# ModelDeployment Source: /reference/modeldeployments/ Deploy a model to the fleet, from one pod to disaggregated prefill and decode. Apply instances as `apiVersion: modelplane.ai/v1alpha1`, `kind: ModelDeployment`. [Concept guide: Deploy a Model](/models/model-deployment/index.md) ## Example ```yaml apiVersion: modelplane.ai/v1alpha1 kind: ModelDeployment metadata: name: qwen3-8b namespace: ml-team spec: replicas: 2 template: spec: engines: - name: qwen3-8b members: - role: Standalone nodeSelector: devices: - name: gpu count: 1 selectors: - cel: | device.capacity["gpu.nvidia.com"].memory.compareTo(quantity("20Gi")) >= 0 template: spec: containers: - name: engine image: vllm/vllm-openai:v0.23.0 args: - --model=Qwen/Qwen3-8B - --served-model-name=$(MODELPLANE_SERVED_MODEL_NAME) ``` ## Definition The CompositeResourceDefinition this reference is generated from, with the complete OpenAPI schema, validation rules, and defaults: ```yaml apiVersion: apiextensions.crossplane.io/v2 kind: CompositeResourceDefinition metadata: name: modeldeployments.modelplane.ai spec: group: modelplane.ai names: categories: [crossplane, modelplane, models] kind: ModelDeployment plural: modeldeployments shortNames: [md] scope: Namespaced versions: - name: v1alpha1 served: true referenceable: true additionalPrinterColumns: - name: REPLICAS type: string jsonPath: .status.replicas.ready # Serve a scale subresource so `kubectl scale` and event-driven autoscalers # (e.g. KEDA) can drive spec.replicas, the deployment's single scaling axis. # statusReplicasPath points at the count of scheduled replicas, mirroring how # Deployment, LeaderWorkerSet, and PodCliqueSet report status.replicas as the observed total # and keep readiness separate. No labelSelectorPath: replica pods run on # remote workload clusters, not alongside this XR, so metric-based HPA can't # observe them; scaling is by kubectl or external metrics. subresources: scale: specReplicasPath: .spec.replicas statusReplicasPath: .status.replicas.total schema: openAPIV3Schema: type: object required: [spec] properties: spec: type: object required: [replicas, template] properties: replicas: type: integer minimum: 0 maximum: 100 description: >- How many ModelReplicas to fan out to. Each replica is a complete serving instance scheduled to one InferenceCluster. 0 parks the deployment: its replicas and endpoints are removed but the object and its spec remain, and conditions report NoReplicasDesired. template: type: object required: [spec] description: >- Template for the ModelReplicas this deployment fans out to. Everything but the replica count lives here, mirroring a Kubernetes Deployment's spec.template. properties: metadata: type: object # Reject malformed labels on the ModelDeployment itself, # rather than letting them fail when the composed ModelReplica # and ModelEndpoint are applied (a child error the user can't # trace back to their input). These mirror Kubernetes label # syntax: an optional DNS-subdomain prefix plus a name of up # to 63 chars, a value of up to 63 chars, both from # [A-Za-z0-9._-] and edged by alphanumerics. x-kubernetes-validations: - rule: "!has(self.labels) || self.labels.all(k, !k.startsWith('modelplane.ai/'))" message: "template.metadata.labels keys must not use the reserved modelplane.ai/ prefix" - rule: "!has(self.labels) || self.labels.all(k, k.matches('^([a-z0-9]([-a-z0-9]*[a-z0-9])?(\\\\.[a-z0-9]([-a-z0-9]*[a-z0-9])?)*/)?[A-Za-z0-9]([-A-Za-z0-9_.]{0,61}[A-Za-z0-9])?$'))" message: "template.metadata.labels keys must be valid Kubernetes label keys" - rule: "!has(self.labels) || self.labels.all(k, k.split('/')[0].size() <= 253)" message: "template.metadata.labels key prefixes must be DNS subdomains of at most 253 characters" - rule: "!has(self.labels) || self.labels.all(k, self.labels[k].matches('^(([A-Za-z0-9][-A-Za-z0-9_.]*)?[A-Za-z0-9])?