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CircleCI Machine Runner Orchestrator turns a Kubernetes cluster with KubeVirt into an elastic fleet of self-hosted runner virtual machines. You create a CircleCI resource class and one-time token, install the orchestrator Helm chart, map that class to a KubeVirt VirtualMachinePool, and target the class from jobs with machine: true. The controller polls demand about every five seconds and adjusts the pool between your configured replica limits.
This guide covers the prerequisites, installation, job configuration, scaling controls, security model, troubleshooting, and upgrade concerns documented for the current 1.0.0 chart. Start with the infrastructure checks: the chart does not install Kubernetes or KubeVirt.
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What the orchestrator does
The Machine Runner Orchestrator is a Kubernetes controller for CircleCI machine runners. It watches task demand for configured CircleCI resource classes and reconciles a KubeVirt VirtualMachinePool. Each VM boots a CircleCI runner, claims work for its resource class, runs the job, and can terminate after becoming idle. This gives a self-hosted fleet the elasticity of a hosted runner pool while keeping compute, network access, images, and credentials under your control.
The deployment is made of four parts:
- CircleCI resource class: the
namespace/nameidentity that jobs request and that the runner token authorizes. - Orchestrator deployment: the Helm-installed controller that polls CircleCI and changes pool size.
- KubeVirt pool: the virtual machines that provide the actual execution capacity.
- Runner job configuration: a CircleCI job using
machine: trueand the exact configured resource class.
The controller and VM lifecycle are separate from CircleCI’s hosted machine images. A self-hosted job does not select a hosted machine.image alias; it selects your resource class instead.
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Read the Machine runner orchestrator documentation alongside your installation. It contains the compatibility matrix and the chart’s authoritative values for the release you deploy.
Prerequisites and capacity planning
Kubernetes and KubeVirt
Provide a Kubernetes cluster with KubeVirt already installed and working before you install the chart. The orchestrator does not install KubeVirt. The guide identifies KubeVirt v1.8 as its tested version; verify the compatibility matrix rather than assuming a newer or older release is supported. Your cluster must be able to schedule the maximum number of runner VMs implied by every pool’s maxReplicas.
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Runner VM defaults
The default runner VM is based on Ubuntu 24.04 with 2 GiB of memory and one CPU. The default container disk is maintained by CircleCI and includes Docker and common CI tools. If your builds need more CPU, memory, storage, a different image, or additional disks, set class-specific KubeVirt spec values or shared resourceClassDefaults. Size the Kubernetes nodes for the resulting VM requests, including the warm minimum and any surge capacity.
Administrative access and secrets
- Kubernetes administrator access sufficient to create a namespace, install a Helm release, and inspect Deployments, pods, and KubeVirt resources.
- An organization administrator in CircleCI who can create a runner resource class and view its token once.
- A secret-management process for runner tokens, CircleCI Server credentials (if applicable), and any cloud-init data. Do not commit tokens to a repository or paste them into ordinary, broadly readable configuration.
- Outbound network connectivity from the orchestrator and each runner VM to the appropriate CircleCI endpoint, plus access to source control, registries, artifact stores, and other services your jobs require.
Step 1: Create the CircleCI namespace and resource class
Resource classes are keyed as namespace/name. An organization generally has one namespace; an existing namespace may have been created for orb use and can normally be reused. Namespace names accept lowercase letters, numbers, underscores, and dashes. Resource-class names additionally accept uppercase letters, colons, and plus signs.
Use the CircleCI interface
- Sign in as an organization administrator and open the Runners area.
- Create or select the organization namespace.
- Create a custom resource class, such as
acme/linux-small, and record its exact spelling. - Generate the runner token and store it immediately in your secret manager. The guide warns that the token is displayed only once.
Use the CLI
The documented command creates a class and generates its token:
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circleci runner resource-class create <namespace>/<resource-class> <description> --generate-tokenReplace the angle-bracketed values with your real namespace, class name, and description when you run it. Treat the output as a credential: anyone who obtains the token can attempt to claim work for that class.
Step 2: Prepare Helm values
Create a dedicated Kubernetes namespace and a values file. A minimal class entry belongs under provisioner.resourceClasses. The following example illustrates one small pool and keeps the token as an environment-substituted value rather than a literal credential:
provisioner:
resourceClasses:
acme/linux-small:
token: "${CIRCLECI_RUNNER_TOKEN}"
scaling:
minReplicas: 1
maxReplicas: 6
headroom: 1
maxSurge: 2
scaleDownDelay: 300s
idleTimeout: 900s
resourceClassDefaults:
# Put settings shared by several classes here.
# A class-specific value overrides an inherited value.The exact secret and values mechanisms supported by your chart version should be followed for production. The chart supports pre-existing Kubernetes Secrets and ConfigMaps, allowing you to keep tokens and user data outside a general values file. If you use shell or CI substitution as in the example, render the final values without printing them to logs.
Per-class configuration can include the runner token, optional cloud-init userData, scaling settings, runner execution settings, extra disk mounts, and a KubeVirt VM spec. Put common settings in resourceClassDefaults and override only what differs between classes.
