Kai is CloudThinker’s Kubernetes AI agent. It detects the incident, finds root cause, remediates in a sandbox, and verifies the fix — under your team’s policy, with brokered credentials and a tamper-evident audit. Engineers stay on the loop, not on the night shift.
Works with EKS, GKE, AKS, and self-managed clusters. No standing credentials required.
Clusters scale faster than the humans who operate them. The signal grows; the on-call bandwidth does not.
Kai runs the DARV loop — Detect, Analyze, Remediate, Verify — so a Kubernetes incident goes from page to proven fix without a human in the middle of every step.
01
02
03
04
New in the DARV loop? Read the DARV loop explained.
Kai does not get the keys on day one. Every runbook starts at L1 — investigate and propose. As it earns trust in your environment, you promote it to act-with-approval, then to autonomous within a defined guardrail. Trust is granted per runbook, per cluster, not all at once.
How graduated autonomy worksGiving an AI agent access to production Kubernetes is only safe when the platform is built for it. Kai’s access is brokered, scoped, sandboxed, tokenized, and logged — end to end.
No standing cluster access. Kai gets scoped, task-time credentials issued at the moment of the job and revoked after.
Learn moreThe credential lives in an isolated environment, never in the prompt. Every action is reversible and contained.
Learn moreSensitive data — secrets, PII in logs — is deterministically tokenized at egress before it ever reaches a model.
Learn moreEvery detection, decision, and action lands in an audit trail you can replay for compliance and post-mortems.
Learn moreA Kubernetes AI agent is an autonomous system that investigates and acts on cluster problems — CrashLoopBackOff, OOMKills, failing rollouts, pending pods, noisy alerts — instead of only surfacing them on a dashboard. CloudThinker’s Kai runs the full DARV loop (Detect, Analyze, Remediate, Verify) under team policy, with brokered credentials, sandboxed execution, deterministic data tokenization, and a tamper-evident audit trail, so engineers stay on the loop rather than in the weeds.
A copilot suggests a command and waits for you to run it; Kai closes the loop. It reasons over live cluster state, proposes or executes a remediation inside a sandbox with scoped, task-time credentials, and verifies that the fix actually held — then writes an audit record. You choose how much autonomy it has per environment, from notify-only up to fully autonomous within a guardrail.
Only within the autonomy level you set. On graduated autonomy, new actions start at L1 (Kai investigates and proposes). As a runbook earns trust you promote it to L2 (act with approval, via a scoped change request), then L3–L4 (autonomous within a defined guardrail). Every action is reversible, scoped to brokered credentials, and logged in a tamper-evident audit.
Common day-2 cluster toil: CrashLoopBackOff and OOMKilled pods, failed or stuck deployments and rollbacks, pending pods and scheduling/node-pressure issues, misconfigured resource requests and limits, HPA and autoscaling anomalies, ingress and networking failures, RBAC and drift questions, and cost/rightsizing across namespaces. Kai correlates the signal, finds root cause, remediates, and verifies.
Yes. Kai connects to your observability and alerting stack (Prometheus, Grafana, Datadog, Alertmanager, PagerDuty) and your clusters (EKS, GKE, AKS, self-managed) through CloudThinker Connections. It ingests the signal you already produce rather than asking you to rip anything out.
It is when the platform is built for it. Kai never holds standing cluster credentials — access is brokered per task, scoped to the job, and lives inside a sandbox rather than a prompt. Sensitive data is deterministically tokenized at egress, and every action lands in a tamper-evident audit. That is the difference between an autonomous Kubernetes agent and an unsupervised script.
Connect a cluster and watch Kai detect, analyze, remediate, and verify — under your policy, with a full audit trail. Start free or book a walkthrough.
Prefer to talk first? Contact our team.