$'))" message: "template.metadata.labels values must be valid Kubernetes label values" properties: labels: type: object description: >- Labels to set on the ModelReplicas and ModelEndpoints this deployment composes, alongside the labels Modelplane manages. Use them to organize and select your own resources (kubectl get modelreplica -l tier=prod) or to route to a subset of endpoints from a ModelService. Keys under the modelplane.ai/ prefix are reserved. maxProperties: 32 additionalProperties: type: string maxLength: 63 spec: type: object required: [engines] # PrefillDecode serving runs one Prefill and one Decode # engine, each marking its phase. Validate the pairing here, # where both serving and the engine list are visible. serving # is optional and defaults to Unified, under which no engine # may carry a phase. x-kubernetes-validations: - rule: "!has(self.serving) || self.serving.mode != 'PrefillDecode' || size(self.engines) == 2" message: "PrefillDecode serving requires exactly two engines (one Prefill, one Decode)" - rule: "!has(self.serving) || self.serving.mode != 'PrefillDecode' || self.engines.exists_one(e, has(e.phase) && e.phase == 'Prefill')" message: "PrefillDecode serving requires exactly one engine with phase Prefill" - rule: "!has(self.serving) || self.serving.mode != 'PrefillDecode' || self.engines.exists_one(e, has(e.phase) && e.phase == 'Decode')" message: "PrefillDecode serving requires exactly one engine with phase Decode" - rule: "(has(self.serving) && self.serving.mode == 'PrefillDecode') || !self.engines.exists(e, has(e.phase))" message: "engine phase may only be set when serving.mode is PrefillDecode" properties: clusterSelector: type: object description: >- Optional label selector to filter InferenceClusters. If omitted, all ready clusters are candidates. properties: matchLabels: type: object additionalProperties: type: string modelCacheRef: type: object required: [name] description: >- Reference to a ModelCache in the same namespace. Optional for single-node engines; required for any engine that spans multiple nodes (a Leader with one or more Workers), since every pod in the gang mounts it. properties: name: type: string description: ModelCache resource name in the same namespace. minLength: 1 serving: type: object x-kubernetes-validations: - rule: "!has(self.endpointPicker) || (has(self.router) && self.router == 'EndpointPicker')" message: "serving.endpointPicker may only be set when serving.router is EndpointPicker" - rule: "!has(self.router) || has(self.endpointPicker)" message: "serving.router EndpointPicker requires serving.endpointPicker with its template" - rule: "self.mode != 'PrefillDecode' || (has(self.router) && self.router == 'EndpointPicker')" message: "PrefillDecode serving requires serving.router EndpointPicker and serving.endpointPicker" description: >- How the deployment is served from the cluster edge to its engines. Modelplane fronts the serving pods with an InferencePool and an endpoint picker in both modes. Unified (the default) serves prefill and decode on each engine. PrefillDecode serves them from the two engines marking those phases, with routing that sequences prefill then decode. Omitted means Unified. required: [mode] properties: mode: type: string enum: [Unified, PrefillDecode] default: Unified description: >- Unified serves prefill and decode on one engine. PrefillDecode splits them across two engines, each marking its phase as Prefill or Decode. router: type: string enum: [EndpointPicker] description: >- The router the user writes. Required under PrefillDecode. Omitted, under Unified, Modelplane routes the deployment with its default picker configuration. EndpointPicker runs the endpoint picker set in endpointPicker, and the user writes any sidecar the picker needs as a container in the member templates. endpointPicker: type: object description: >- The endpoint picker Modelplane runs in front of the serving pods. Required exactly when router is EndpointPicker. Modelplane composes the picker's InferencePool, Service and RBAC around it. required: [template] properties: template: type: object description: >- Pod template for the picker. A curated subset of PodTemplateSpec, like a member's. The user writes the picker's command line, since