1. 接口描述
接口请求域名： dlc.tencentcloudapi.com 。
获取数据实验室对应的RayCluster YAML内容
默认接口请求频率限制：20次/秒。
推荐使用 API Explorer
点击调试
API Explorer 提供了在线调用、签名验证、SDK 代码生成和快速检索接口等能力。您可查看每次调用的请求内容和返回结果以及自动生成 SDK 调用示例。
2. 输入参数
以下请求参数列表仅列出了接口请求参数和部分公共参数，完整公共参数列表见 公共请求参数。
| 参数名称 | 必选 | 类型 | 描述 |
|---|---|---|---|
| Action | 是 | String | 公共参数，本接口取值：GetLabYaml。 |
| Version | 是 | String | 公共参数，本接口取值：2021-01-25。 |
| Region | 是 | String | 公共参数，详见产品支持的 地域列表，本接口仅支持其中的: ap-beijing, ap-chongqing, ap-guangzhou, ap-shanghai, ap-singapore 。 |
| Id | 是 | String | 数据实验室Id 示例值：raylab-20260530151529-r6av |
3. 输出参数
| 参数名称 | 类型 | 描述 |
|---|---|---|
| Yaml | String | RayCluster YAML 示例值：---apiVersion: "ray.io/ |
| RequestId | String | 唯一请求 ID，由服务端生成，每次请求都会返回（若请求因其他原因未能抵达服务端，则该次请求不会获得 RequestId）。定位问题时需要提供该次请求的 RequestId。 |
4. 示例
示例1 GetLabYaml
获取实验室yaml配置
输入示例
POST / HTTP/1.1
Host: dlc.tencentcloudapi.com
Content-Type: application/json
X-TC-Action: GetLabYaml
<公共请求参数>
{
"Id": "raylab-20260530151529-r6av"
}输出示例
{
"Response": {
"Yaml": "---\napiVersion: \"ray.io/v1\"\nkind: \"RayCluster\"\nmetadata:\n creationTimestamp: \"2026-05-30T07:17:05Z\"\n generation: 2\n labels:\n app.kubernetes.io/instance: \"raylab-20260530151529-r6av\"\n app.kubernetes.io/managed-by: \"neutrino-clustermanager\"\n app.kubernetes.io/name: \"neutrino-cluster\"\n kueue.x-k8s.io/priority-class: \"priority-80000\"\n kueue.x-k8s.io/queue-name: \"dlc-p-bleurqnv-default-lq\"\n neutrino.io/appid: \"260200065\"\n neutrino.io/cluster-type: \"lab\"\n neutrino.io/cluster-uuid: \"raylab-20260530151529-r6av\"\n queueName: \"default\"\n name: \"raylab-20260530151529-r6av\"\n namespace: \"dlc-p-bleurqnv\"\n resourceVersion: \"32588055440\"\n uid: \"b0421e5e-5edf-420b-bec8-383d249644dc\"\nspec:\n autoscalerOptions:\n env: []\n envFrom: []\n idleTimeoutSeconds: 60\n imagePullPolicy: \"IfNotPresent\"\n resources:\n limits:\n cpu: \"1\"\n memory: \"2Gi\"\n requests:\n cpu: \"0\"\n memory: \"0\"\n securityContext: {}\n upscalingMode: \"Default\"\n enableInTreeAutoscaling: false\n headGroupSpec:\n enableIngress: true\n rayStartParams:\n dashboard-host: \"0.0.0.0\"\n disable-usage-stats: \"true\"\n object-store-memory: \"100000000\"\n replicas: 1\n resources:\n cpu: \"0\"\n template:\n metadata:\n annotations:\n kueue.x-k8s.io/workload: \"raycluster-raylab-20260530151529-r6av-9d580\"\n kueue.x-k8s.io/workload-slice-name: \"raycluster-raylab-20260530151529-r6av-9d580\"\n prometheus.io/path: \"/metrics\"\n prometheus.io/port: \"8080\"\n prometheus.io/scheme: \"http\"\n prometheus.io/scrape: \"true\"\n labels:\n dlc/app-id: \"260200065\"\n dlc/engine-id: \"raylab-20260530151529-r6av\"\n dlc/engine-name: \"raylab-20260530151529-r6av\"\n dlc/pay-mode: \"1\"\n dlc/sub-uin: \"700002655693\"\n dlc/task-id: \"raylab-20260530151529-r6av\"\n dlc/task-type: \"RAY_LAB\"\n dlc/uin: \"700002655693\"\n kueue.x-k8s.io/cluster-queue-name: \"dlc-p-bleurqnv-default-cq\"\n kueue.x-k8s.io/local-queue-name: \"dlc-p-bleurqnv-default-lq\"\n kueue.x-k8s.io/podset: \"head\"\n neutrino.io/cluster-uuid: \"raylab-20260530151529-r6av\"\n neutrino.io/node-type: \"head\"\n neutrino.io/ray-log-collector: \"true\"\n neutrino.io/ray-log-metadata-uuid: \"raylab-20260530151529-r6av\"\n pod-role: \"head\"\n spec:\n containers:\n - env:\n - name: \"TZ\"\n value: \"Asia/Shanghai\"\n - name: \"RAY_CLUSTER_UUID\"\n value: \"raylab-20260530151529-r6av\"\n - name: \"RAY_GRAFANA_HOST\"\n value: \"http://grafana.monitor.svc.cluster.local:3000\"\n - name: \"RAY_GRAFANA_IFRAME_HOST\"\n value: \"https://cls-pdb9lgk2.tcray-gateway.ap-guangzhou.cloud.tencent.com/grafana\"\n - name: \"RAY_GRAFANA_CLUSTER_FILTER\"\n valueFrom:\n fieldRef:\n fieldPath: \"metadata.labels['ray.io/cluster']\"\n - name: \"RAY_AUTH_MODE\"\n value: \"token\"\n - name: \"RAY_AUTH_TOKEN\"\n value: \"4a8814e5ff70429e82ac5e2f7f3d0ec6\"\n image: \"ccr.ccs.tencentyun.com/emr-image/tcray:2.55.1-py311-cpu\"\n imagePullPolicy: \"IfNotPresent\"\n name: \"ray-head\"\n ports:\n - containerPort: 6379\n name: \"gcs-server\"\n protocol: \"TCP\"\n - containerPort: 8265\n name: \"dashboard\"\n protocol: \"TCP\"\n - containerPort: 10001\n name: \"client\"\n protocol: \"TCP\"\n resources:\n limits:\n cpu: \"1\"\n memory: \"4Gi\"\n requests:\n cpu: \"0.4\"\n memory: \"1638Mi\"\n securityContext:\n privileged: true\n volumeMounts:\n - mountPath: \"/tmp/ray\"\n name: \"ray-tmp\"\n - args:\n - \"/usr/local/bin/lab/lab-entrypoint.sh\"\n command:\n - \"/bin/bash\"\n - \"-lc\"\n env:\n - name: \"TZ\"\n value: \"Asia/Shanghai\"\n - name: \"RAY_CLUSTER_UUID\"\n value: \"raylab-20260530151529-r6av\"\n - name: \"WORKDIR\"\n value: \"/workspace\"\n - name: \"ENABLE_JUPYTER\"\n value: \"true\"\n - name: \"ENABLE_WEBSHELL\"\n value: \"true\"\n - name: \"ENABLE_VSCODE\"\n value: \"true\"\n - name: \"JUPYTER_TOKEN\"\n value: \"\"\n - name: \"VSCODE_AUTH\"\n value: \"none\"\n - name: \"VSCODE_PASSWORD\"\n value: \"\"\n - name: \"JUPYTER_PORT\"\n value: \"8888\"\n - name: \"WEBSHELL_PORT\"\n value: \"8889\"\n - name: \"VSCODE_PORT\"\n value: \"8890\"\n - name: \"CODE_ARCHIVE_URL\"\n value: \"\"\n - name: \"XDG_DATA_HOME\"\n value: \"/tmp/xdg-data\"\n - name: \"JUPYTER_BASE_URL\"\n value: \"/dlc-p-bleurqnv/raylab-20260530151529-r6av/lab/jupyter\"\n - name: \"MY_POD_IP\"\n valueFrom:\n fieldRef:\n fieldPath: \"status.podIP\"\n - name: \"RAY_NODE_IP_ADDRESS\"\n value: \"$(MY_POD_IP)\"\n - name: \"RAY_AUTH_MODE\"\n value: \"token\"\n - name: \"RAY_AUTH_TOKEN\"\n value: \"4a8814e5ff70429e82ac5e2f7f3d0ec6\"\n image: \"ccr.ccs.tencentyun.com/emr-image/tcray:2.55.1-py311-cpu-lab\"\n imagePullPolicy: \"IfNotPresent\"\n livenessProbe:\n exec:\n command:\n - \"/usr/local/bin/lab/healthcheck.sh\"\n - \"--timeout\"\n - \"5\"\n failureThreshold: 3\n periodSeconds: 30\n timeoutSeconds: 20\n name: \"lab\"\n ports:\n - containerPort: 8888\n name: \"jupyter\"\n protocol: \"TCP\"\n - containerPort: 8889\n name: \"webshell\"\n protocol: \"TCP\"\n - containerPort: 8890\n name: \"vscode\"\n protocol: \"TCP\"\n readinessProbe:\n exec:\n command:\n - \"/usr/local/bin/lab/healthcheck.sh\"\n - \"--timeout\"\n - \"3\"\n failureThreshold: 3\n periodSeconds: 10\n timeoutSeconds: 10\n resources:\n limits:\n cpu: \"2\"\n memory: \"4Gi\"\n requests:\n cpu: \"0\"\n memory: \"0\"\n startupProbe:\n exec:\n command:\n - \"/usr/local/bin/lab/healthcheck.sh\"\n - \"--timeout\"\n - \"5\"\n failureThreshold: 30\n initialDelaySeconds: 10\n periodSeconds: 10\n timeoutSeconds: 20\n volumeMounts:\n - mountPath: \"/tmp/ray\"\n name: \"ray-tmp\"\n - mountPath: \"/workspace\"\n name: \"volume-1\"\n subPath: \"raylab-20260530151529-r6av\"\n nodeSelector:\n instance_type: \"sv_dlc_standard_cu_standard_cu\"\n shareProcessNamespace: true\n volumes:\n - emptyDir: {}\n name: \"ray-tmp\"\n - name: \"volume-1\"\n persistentVolumeClaim:\n claimName: \"raylab-20260530151529-r6av-cos-ea42a9657cb4a266f40406bc9fc8530d-pvc\"\n rayVersion: \"2.55.1\"\n suspend: false\n workerGroupSpecs: []\nstatus:\n conditions:\n - lastTransitionTime: \"2026-05-30T07:17:48Z\"\n message: \"\"\n reason: \"HeadPodRunningAndReady\"\n status: \"True\"\n type: \"HeadPodReady\"\n - lastTransitionTime: \"2026-05-30T07:17:48Z\"\n message: \"All Ray Pods are ready for the first time\"\n reason: \"AllPodRunningAndReadyFirstTime\"\n status: \"True\"\n type: \"RayClusterProvisioned\"\n - lastTransitionTime: \"2026-05-30T07:17:06Z\"\n message: \"\"\n reason: \"RayClusterSuspended\"\n status: \"False\"\n type: \"RayClusterSuspended\"\n - lastTransitionTime: \"2026-05-30T07:17:06Z\"\n message: \"\"\n reason: \"RayClusterSuspending\"\n status: \"False\"\n type: \"RayClusterSuspending\"\n desiredCPU: \"400m\"\n desiredGPU: \"0\"\n desiredMemory: \"1638Mi\"\n desiredTPU: \"0\"\n endpoints:\n client: \"10001\"\n dashboard: \"8265\"\n gcs-server: \"6379\"\n metrics: \"8080\"\n head:\n podIP: \"30.0.1.160\"\n podName: \"raylab-20260530151529-r6av-head-78mtl\"\n serviceIP: \"30.0.1.160\"\n serviceName: \"raylab-20260530151529-r6av-head-svc\"\n lastUpdateTime: \"2026-05-30T07:17:48Z\"\n observedGeneration: 2\n state: \"ready\"\n stateTransitionTimes:\n ready: \"2026-05-30T07:17:48Z\"\n",
"RequestId": "c5b4610c-9021-458b-a9df-ee8d087dbef6"
}
}5. 开发者资源
腾讯云 API 平台
腾讯云 API 平台 是综合 API 文档、错误码、API Explorer 及 SDK 等资源的统一查询平台，方便您从同一入口查询及使用腾讯云提供的所有 API 服务。
API Inspector
用户可通过 API Inspector 查看控制台每一步操作关联的 API 调用情况，并自动生成各语言版本的 API 代码，也可前往 API Explorer 进行在线调试。
SDK
云 API 3.0 提供了配套的开发工具集（SDK），支持多种编程语言，能更方便的调用 API。
- Tencent Cloud SDK 3.0 for Python: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for Java: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for PHP: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for Go: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for Node.js: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for .NET: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for C++: CNB, GitHub, Gitee
- Tencent Cloud SDK 3.0 for Ruby: CNB, GitHub, Gitee
命令行工具
6. 错误码
该接口暂无业务逻辑相关的错误码，其他错误码详见 公共错误码。