Step 3: Install the chart
The current guide documents chart version 1.0.0 in the CircleCI Helm repository. Pin the version in automation and review the release notes before changing it; configuration names and defaults may change before a release reaches general availability.
helm repo add circleci https://packagecloud.io/circleci/machine-runner-orchestrator/helm
helm repo update
helm upgrade --install machine-runner-orchestrator
circleci/machine-runner-orchestrator
--version 1.0.0
--namespace circleci-runners
--create-namespace
--values values.yamlUse your organization’s approved method for supplying the token while running Helm. After installation, verify that the controller is ready and that the expected KubeVirt pool appears:
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kubectl get deployment -n circleci-runners
kubectl get virtualmachinepool -n circleci-runners
kubectl get pods -n circleci-runners
kubectl logs deployment/machine-runner-orchestrator -n circleci-runnersThe provisioner logs should report task counts and reconciliation decisions. A pool may initially contain only its warm minimum; it should grow when an eligible CircleCI job is queued.
CircleCI Server installations
For a self-hosted CircleCI Server instance, set provisioner.circleciAPIAddr to the instance URL. The guide says this address is injected into each VM and that registration fails when it is omitted. Ensure both the orchestrator and every runner VM can resolve and reach that URL. The Server example also uses a CircleCI API token in addition to the resource-class token; store and pass that credential through the chart’s supported secret configuration.
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Step 4: Target the fleet from CircleCI jobs
A job must explicitly select the class that you configured in the Helm release:
version: 2.1
jobs:
build:
machine: true
resource_class: acme/linux-small
steps:
- checkout
- run: echo "Hi from a self-hosted runner"The resource_class value must match the configured namespace/name exactly. Do not add a CircleCI-hosted machine.image alias to this job. If the class is misspelled, absent from the release, or uses a token from another class, the job will remain unclaimed.
Commit the configuration only after confirming that the class is available to the project and that your organization’s security policy permits the project to use self-hosted runners.
How scaling decisions work
The scaler polls CircleCI approximately every five seconds. For each configured class, it considers unclaimed tasks and running tasks, adds headroom when tasks exist, clamps the result between the configured minimum and maximum, and applies maxSurge to limit how many new VMs can be requested above the ready capacity.
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| Setting | Effect | Operational implication |
|---|---|---|
minReplicas |
Warm floor for the pool. | Use a positive value to reduce cold-start latency; use 0 to allow scale-to-zero while idle. |
maxReplicas |
Upper bound on pool size. | Reserve enough Kubernetes capacity and keep it consistent with CircleCI plan concurrency. |
headroom |
Extra warm VMs above current task demand when tasks exist. | Improves burst response at the cost of idle compute. |
maxSurge |
Limits launches above VMs already ready. | Prevents a large queue from creating an uncontrolled burst; a low value ramps in waves. |
scaleDownDelay |
Waits after demand falls before reducing the pool. | Absorbs short gaps between jobs and avoids churn. |
idleTimeout |
Allows an idle VM to shut itself down after the configured period. | Controls how quickly individual VMs release capacity. Without it, an idle VM waits indefinitely. |
Scale-in does not forcibly stop a VM in the middle of a job. The pool shrinks as VMs finish their task or self-terminate after the idle timeout. Set the timeout and delay together: a long delay preserves warm capacity, while a short timeout reduces idle usage but can increase boot activity.
Do not set a maximum that your CircleCI plan cannot use. CircleCI’s scaling guidance warns against starting compute that is unavailable to jobs because of plan concurrency limits. Conversely, a maximum below your normal parallelism will leave tasks queued even when Kubernetes has spare capacity.
Choosing one pool or several
A single Helm deployment can serve multiple resource classes. The 1.0.0 release adds multi-class support for CPU, GPU, and ARM workloads, as well as support for GKE, AKS, EKS, and other KubeVirt-based Kubernetes clusters. Use separate classes when workloads need materially different VM shapes, operating-system images, architectures, disks, or trust boundaries.
provisioner:
resourceClasses:
acme/linux-small:
token: "${SMALL_TOKEN}"
scaling:
minReplicas: 1
maxReplicas: 8
acme/linux-large:
token: "${LARGE_TOKEN}"
scaling:
minReplicas: 0
maxReplicas: 4
spec:
# Supply the KubeVirt VM settings required by your chart version.
# Example: more CPU, memory, or attached storage.Keep defaults conservative and override them per class. A GPU or ARM class should have its own node placement and VM specification, while a small general-purpose class can inherit the common runner image and cloud-init settings. In CircleCI configuration, route each job to the class whose capacity and isolation it requires.
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Protect tokens and the guest boundary
The chart’s default sidecar proxy supplies the resource-class token only when claiming work, so the token itself does not have to be passed into the guest VM. Disabling that sidecar hands the token to the VM and removes support for grantSudo and SSH. Keep the sidecar enabled unless you have a documented reason to accept that exposure.