each picker spells it differently. required: [spec] properties: spec: type: object required: [containers] properties: containers: type: array minItems: 1 maxItems: 1 x-kubernetes-list-type: map x-kubernetes-list-map-keys: [name] description: >- The picker container, named "epp". Modelplane sets MODELPLANE_POOL_NAME, MODELPLANE_POOL_NAMESPACE and, when config is set, MODELPLANE_PICKER_CONFIG in its environment, for its args to pass on as $(MODELPLANE_POOL_NAME). The picker serves the gateway's gRPC on 9002, gRPC health on 9003 and Prometheus metrics on 9090. Modelplane declares those ports, and probes readiness on 9003. x-kubernetes-validations: - rule: "self.all(c, c.name == 'epp')" message: "the endpoint picker's container must be named 'epp'" items: type: object required: [name, image] properties: name: type: string minLength: 1 maxLength: 63 image: type: string minLength: 1 command: type: array items: type: string args: type: array items: type: string env: type: array items: type: object required: [name] properties: name: type: string value: type: string valueFrom: type: object properties: secretKeyRef: type: object required: [name, key] properties: name: type: string key: type: string optional: type: boolean configMapKeyRef: type: object required: [name, key] properties: name: type: string key: type: string optional: type: boolean fieldRef: type: object required: [fieldPath] properties: fieldPath: type: string apiVersion: type: string resources: type: object x-kubernetes-validations: - rule: "(!has(self.requests) || self.requests.all(k, k in ['cpu', 'memory', 'ephemeral-storage'])) && (!has(self.limits) || self.limits.all(k, k in ['cpu', 'memory', 'ephemeral-storage']))" message: "resources take only cpu, memory and ephemeral-storage; a member gets devices from its node pool's device requests" properties: requests: type: object maxProperties: 3 additionalProperties: anyOf: [{type: integer}, {type: string}] x-kubernetes-int-or-string: true limits: type: object maxProperties: 3 additionalProperties: anyOf: [{type: integer}, {type: string}] x-kubernetes-int-or-string: true imagePullSecrets: type: array items: type: object required: [name] properties: name: type: string config: type: object x-kubernetes-preserve-unknown-fields: true minProperties: 1 description: >- The picker's configuration, such as an llm-d EndpointPickerConfig. Modelplane mounts it at $(MODELPLANE_PICKER_CONFIG) without reading it. Omitted for a picker that takes no configuration. tolerations: type: array description: >- Tolerations that let this deployment's replicas schedule onto, and stay on, InferenceClusters carrying matching taints, following the Kubernetes toleration model. A replica tolerating a cluster's NoSchedule taint can be placed there; one tolerating a NoExecute taint is not drained when that taint is applied. x-kubernetes-list-type: atomic items: type: object x-kubernetes-validations: - rule: "self.operator != 'Equal' || (has(self.key) && self.key != '')" message: "an Equal toleration must set a key" - rule: "self.operator != 'Exists' || !has(self.value)" message: "an Exists toleration must not set a value" properties: key: type: string description: >- Taint key to match. Empty with operator Exists tolerates every taint. operator: type: string enum: [Exists, Equal] default: Equal description: >- Exists matches any taint with the key (ignoring value); Equal matches key and value. value: type: string effect: type: string enum: [NoSchedule, NoExecute] description: >- Taint effect to match. Empty matches all effects. engines: type: array description: >- A ModelReplica's inference engines. An engine is one serving unit: a single Standalone pod, or a gang of a Leader and one or more Workers coordinating across nodes. Modelplane composes the whole array once per ModelReplica; an engine composes to a Deployment (Standalone) or, for a Leader/Worker gang, a LeaderWorkerSet or a Grove PodCliqueSet depending on the cluster's stack, but the workload kind is an implementation detail. Modelplane is unopinionated