations, switching policies between Audit and Enforce, applying and deleting policies |

### Observability & Analytics

| Integration | Purpose |
| - | - |
| [Datadog](https://docs.usekestrel.ai/integrations/datadog.md) | Metrics, monitors, and observability context. **Workflows:** actions include querying metrics, creating monitors, sending events, muting monitors |
| [OpenTelemetry](https://docs.usekestrel.ai/integrations/opentelemetry.md) | Metrics for incident root cause analysis and copilot context |
| [PostHog](https://docs.usekestrel.ai/integrations/posthog.md) | Product analytics events and session replay. **Workflows:** trigger on exceptions, rage clicks, console errors, log alerts; actions include session summaries, event queries, error issue details |

### Incident Management & Ticketing

| Integration | Purpose |
| - | - |
| [PagerDuty](https://docs.usekestrel.ai/integrations/pagerduty.md) | On-call alerting with RCA context and auto-resolution. **Workflows:** trigger on PD incidents; actions include creating/acknowledging/resolving alerts, adding notes, escalation |
| [Jira](https://docs.usekestrel.ai/integrations/jira.md) | Ticket creation and incident tracking. **Workflows:** actions include creating tickets, adding comments, transitioning ticket status |
| [Linear](https://docs.usekestrel.ai/integrations/linear.md) | Issue tracking. **Workflows:** actions include creating issues. Also used as a knowledge source |

### Notifications & Knowledge

| Integration | Purpose |
| - | - |
| [Slack](https://docs.usekestrel.ai/integrations/slack.md) | Notifications, interactive Q\&A, `/kestrel` copilot, `/kestrel-workflow` triggers. **Workflows:** trigger from Slack requests; actions include sending messages, threaded replies, approval requests, DMs |
| [Confluence](https://docs.usekestrel.ai/integrations/confluence.md) | RCA publishing, postmortems, runbooks. **Workflows:** actions include publishing RCA pages, postmortems, runbook entries, updating existing pages. Also used as a knowledge source during incident investigation |
| [Glean](https://docs.usekestrel.ai/integrations/glean.md) | Enterprise knowledge search during incident investigation |
| [Knowledge Sources](https://docs.usekestrel.ai/integrations/knowledge-sources.md) | Connect Slack, Confluence, Jira, Linear, Notion, and Glean as knowledge sources so incident investigations include similar past incidents, runbooks, and postmortems |

## Enterprise Security

Built for organizations that demand the highest standards of data privacy, security, and compliance.

* **SOC 2 Compliant** — Enterprise-grade security controls audited by an independent third party
* **Complete Data Isolation** — Your data is never combined with other customers
* **No Cross-Customer Training** — AI models are never trained on another customer's data
* **Read-Only by Default** — No write access unless you explicitly enable auto-remediation
* **Full Control Over Fixes** — Every AI-generated change requires your explicit approval
* **No Sensitive Data Storage** — Secrets are never sent to or stored on Kestrel servers

## Getting Started

> [card] [Workflows Quickstart](https://docs.usekestrel.ai/quickstart/workflows.md)
>
> Build your first workflow automation in seconds.

> [card] [Incident Response Quickstart](https://docs.usekestrel.ai/quickstart/incident-response.md)
>
> Set up agentic incident detection and response.

> [card] [Copilot Quickstart](https://docs.usekestrel.ai/quickstart/copilot.md)
>
> Start asking questions about your infrastructure and applications.


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