Definition
Pipelines as real code
Starlark gives you functions, loops and reusable modules while evaluation stays deterministic and reviewable beside the repository.
Hive platform
Your pipelines. Your runners. One control plane.
Hive evaluates real pipeline code, schedules its DAG across the hardware you connect, keeps expensive inputs warm and exposes every run to people, scripts and agents through the same API.
The hosted control plane is operated in Germany. Your runners execute wherever you place them.
Scheduler · projected placement
One DAG can use very different machines.
Constraints, capacity, warm inputs and queue policy decide placement. The frozen run plan records what Hive decided before execution starts.
lintlinux · own runner
test × 3k8s · warm database
desktopmacOS · workstation node
deployprotected · release lane
- Pipeline language
- Starlark, versioned with code
- Execution
- BYO runners or booster capacity
- Interfaces
- Web · CLI · API · MCP
CI/CD core
A build system worth keeping even without an agent.
The agent layer is the differentiator. The scheduler, execution and data plane underneath are the reason its fixes can be verified.
Placement
Run where the work fits
Connect Linux, macOS, Windows or Kubernetes capacity. Labels, constraints, architectures, queues and caps shape placement.
Warm path
Start from warm inputs
Fingerprint-keyed images, registry caches and template test databases reduce repeated setup across nodes and runs.
Evidence
Tests and timing become platform data
Parsed reports, flaky-test history, step duration, queue wait, artifacts and logs accumulate without separate instrumentation.
Interfaces
One answer across web, CLI, API and MCP
Runs, logs, tests, fleet state and actions are first-class calls, so operators and agents do not scrape the UI.
Isolation
Tenant and lane boundaries stay explicit
Identity, scoped tokens, queue policy, resource limits and guarded actions are enforced by the control plane around each workload.
Hybrid execution
Bring hardware first. Rent bursts when it helps.
The hosted product keeps the control plane out of your operations budget while leaving compute placement under your control.
Your runners
Connect machines you already own.
A pull-based agent joins a machine or VM to the scheduler. Compute on those runners is not billed by Hive.
Booster capacity
Spill bursts onto rented hardware.
CPU-minute packs fund hosted execution when your own capacity is busy or the task needs a lane you do not operate.
Hosted control plane
We operate the coordination layer.
Projects, pipelines, runs, logs, artifacts, agents and policy stay available without asking your team to run Hive itself.
Fits the stack
If it can run in CI, Hive can schedule it.
First-class helpers shorten common cases; ordinary commands keep the platform open-ended.
Build + test
pytestruffvitestESLintgo testclippynextest
Delivery
GitHubArgoCDKubernetesregistriesartifacts
Agents
OpenAI CodexOpenRouterAnthropic ClaudeCursorMCP
What the platform enables
Move from orchestration to a control loop that can act on its own evidence.
Self-healing CI
Turn eligible red checks into candidates
The run wakes a scoped agent; the resulting branch gate remains authoritative.
Explore the repair loopAgents
Operate sessions across the same fleet
Workstation, cloud and Factory agents share the workspace around the pipeline.
Explore the agent platformPrivate beta
Bring one repository. See the whole system work.
Start on your own runner, keep your existing CI beside it, and watch Hive turn the next eligible red check into a reviewable fix.