Introduction - Kestrel AI

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

Workflows

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.

Incident Response

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.

Cloud AI Copilot

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

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.

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.

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	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	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	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
OCI	Oracle Cloud resource inventory, incident detection, VCN Flow Logs
Cloudflare	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	Deployment events and build management. Workflows: trigger on deployment failures/successes, error anomalies; actions include getting deployments, build logs, rollbacks, promotions, AI investigation
Railway	Deployment automation. Workflows: trigger on deployment events; actions include deployment logs, redeploys, restarts, rollbacks, environment variables, AI investigation
Fly.io	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	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	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	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	Project and branch automation. Workflows: actions include project/branch/backup/read-replica lifecycle, network restrictions, AI investigation
Neon	Serverless Postgres. Workflows: actions include branch lifecycle, compute suspend/resume and autoscaling, reset-from-parent, credential rotation, AI investigation
PlanetScale	MySQL branching and schema migrations. Workflows: trigger on branch/deploy-request events; actions include branch, deploy-request (schema migration), backup, and credential automation
ClickHouse	ClickHouse Cloud services. Workflows: trigger on error spikes; actions include service start/stop/scale, IP access lists, backups, ClickPipes ingestion, usage costs, AI investigation

CI/CD & GitOps

Integration	Purpose
GitHub	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	GitOps deployments, merge request remediation. Workflows: actions include creating MRs/issues, triggering pipelines, waiting for pipeline completion
Jenkins	Build automation. Workflows: trigger on build failures; actions include triggering builds (with parameters), monitoring builds, console logs, stopping runaway builds, AI investigation
CircleCI	Pipeline automation. Workflows: trigger on pipeline/workflow failures; actions include triggering pipelines, rerunning/canceling workflows, approving on-hold jobs, test results, AI investigation
ArgoCD	GitOps deployment management. Workflows: actions include triggering syncs, waiting for sync completion, checking application health status
Argo Rollouts	Progressive delivery. Workflows: actions include promoting, aborting, retrying, and rolling back canary and blue-green rollouts
Flux CD	GitOps reconciliation. Workflows: actions include reconciling, suspending, and resuming Kustomizations, HelmReleases, and sources
Helm	Release management. Workflows: actions include installing, upgrading, rolling back, and uninstalling Helm releases

Infrastructure as Code

Integration	Purpose
Terraform Cloud	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	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

Observability & Analytics

Integration	Purpose
Datadog	Metrics, monitors, and observability context. Workflows: actions include querying metrics, creating monitors, sending events, muting monitors
OpenTelemetry	Metrics for incident root cause analysis and copilot context
PostHog	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	On-call alerting with RCA context and auto-resolution. Workflows: trigger on PD incidents; actions include creating/acknowledging/resolving alerts, adding notes, escalation
Jira	Ticket creation and incident tracking. Workflows: actions include creating tickets, adding comments, transitioning ticket status
Linear	Issue tracking. Workflows: actions include creating issues. Also used as a knowledge source

Notifications & Knowledge

Integration	Purpose
Slack	Notifications, interactive Q&A, `/kestrel` copilot, `/kestrel-workflow` triggers. Workflows: trigger from Slack requests; actions include sending messages, threaded replies, approval requests, DMs
Confluence	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	Enterprise knowledge search during incident investigation
Knowledge Sources	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

Workflows Quickstart

Build your first workflow automation in seconds.

Incident Response Quickstart

Set up agentic incident detection and response.

Copilot Quickstart

Start asking questions about your infrastructure and applications.

​What Kestrel Does

Workflows

Incident Response

Cloud AI Copilot

​How It Works

​Integrations

​Clouds & Infrastructure

​PaaS & Deployment Platforms

​AI Compute & Sandboxes

​Databases

​CI/CD & GitOps

​Infrastructure as Code

​Observability & Analytics

​Incident Management & Ticketing

​Notifications & Knowledge

​Enterprise Security

​Getting Started