about the engine itself: parallelism, quantization, and KV transfer all live in the members' engine flags, written by the user, never injected by Modelplane. minItems: 1 maxItems: 8 x-kubernetes-list-type: map x-kubernetes-list-map-keys: [name] items: type: object required: [name, members] # An engine is exactly one Standalone member, or one Leader # and one or more Workers. No other combination of roles # forms a valid serving unit. x-kubernetes-validations: - rule: >- (self.members.size() == 1 && self.members[0].role == 'Standalone') || (self.members.exists_one(m, m.role == 'Leader') && self.members.exists(m, m.role == 'Worker') && !self.members.exists(m, m.role == 'Standalone')) message: >- an engine must be either a single Standalone member or one Leader and one or more Workers # nodeSelector is the only path to a GPU, so an engine where # no member carries one would deploy with no devices at all - # a mistake, not a deployment. A member may omit its own # selector (a coordinator-only leader claims nothing), but # some member must claim. - rule: "self.members.exists(m, has(m.nodeSelector))" message: >- at least one member of an engine must carry a nodeSelector requesting devices properties: name: type: string description: >- Identifies the engine within the deployment. Becomes part of the composed workload names, so it must be a DNS label. minLength: 1 maxLength: 63 copies: type: integer description: >- How many identical copies of this engine to run per ModelReplica. A fixed number, sized once per deployment; scaling happens by adding ModelReplicas (spec.replicas), never by varying copies. Maps to the composed Deployment's or LeaderWorkerSet's replica count, or a Grove PodCliqueSet's podCliqueScalingGroups[].replicas (its spec.replicas stays 1). Defaults to 1. default: 1 minimum: 1 maximum: 64 phase: type: string enum: [Prefill, Decode] description: >- The engine's phase in a PrefillDecode deployment, Prefill or Decode. Set only when serving.mode is PrefillDecode, where exactly one engine takes each phase. members: type: array description: >- The engine's pods. Either a single Standalone member, or one Leader and one or more Workers. minItems: 1 maxItems: 2 x-kubernetes-list-type: atomic items: type: object required: [template] # worker is meaningful only for a Worker member: a # Standalone and a Leader are always exactly one pod on # one node. x-kubernetes-validations: - rule: "!has(self.worker) || self.role == 'Worker'" message: "worker may only be set on a Worker member" # The ports of a serving pod: a Standalone member or a Leader. A Worker # doesn't serve, so these skip it. Keep in sync with apis/modelreplicas/definition.yaml. # - At most one container declares 8000, where requests arrive. # - If a container beside the engine declares 8000, the engine declares # its http port elsewhere, and if the engine's http port is elsewhere, # a container beside it declares 8000. # - The engine may name port 8000 only http. - rule: "(has(self.role) && self.role == 'Worker') || !has(self.template.spec) || self.template.spec.containers.filter(c, has(c.ports) && c.ports.exists(p, p.containerPort == 8000)).size() <= 1" message: "at most one container in a serving pod may declare containerPort 8000" - rule: "(has(self.role) && self.role == 'Worker') || !has(self.template.spec) || !self.template.spec.containers.exists(c, c.name != 'engine' && has(c.ports) && c.ports.exists(p, p.containerPort == 8000)) || self.template.spec.containers.exists(c, c.name == 'engine' && has(c.ports) && c.ports.exists(p, has(p.name) && p.name == 'http' && p.containerPort != 8000))" message: "when another container declares containerPort 8000, the engine container must declare its 'http' port on a different port" - rule: "(has(self.role) && self.role == 'Worker') || !has(self.template.spec) || !self.template.spec.containers.exists(c, c.name == 'engine' && has(c.ports) && c.ports.exists(p, has(p.name) && p.name == 'http' && p.containerPort != 8000)) || self.template.spec.containers.exists(c, c.name != 