kyber
AI
Run a fleet of sandboxed AI agents on a Kubernetes cluster and manage them from a console, API or chat
Kyber runs a fleet of long-lived AI agents on a Kubernetes cluster, giving each agent its own sandboxed pod with disk, tools, repos and memory that persist across restarts, upgrades and preemption. Agents are managed from a web console, a REST API, or two-way Telegram, Discord and Slack chat, and can be placed on cron schedules or send each other signed messages so one agent's output becomes another's prompt. It installs from a published Helm chart and is made to sign in with an existing Claude or ChatGPT subscription, with API keys as an alternative. Agent pods run with elevated privileges, so the documentation directs it at a cluster you are comfortable trusting agents with rather than a shared production one.
Self-hosted editions
- Self-hostedFree self-hosted
- LicenceOpen source · Apache-2.0DeploymentSelf-hosted
Limits, notes & source
Self-hosted
Pros & cons
Strengths
- Each agent keeps its whole filesystem across restarts: installed packages, cloned repos, credentials and memory. Source
- Manage the fleet from a web console, the REST API, or two-way Telegram, Discord and Slack chat from a phone. Source
- Agents can run on cron schedules that survive restarts and send each other signed messages to chain work. Source
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- Choose each agent's machine, VM type, disk, CPU and memory, then reboot, stop or open a shell into it. Source
Trade-offs
- You need a Kubernetes cluster for it, and the install is kubectl and Helm steps: namespace, signing key, API key. Source
- Agent pods run with elevated privileges, so it belongs on a cluster you trust agents with, not shared production. Source
- Kyber is solo-maintained and its CRDs and REST API are still evolving, with breaking changes in minor versions. Source
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