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Register a CircleCI namespace and a resource class for each runner pool, save the one-time class token securely, install Machine Runner 3 on every host, and route jobs with resource_class: namespace/name. For capacity changes, measure unclaimed and running tasks separately for each class, stay below your organization’s concurrency limit, and use single-task runners for disposable hosts or continuous runners with an idle-reclamation controller for persistent hosts.
How the pieces fit together
A multi-host self-hosted fleet has three distinct layers:
- Namespace: your organization’s scope for self-hosted runners. Most organizations use one namespace.
- Resource class: the named pool that describes a compatible execution environment, such as Linux, macOS, a particular CPU architecture, specialized hardware, or a trust tier.
- Runner host: a machine running CircleCI Machine Runner 3 and configured with the token for one resource class.
A job is routed to a pool by specifying the exact class name in its configuration. The value is always namespace/resource-class, not merely the host name. Namespace and class concepts are described in CircleCI’s self-hosted runner concepts and resource class overview.
Keep pools separate when machines differ in operating system, architecture, installed dependencies, hardware, network access, or trust level. Hosts that can execute the same jobs can share one class; materially different hosts should not be mixed and then discovered through failing jobs.
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Choose a fleet and lifecycle model first
| Decision | Manually managed hosts | Machine Runner Orchestrator |
|---|---|---|
| Provisioning control | You create, configure, patch, and retire machines with your existing host or cloud tooling. | Kubernetes and KubeVirt create runner virtual machines from a declarative deployment. |
| Best fit | Teams with established VM, bare-metal, or autoscaling-group operations. | Teams already operating Kubernetes, KubeVirt, Helm, and virtualized runner workloads. |
| Lifecycle choices | Use single-task for disposable machines or continuous for persistent machines. |
The orchestrator provisions hosts, but you still choose class settings and capacity behavior. |
| Scaling responsibility | Your fleet controller responds to class-specific demand and creates or destroys hosts. | The orchestrator manages runner VMs; Kubernetes cluster compute still has to be sized and scaled separately. |
| Prerequisites | Supported operating system, network access, runner installation, and secure token delivery. | Kubernetes, KubeVirt, kubectl, Helm 3 or later, class tokens, and /dev/kvm on every node that runs runner VMs. |
CircleCI documents the orchestrator prerequisites and configuration in its Machine Runner Orchestrator guide. It is an infrastructure option, not an automatic expansion of your underlying Kubernetes cluster. Likewise, container-runner pods may be created as work arrives, while the Kubernetes nodes that host them remain your responsibility.
Register the namespace and resource class
An organization administrator must create the self-hosted runner namespace and class. If your organization already uses CircleCI Orbs, the runner namespace is shared with that setup rather than being a second, isolated namespace.
- Identify the organization ID and decide on a stable namespace name. Treat it as part of your job configuration API; changing it later requires updating every job that references it.
- If the organization does not already have a namespace, create one with the CircleCI CLI:
circleci namespace create <name> --org-id <organization-id>- Create a resource class and ask the CLI to generate its token:
circleci runner resource-class create <namespace>/<resource-class> <description> --generate-token- Copy the token into an approved secret manager immediately. CircleCI displays a resource-class token only during class creation; do not put it in a repository, image layer, ticket, shell history, or public configuration.
- Record the class’s intended capabilities and trust boundary. Examples include
acme/linux-x86,acme/macos, or a class reserved for jobs that require a hardware device. Use names that remain accurate as hosts are replaced.
The command flow and one-time token behavior are covered in Machine Runner 3 manual installation. CLI syntax, package versions, and supported platforms can change, so check that page immediately before executing the commands.
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Install the current Machine Runner 3 package using CircleCI’s platform-specific instructions, then configure each host with the token for the class it should serve. The installation page uses current as the selector for the current binary; you can pin a specific version by changing that selection when reproducibility requires it.
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- Prepare the host. Use a dedicated operating-system account with only the permissions required by the jobs. Install required build tools and make sure the host can reach the CircleCI runner service and any registries or services that builds need.
- Install the runner. Follow the operating-system command sequence in the manual installation guide. Do not copy an old package URL or assume that a previous binary remains supported.
- Set a unique runner name. Every host should have a distinct, meaningful name, such as a hostname plus an availability-zone or role suffix. This makes inventory and incident response possible when several machines share one class.
- Choose a working directory. Give the runner a dedicated path with enough space for checkouts, caches, Docker layers, and build artifacts. Apply the cleanup policy appropriate for your workload so credentials and source files do not remain indefinitely.
- Provide the class token through the runner API configuration. Inject it from your secret store at service start instead of hard-coding it in an image or configuration repository.
- Select the lifecycle mode. Configure
single-taskwhen the host will be destroyed or re-imaged after one task. Configurecontinuouswhen the host should poll for more work after completing a task and a separate controller will remove idle capacity. - Start the service and verify registration. Confirm that the process remains running, reports the expected runner name and class, and appears in the runner inventory before sending production jobs to it.