'engine' && has(c.ports) && c.ports.exists(p, p.containerPort == 8000))" message: "when the engine container's 'http' port isn't 8000, another container in its pod must declare containerPort 8000" - rule: "(has(self.role) && self.role == 'Worker') || !has(self.template.spec) || !self.template.spec.containers.exists(c, c.name == 'engine' && has(c.ports) && c.ports.exists(p, p.containerPort == 8000 && has(p.name) && p.name != 'http'))" message: "the engine container may name containerPort 8000 only 'http'" properties: role: type: string description: >- The member's role in the engine. Standalone is a lone pod; a Leader coordinates and serves while its Workers join it. Defaults to Standalone. enum: [Standalone, Leader, Worker] default: Standalone nodeSelector: type: object description: >- The per-node device request for this member's pods: what devices each pod needs from its node. The scheduler matches it against a candidate pool's InferenceClass devices (surfaced on InferenceCluster status.gpuPools) and places the member on a pool that satisfies it, preferring one pool for the whole engine and splitting members across pools only when no pool satisfies them all. claim: DRA requests also become DeviceRequests in the ResourceClaim the member's pods bind GPUs through. A GPU request's count is the GPUs per node. Omitted, the member claims no devices and schedules onto its engine's pool - a coordinator-only leader. At least one member per engine must carry a nodeSelector, and at least one member's requests must resolve to a claimable (claim: DRA) device; an engine that matches only synthetic devices leaves its pods nothing to claim, so the scheduler treats such a pool as ineligible and the deployment reports InsufficientCapacity. required: [devices] properties: devices: type: array description: >- Device requests. A pool matches a request when it has a device whose count covers the request and whose driver, attributes, and capacity satisfy every selector. minItems: 1 maxItems: 16 x-kubernetes-list-type: map x-kubernetes-list-map-keys: [name] items: type: object required: [name, selectors] properties: name: type: string description: >- Name of this request. Mirrors a DRA DeviceRequest name; carried through to the ResourceClaim. minLength: 1 maxLength: 63 count: type: integer description: >- How many matching devices a node must have. For a GPU request this is the per-node GPU count. default: 1 minimum: 1 maximum: 64 selectors: type: array description: >- Selectors a device must satisfy, all ANDed. Each is a one-of; today only cel is supported. minItems: 1 maxItems: 8 x-kubernetes-list-type: atomic items: type: object # A selector must carry at least one # selector kind (today only cel). Without # this an empty {} selector would match # every device, and since nodeSelector is # the only path to a GPU that silently # claims an arbitrary one. minProperties: 1 properties: cel: type: string description: >- A DRA CEL expression evaluated against one device. Reads device.driver, device.attributes[""]. (typed), and device.capacity[""]. (a Quantity), with quantity() and semver() helpers, e.g. device.capacity["gpu.nvidia.com"].memory.compareTo(quantity("141Gi")) >= 0. minLength: 1 maxLength: 10240 # This object has no schema default on purpose: the # apiserver applies defaults before CEL validation, so # defaulting it would inject it onto Standalone and # Leader members and trip the rule that forbids it # there. worker: type: object description: >- Settings for a Worker member. Valid only on a member whose role is Worker. required: [nodes] properties: nodes: type: integer description: >- How many nodes this member spans - how big the engine is. Each node runs one worker pod, so the engine's gang spans 1 (the Leader) plus this many worker pods. Defaults to 1. minimum: 1 maximum: 63 template: type: object description: >- Pod template for this member's engine pods. A curated subset of PodTemplateSpec. properties: metadata: type: object description: >- Metadata applied to the member's pods. Useful for labels and annotations that