Use Kubernetes Secrets or your organization’s secret-management integration for resource-class tokens, CircleCI Server credentials, and sensitive cloud-init data. Restrict read access to the controller’s service account and the operators who maintain the fleet. Rotate a token by updating the secret and confirming that newly started runners claim work before retiring the old credential.
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Assume job code is privileged
CircleCI’s self-hosted runner FAQ states: Allowing jobs to access a Docker daemon is equivalent to providing root access to the machine.
Machine runners let the operator choose the job-execution user, but you are responsible for restricting its permissions. Pre-installing dependencies is described as the more secure option; the trade-off is that dependency changes require machine reconfiguration.
Untrusted jobs on persistent self-hosted machines can run malicious programs, attempt to escape the runner sandbox, reach internal services, or leave unwanted data for the next job. Use trusted-project policies, network segmentation, least-privilege identities, short-lived or clean VMs, and controlled persistence. Treat Docker socket access, host mounts, SSH, and grantSudo as deliberate privileged features, not convenience defaults.
Self-hosted runners are unavailable for public projects with the Build forked pull requests setting enabled, for security reasons. Check the project setting before diagnosing an apparently missing runner.
See the self-hosted runner FAQ and runner concepts documentation for the vendor’s security model and responsibility boundaries.
Operating and updating the fleet
Observe three layers
- CircleCI demand: confirm that the job requests the intended class and is waiting rather than being filtered by project or plan policy.
- Controller: inspect provisioner logs for task counts, desired replicas, token errors, and API failures.
- Kubernetes and KubeVirt: inspect the Deployment, pool status, VM objects, events, node capacity, and runner service logs inside the VM.
Scaling configuration and class credentials hot-reload. KubeVirt VM spec values and userData apply at boot, so changing them does not retrofit existing VMs. Recycle old VMs in an orderly way after a change: let active jobs finish, reduce or cordon the pool as appropriate, and verify that newly booted VMs contain the new settings.
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| Symptom | Likely causes | Checks and fixes |
|---|---|---|
| Job remains queued. | Class mismatch, invalid token, class not loaded, or project policy blocks self-hosted runners. | Compare the job’s resource_class character-for-character with the Helm key; inspect controller logs and confirm the class token; review project runner permissions. |
| Pool never grows. | Controller cannot reach CircleCI, maximum already reached, or Kubernetes lacks capacity. | Read provisioner logs for task counts and API errors; check maxReplicas, plan concurrency, node resources, and KubeVirt events. |
| VM starts but never registers. | Unreachable CircleCI endpoint, missing Server API address, bad token, or cloud-init did not run. | From the VM, test DNS and HTTPS reachability to the endpoint; verify provisioner.circleciAPIAddr for Server; inspect the runner service and cloud-init logs. |
| New VM has old settings. | VM spec and userData are boot-time configuration. |
Confirm the release values, then retire and recreate the affected VMs rather than waiting for a hot reload. |
| Idle VMs remain indefinitely. | No idle timeout is configured, or the VM still has a task. | Check task state and set an appropriate idleTimeout; remember that scaleDownDelay also postpones pool reduction. |
Version and upgrade considerations
The 1.0.0 release note records the product rename from runner-provisioner to Machine Runner Orchestrator. Existing deployments must be uninstalled and reinstalled under the new chart name, with runners offline during that transition. Plan a maintenance window, drain or finish active jobs, export the current values, and validate the new Deployment and pools before re-enabling traffic.
The same release note identifies patches for two high-severity gRPC-Go denial-of-service vulnerabilities, CVE-2026-84304 and CVE-2026-84445. Treat those identifiers and the 1.0.0 details as release-specific: review the official release note and current compatibility guidance before applying them to an existing installation.
Installation checklist
- Kubernetes is running, KubeVirt is installed, and the chosen KubeVirt version is in the compatibility guidance.
- Nested virtualization works for the provider and node pool, where required.
- Cluster capacity covers every pool’s minimum, maximum, and surge behavior.
- The organization namespace and resource class exist, and the one-time token is stored securely.
- The Helm chart is pinned and values use the correct
namespace/namekeys. - CircleCI Server users set
provisioner.circleciAPIAddrand provide the required API credential. - The controller,
VirtualMachinePool, VMs, and runner services are healthy. - A test job uses
machine: trueand the exact self-hostedresource_class, without a hostedmachine.imagealias. - Scaling limits, headroom, surge, delay, and idle timeout match both workload latency goals and CircleCI plan concurrency.
- Network access, Docker privileges, persistence, project trust, and secret rotation are documented before production use.
For the general scaling model, including unclaimed-task queries and the distinction between ephemeral single-task machines and continuous agents, consult CircleCI’s self-hosted runner scaling guide.
The Bottom Line
A reliable CircleCI self-hosted fleet starts with a functioning KubeVirt cluster and a securely managed resource class. Install the pinned orchestrator chart, target the class explicitly from jobs, and tune replica and security settings together; otherwise the controller can create capacity that jobs cannot safely or usefully consume.
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