For CircleCI Server, set the runner API URL to the hostname of the Server installation rather than assuming the Cloud endpoint. On CircleCI Cloud, the runner API is hosted at runner.circleci.com. Installation details and Server-specific settings are maintained in the manual installation documentation.
Route jobs to the correct host pool
Reference the exact namespace and class in the job. This illustrative configuration sends a machine job to the my-org/linux pool:
jobs:
build:
machine: true
resource_class: my-org/linux
steps:
- run: echo "Hello runner"Replace both parts with the values created for your organization. A typo in either component prevents the job from reaching the intended pool; it does not fall back to another class. Keep class names in one configuration variable or reusable command where many projects must target the same pool, but preserve the fully qualified value that CircleCI expects.
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- Create separate classes for Linux and macOS rather than allowing incompatible jobs to compete for one pool.
- Separate ARM and x86 hosts when binaries, caches, or toolchains are architecture-specific.
- Use a distinct class for GPU, licensed, device-attached, or otherwise scarce hardware.
- Isolate jobs with different network reachability or trust requirements; a class boundary is an operational and authorization control, not just a performance label.
Scale capacity from demand, class by class
Do not treat all runners as one interchangeable fleet. CircleCI’s scaling guidance uses unclaimed tasks, running tasks, and resource-class information. The task data is scoped to one resource class, so a controller must evaluate each class independently.
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- Enumerate classes. Maintain the classes your organization permits and map each class to its provisioning method, maximum size, and lifecycle mode.
- Query unclaimed tasks for one class. These are jobs that require that exact class but do not yet have a runner available to claim them.
- Query running tasks for the same class. Running work tells you how much capacity is already occupied and prevents a controller from adding hosts based only on a transient queue snapshot.
- Check the organization concurrency ceiling. Your plan’s organization-level concurrency limit caps the number of jobs that can execute. Adding machines beyond that ceiling can produce hosts that start successfully but cannot run additional work.
- Calculate a target for that class. Add enough capacity for pending work and an intentionally chosen warm buffer, subject to the class’s maximum and the organization limit. The exact thresholds, polling interval, warm count, and cloud-provider implementation are design choices, not universal CircleCI values.
- Provision or retire hosts. For
single-task, launch a clean host for a task and allow it to exit so the infrastructure controller can recycle it. Forcontinuous, add hosts when demand rises and remove idle hosts when demand falls. - Recheck after each change. Provisioning and runner registration are asynchronous. Poll again before launching another batch, and use running-task data to avoid a feedback loop that over-provisions while hosts are still starting.
The relevant runner API operations, including installed-runner inventory and unclaimed or running task queries, are documented in CircleCI’s self-hosted runner API reference. Confirm authentication, endpoint details, and the Server API address for your deployment before coding a controller.
A practical controller loop
- Poll each class on a fixed cadence with jitter so multiple controllers do not synchronize.
- Record the last observation, desired count, actual registered count, and provisioning operations for auditability.
- Use a scale-up threshold that requires pending work, then impose a cooldown while new hosts register.
- Use a longer scale-down delay than the scale-up delay to avoid destroying a host between short bursts.
- Stop launching capacity when the organization concurrency limit is reached, even if unclaimed tasks remain.
- Alert when hosts are registered but never claim work, when tasks remain unclaimed beyond your service target, or when runner versions drift.
Pick the right runner lifecycle
single-task for ephemeral capacity
A single-task runner exits after one task. This is useful when an image or VM is created for a job, then discarded. The exit signal gives your infrastructure controller a clean point to delete the machine and removes the need to scrub an unknown number of workspaces from a long-lived host. Startup time and image-pull time become part of job latency, so keep the image reproducible and provision only as much warm capacity as your workload justifies.
continuous for persistent capacity
A continuous runner polls for another task after completing one. It can reduce startup overhead for steady workloads, but it remains a live machine with workspaces, credentials, caches, and network access. Your controller must track idle hosts and shut down unused capacity. CircleCI also documents runner idle timeout as a way to recycle resources when demand drops; configure it with your cleanup and termination behavior rather than assuming it replaces fleet management.
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|---|---|---|
| Host lifetime | One task, then runner exits. | Multiple tasks until explicitly retired or timed out. |
| Isolation | Fresh host per task is straightforward. | Requires workspace cleanup, patching, and careful trust controls. |
| Scale-down trigger | Infrastructure can recycle the host after runner exit. | Controller must identify and remove idle hosts. |
| Startup overhead | Paid for each new host unless you keep warm capacity. | Amortized across tasks while the host remains available. |
Use the Machine Runner Orchestrator when Kubernetes is your control plane
The documented orchestrator creates runner VMs with Kubernetes and KubeVirt. Before deploying it, verify all of the following:
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- A functioning Kubernetes cluster with KubeVirt installed.
kubectlaccess and Helm 3 or later.- A resource-class token for every class the deployment will provision.