control cluster-level features like service mesh injection. Label keys under the modelplane.ai/ prefix are reserved. # Mirrors the template.metadata label rules # above: reject reserved and malformed labels # (and malformed annotation keys, validated as # qualified names just like label keys) # at admission rather than composing a pod # template the workload cluster rejects (or, # for the reserved prefix, silently dropping # the label - the modelplane.ai/ labels drive # the serving Service and workload selectors, # so a user value can't be honored). x-kubernetes-validations: - rule: "!has(self.labels) || self.labels.all(k, !k.startsWith('modelplane.ai/'))" message: "member template.metadata.labels keys must not use the reserved modelplane.ai/ prefix" - rule: "!has(self.labels) || self.labels.all(k, k.matches('^([a-z0-9]([-a-z0-9]*[a-z0-9])?(\\\\.[a-z0-9]([-a-z0-9]*[a-z0-9])?)*/)?[A-Za-z0-9]([-A-Za-z0-9_.]{0,61}[A-Za-z0-9])?$'))" message: "member template.metadata.labels keys must be valid Kubernetes label keys" - rule: "!has(self.labels) || self.labels.all(k, k.split('/')[0].size() <= 253)" message: "member template.metadata.labels key prefixes must be DNS subdomains of at most 253 characters" - rule: "!has(self.labels) || self.labels.all(k, self.labels[k].matches('^(([A-Za-z0-9][-A-Za-z0-9_.]*)?[A-Za-z0-9])?$'))" message: "member template.metadata.labels values must be valid Kubernetes label values" - rule: "!has(self.annotations) || self.annotations.all(k, k.matches('^([a-z0-9]([-a-z0-9]*[a-z0-9])?(\\\\.[a-z0-9]([-a-z0-9]*[a-z0-9])?)*/)?[A-Za-z0-9]([-A-Za-z0-9_.]{0,61}[A-Za-z0-9])?$'))" message: "member template.metadata.annotations keys must be valid Kubernetes annotation keys" - rule: "!has(self.annotations) || self.annotations.all(k, k.split('/')[0].size() <= 253)" message: "member template.metadata.annotations key prefixes must be DNS subdomains of at most 253 characters" properties: labels: type: object maxProperties: 32 additionalProperties: type: string maxLength: 63 annotations: type: object maxProperties: 32 additionalProperties: type: string maxLength: 8192 spec: type: object required: [containers] description: >- Pod spec for this member's engine pods. properties: containers: type: array minItems: 1 maxItems: 8 x-kubernetes-list-type: map x-kubernetes-list-map-keys: [name] description: >- Containers for the engine pod. Exactly one is named "engine", the inference engine. The others run beside it, such as a routing sidecar. Modelplane adds device claims, MODELPLANE_ environment, ModelCache mounts, /dev/shm and the readiness probe to the engine container only. x-kubernetes-validations: - rule: "self.exists_one(c, c.name == 'engine')" message: "exactly one container must be named 'engine'" - rule: "!self.exists(c, c.name == 'engine' && has(c.readinessProbe))" message: "the engine container can't set readinessProbe; Modelplane probes it on its http port" items: type: object required: [name, image] properties: name: type: string minLength: 1 maxLength: 63 pattern: '^[a-z0-9]([-a-z0-9]*[a-z0-9])?$' description: >- Container name. The container named "engine" is the inference engine. image: type: string minLength: 1 description: Container image. command: type: array description: >- Container entrypoint override, passed through verbatim. For a Leader or Worker, the command owns cross-node coordination: it addresses the leader through $(MODELPLANE_LEADER_ADDRESS), which Modelplane injects into every engine container on either stack. The pod's rank (0 for the Leader, 1..worker.nodes for followers) comes from $(MODELPLANE_RANK) on a Standard cluster; on Dynamo the command derives it from Grove's GROVE_PCLQ_POD_INDEX, since Grove exposes no group-wide pod index yet. items: type: string args: type: array description: >- Container args, passed through to the serving engine. Includes the model identifier (e.g. --model=...) and any parallelism flags. Pass --served-model-name $(MODELPLANE_SERVED_MODEL_NAME), the variable Modelplane injects, so the engine answers to the name a gateway routes