wehub-resource-sync
179 lines
4.7 KiB
YAML
179 lines
4.7 KiB
YAML
# File name: config.yaml
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kind: ConfigMap
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apiVersion: v1
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metadata:
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name: redis-config
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labels:
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app: redis
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data:
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redis.conf: |-
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port 6379
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bind 0.0.0.0
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protected-mode no
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requirepass 5241590000000000
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: redis
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labels:
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app: redis
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spec:
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type: ClusterIP
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ports:
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- name: redis
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port: 6379
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selector:
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app: redis
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---
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: redis
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labels:
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app: redis
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spec:
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replicas: 1
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selector:
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matchLabels:
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app: redis
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template:
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metadata:
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labels:
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app: redis
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spec:
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containers:
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- name: redis
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image: redis:5.0.8
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command:
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- "sh"
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- "-c"
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- "redis-server /usr/local/etc/redis/redis.conf"
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ports:
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- containerPort: 6379
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volumeMounts:
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- name: config
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mountPath: /usr/local/etc/redis/redis.conf
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subPath: redis.conf
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volumes:
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- name: config
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configMap:
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name: redis-config
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---
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apiVersion: ray.io/v1alpha1
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kind: RayService
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metadata:
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name: rayservice-sample
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annotations:
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ray.io/ft-enabled: "true"
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spec:
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serviceUnhealthySecondThreshold: 300
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deploymentUnhealthySecondThreshold: 300
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serveConfig:
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importPath: "sleepy_pid:app"
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runtimeEnv: |
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working_dir: "https://github.com/ray-project/serve_config_examples/archive/42d10bab77741b40d11304ad66d39a4ec2345247.zip"
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deployments:
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- name: SleepyPid
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numReplicas: 6
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rayActorOptions:
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numCpus: 0
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rayClusterConfig:
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rayVersion: '2.3.0'
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headGroupSpec:
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replicas: 1
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rayStartParams:
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num-cpus: '2'
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dashboard-host: '0.0.0.0'
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redis-password: "5241590000000000"
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template:
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spec:
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containers:
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- name: ray-head
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image: rayproject/ray:2.3.0
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imagePullPolicy: Always
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env:
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- name: MY_POD_IP
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valueFrom:
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fieldRef:
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fieldPath: status.podIP
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- name: RAY_REDIS_ADDRESS
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value: redis:6379
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resources:
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limits:
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cpu: 2
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memory: 2Gi
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requests:
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cpu: 2
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memory: 2Gi
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ports:
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- containerPort: 6379
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name: redis
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- containerPort: 8265
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name: dashboard
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- containerPort: 10001
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name: client
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- containerPort: 8000
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name: serve
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workerGroupSpecs:
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- replicas: 2
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minReplicas: 2
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maxReplicas: 2
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groupName: small-group
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rayStartParams:
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node-ip-address: $MY_POD_IP
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template:
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spec:
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containers:
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- name: machine-learning
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image: rayproject/ray:2.3.0
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imagePullPolicy: Always
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env:
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- name: RAY_DISABLE_DOCKER_CPU_WARNING
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value: "1"
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- name: TYPE
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value: "worker"
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- name: CPU_REQUEST
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valueFrom:
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resourceFieldRef:
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containerName: machine-learning
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resource: requests.cpu
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- name: CPU_LIMITS
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valueFrom:
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resourceFieldRef:
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containerName: machine-learning
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resource: limits.cpu
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- name: MEMORY_LIMITS
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valueFrom:
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resourceFieldRef:
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containerName: machine-learning
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resource: limits.memory
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- name: MEMORY_REQUESTS
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valueFrom:
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resourceFieldRef:
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containerName: machine-learning
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resource: requests.memory
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- name: MY_POD_NAME
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valueFrom:
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fieldRef:
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fieldPath: metadata.name
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- name: MY_POD_IP
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valueFrom:
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fieldRef:
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fieldPath: status.podIP
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ports:
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- containerPort: 80
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name: client
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lifecycle:
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preStop:
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exec:
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command: ["/bin/sh","-c","ray stop"]
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resources:
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limits:
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cpu: "1"
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memory: "2Gi"
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requests:
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cpu: "500m"
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memory: "2Gi"
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