/dev/kvmexposed on every node that hosts runner VMs. Cloud nodes may require nested virtualization enabled before those nodes are created.- The correct CircleCI API address: Cloud uses the documented Cloud service; Server requires the appropriate Server address.
The orchestrator’s values configure resource classes as a map keyed by namespace/name. Several classes can share defaults while overriding settings for a particular operating system, image, size, or capacity policy. Validate the chart version and current compatibility matrix in the orchestrator documentation at implementation time.
Remember the boundary between runner and cluster scaling: creating more runner VMs does not create more Kubernetes nodes. If the cluster cannot schedule additional VMs, CircleCI jobs will remain unclaimed even though the desired runner count has increased.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Security controls for a multi-host runner fleet
Machine-runner jobs execute with the privileges of the operating-system account running the runner. Access to a Docker daemon is effectively root access on that machine. A runner process is therefore not a security boundary for arbitrary or untrusted workloads.
- Store class tokens in a secret manager and limit who can read or rotate them.
- Restrict which projects may target classes that have production network access, proprietary tools, signing keys, or attached devices.
- Use separate classes and accounts for less-trusted code; do not mix untrusted pull-request jobs with sensitive continuous hosts.
- Prefer disposable single-task hosts for workloads that cannot be strongly trusted or scrubbed.
- Remove credentials, source trees, temporary files, and Docker artifacts during host retirement or between continuous tasks.
- Patch the operating system, runner binary, build tools, and images on a defined schedule, and monitor runner versions in inventory.
- Limit outbound network access to what builds require and log administrative access to runner hosts.
CircleCI’s security cautions and runner model are covered in the runner concepts documentation and the installation guide.
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Inventory, observability, and troubleshooting
Use the runner API to reconcile what you intended to provision with what CircleCI can see. The list response can include hostname, runner name, resource class, connection timestamps, last-use timestamp, and runner version. Those fields help distinguish a host that never connected from one that connected but stopped claiming tasks.
Jobs remain unclaimed
- Confirm the job’s
resource_classexactly matches the registered namespace and class. - Check that the class has registered runners and that they are connected.
- Query unclaimed tasks for that class rather than a different pool.
- Inspect organization concurrency; the queue may exceed the number of jobs the plan permits to run.
- Verify that hosts can reach the correct Cloud or Server runner API endpoint.
A host registers but does not receive work
- Compare its configured class token and runner name with the intended class.
- Check the host’s last-use and connection timestamps in inventory.
- Confirm that project authorization permits the job to target the class.
- Look for a class mismatch caused by a copied configuration file or an outdated image.
Capacity grows without reducing the queue
- Ensure the controller queries each class separately; demand in one class cannot be satisfied by another.
- Check whether hosts are still booting, waiting for KubeVirt scheduling, or blocked by missing
/dev/kvm. - Compare desired, registered, running, and unclaimed counts to find where the pipeline is stalled.
- Apply a provisioning cooldown so slow registration does not trigger repeated scale-up batches.
Continuous hosts become stale or unsafe
- Verify idle-timeout and controller scale-down behavior.
- Inspect cleanup logs for workspaces, credentials, Docker layers, and generated files.
- Retire hosts that drift from the approved runner version or image rather than trying to repair indefinite drift in place.
Operational checklist
- Namespace exists and is associated with the correct organization.
- Every class has a documented purpose, owner, maximum capacity, and trust level.
- Tokens are stored outside source control and delivered only at runner startup.
- Each host has a unique name, dedicated working directory, cleanup policy, and supported runner version.
- Jobs use the exact fully qualified class name.
- Scaling logic reads unclaimed and running tasks per class and enforces the organization concurrency ceiling.
- Ephemeral and persistent lifecycle behavior is explicit, tested, and observable.
- Cloud and Server API addresses are not conflated.
- Orchestrator nodes expose
/dev/kvm, and Kubernetes capacity is monitored separately from runner count. - Inventory, queue age, registration failures, idle hosts, runner versions, and provisioning errors generate alerts.
Which approach should you use?
Use manually managed hosts when your team already has reliable VM or bare-metal provisioning and wants direct control over images, networks, and retirement. Choose single-task hosts when isolation and clean teardown matter more than startup latency. Choose continuous hosts for predictable, sustained workloads only when you can enforce cleanup, patching, authorization, and idle scale-down.
Use Machine Runner Orchestrator when Kubernetes and KubeVirt are already an operational strength and you want resource classes represented in one deployment. It adds those platform prerequisites and does not remove the need to scale the Kubernetes nodes underneath the runner VMs. In every model, the durable design is the same: explicit resource-class boundaries, secret-safe registration, class-specific demand signals, and a controller that respects the organization concurrency limit.
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