to. An engine started under a literal name may return a 404 for every request. items: type: string env: type: array description: >- Environment variables. Supports valueFrom.secretKeyRef / configMapKeyRef for secrets and config (like HF_TOKEN), and valueFrom.fieldRef for pod fields (e.g. status.podIP for vLLM's VLLM_HOST_IP on multi-NIC nodes). items: type: object required: [name] properties: name: type: string value: type: string valueFrom: type: object properties: secretKeyRef: type: object required: [name, key] properties: name: type: string key: type: string optional: type: boolean configMapKeyRef: type: object required: [name, key] properties: name: type: string key: type: string optional: type: boolean fieldRef: type: object description: >- Reference a pod field via the downward API, e.g. status.podIP, metadata.name, or metadata.namespace. required: [fieldPath] properties: fieldPath: type: string apiVersion: type: string resources: type: object description: >- CPU and memory requests and limits. On the engine container, Modelplane adds the member's device claim beside them. x-kubernetes-validations: - rule: "(!has(self.requests) || self.requests.all(k, k in ['cpu', 'memory', 'ephemeral-storage'])) && (!has(self.limits) || self.limits.all(k, k in ['cpu', 'memory', 'ephemeral-storage']))" message: "resources take only cpu, memory and ephemeral-storage; a member gets devices from its node pool's device requests" properties: requests: type: object maxProperties: 3 additionalProperties: anyOf: [{type: integer}, {type: string}] x-kubernetes-int-or-string: true limits: type: object maxProperties: 3 additionalProperties: anyOf: [{type: integer}, {type: string}] x-kubernetes-int-or-string: true readinessProbe: type: object description: >- How Kubernetes checks that a container beside the engine is ready, such as a sidecar on port 8000. The engine container can't set one: Modelplane probes the engine on its http port. x-kubernetes-validations: - rule: "[has(self.httpGet), has(self.tcpSocket), has(self.grpc)].filter(h, h).size() == 1" message: "readinessProbe sets exactly one of httpGet, tcpSocket and grpc" properties: httpGet: type: object required: [port] properties: path: type: string port: anyOf: [{type: integer}, {type: string}] x-kubernetes-int-or-string: true tcpSocket: type: object required: [port] properties: port: anyOf: [{type: integer}, {type: string}] x-kubernetes-int-or-string: true grpc: type: object required: [port] properties: port: type: integer service: type: string initialDelaySeconds: type: integer minimum: 0 periodSeconds: type: integer minimum: 1 timeoutSeconds: type: integer minimum: 1 successThreshold: type: integer minimum: 1 failureThreshold: type: integer minimum: 1 ports: type: array maxItems: 8 x-kubernetes-list-type: map x-kubernetes-list-map-keys: [containerPort] x-kubernetes-validations: - rule: "self.all(p, !has(p.name) || self.exists_one(q, has(q.name) && q.name == p.name))" message: "port names must be unique within a container" description: >- Ports the container listens on. The engine container's port named "http" is where Modelplane probes the engine and scrapes its metrics. Without one, the engine serves on 8000, and an unnamed port 8000 is its "http" port. A container in front of the engine declares 8000, and the engine then declares its "http" port elsewhere. A Worker's ports pass through as written. items: type: object required: [containerPort] properties: name: type: string minLength: 1 maxLength: 15 pattern: '^[a-z0-9]([-a-z0-9]*[a-z0-9])?$' description: >- Port name. The engine container's port named "http" is where Modelplane probes the engine and scrapes its metrics. containerPort: type: integer minimum: 1 maximum: 65535 description: Port number the container listens on. imagePullSecrets: type: array description: >- Image pull secrets for private registries (NGC etc.). items: type: object required: [name] properties: name: type: string status: type: object properties: replicas: type: object properties: total: type: integer ready: type: integer ```