KubeBolt Cloud — KubeBolt Docs

KubeBolt Cloud is the managed offering of KubeBolt, the Kubernetes operations platform: the same core, run by us at app.kubebolt.io, plus the features that only exist there. You connect clusters with the agent exactly as documented in Connecting Clusters — the agent only ever dials outbound, so no inbound access to your clusters is required.

Sign up with email or social login (Google, Microsoft, or GitHub). Free and Team are available today; Business and Enterprise arrive in stages — see the public roadmap.

Open source vs Cloud

	Open source (self-hosted)	Cloud
Core platform — dashboards, insights, security findings, actions, multi-cluster	✅ Apache 2.0, free forever	✅
Kobi Copilot — you ask, Kobi answers and proposes actions you approve	✅ With your own LLM key (Anthropic or any OpenAI-compatible API)	✅ Managed, no key to configure
Kobi MCP server (read-only)	✅	✅
AI usage	You pay your provider directly	AI credits included per plan
Kobi Autopilot — Kobi acts on its own, you approve the destructive part	—	✅ Open beta, from the Free plan
Hosting, upgrades, backups	You	Us
Sign-in	Local users and passwords	Email and password, or Google, Microsoft and GitHub
Teams & organizations	One organization, a single default team; Viewer / Editor / Admin roles	Organizations and teams with roles

The open-source core is not a demo — it’s the same engine, including Kobi Copilot, and it stays Apache 2.0. Cloud is for teams that would rather not run it themselves, and for Kobi Autopilot.

Kobi Autopilot (open beta)

Kobi Autopilot is Kobi’s autonomous mode: it investigates an incident and, within the policy your team sets, remediates it. It runs only on Cloud and is in open beta from the Free plan. It ships with deliberate guardrails:

Off until you turn it on — each organization opts in explicitly, and it starts in suggest-only mode.
Unattended time window — you define when it may work on its own, with a real timezone. Outside the window, incidents are parked and visible, not silently worked.
Destructive actions always require human approval, in every mode.
Approving takes a role. Approving or rejecting an action and re-running an incident require Editor; changing Autopilot’s settings requires Admin. Viewers no longer see Approve or Reject. Every decision is recorded with the user who made it, and approvals, re-runs and role rejections are audited.
One credit pool — Kobi Copilot and Autopilot draw from the same monthly pool of AI credits, and Usage & Credits shows how it splits between them.

Autopilot is a Cloud feature. In the open-source distribution, Kobi Copilot proposes and you approve — see Actions & Governance.

Repeats and credit pacing

Two rules keep Autopilot from spending the month on problems it has already diagnosed. Both live in Administration → AI & Autopilot → Kobi Autopilot → Repeats and credit pacing.

A diagnosis stands. A run that ends in a recommendation (or hands the incident to a person) leaves a diagnosis that holds for 7 days by default (Re-investigate an unchanged problem after … days; 0 turns it off). If the same problem comes back with no material change, Autopilot reopens the diagnosed incident and counts a recurrence instead of paying for a new run. A material change is a different rule; for a Deployment’s pods, a different pod-template-hash (a rollout undo back to the same broken spec is not one); otherwise a new generation of the owning workload.
One problem, one investigation. A consequence and its cause share one run whichever fires first: a rollout past its deadline is covered by image-pull, crash-loop, OOM, missing ConfigMap/Secret and readiness failures, and a crash-loop by OOM and liveness failures. A StatefulSet’s replicas (kafka-0, kafka-1, …) count as one workload.
The month’s credit is spread. With Spread this month’s credits across the month on (the default), what Autopilot may have spent by a given day is capped at pool × (day + days ahead) / days in the month, in UTC. A quiet day leaves its share for later; a busy one can borrow up to 3 days ahead by default. Paced runs go one at a time, and an incident that has to wait is parked as skipped_pacing and picked up again on its own, without a notification. Critical incidents ignore pacing (on by default).

A parked incident (skipped_quota, skipped_schedule, skipped_rate_limit, skipped_pacing) stays one incident for as long as the problem lasts.

Who hears about a recommendation

A recommendation waits for a person, so Autopilot makes sure one hears about it. In Kobi Autopilot → Who hears about it, Email recommendations and a weekly digest to the organization’s admins is on by default and independent of insight email, so silencing noisy insight mail does not silence Autopilot.

When no notification channel would carry a ready recommendation, it is emailed to the organization’s verified admins who have not opted out: once per incident every 24 hours, at most 20 per organization per day. The email names the organization, the cluster and the workload.
Once a week, admins get the recommendations nobody has applied yet, grouped by workload across every cluster. With nothing waiting, no email.
When nothing would reach anyone, Autopilot’s pages say so with a banner (Autopilot can’t notify anyone), and the settings show the delivery status.

Only the organization’s master notifications switch turns both emails off.

AI credits

Cloud plans include AI credits consumed by Kobi Copilot conversations and Autopilot runs; there is no bring-your-own-key on Cloud. Usage is visible in the unified AI hub, in credits, not dollars: the Copilot and Autopilot usage views, the credit pool, the session and run details and the incident pages all count in the same unit your plan is sold in. When a plan’s monthly credits run out, Kobi pauses until the next month — the non-AI parts of the product keep working.

Signing up? Go straight to Cloud onboarding. Self-hosting instead? Installation methods covers every way to run KubeBolt yourself.