mirror of
https://github.com/clearml/clearml-helm-charts
synced 2025-04-17 01:31:13 +00:00
One default agent (#10)
* one cpu only agent by default * helm-docs update * suggest kind for single done cluster * bump up version * fix trailing space
This commit is contained in:
Valeriano Manassero
GitHub
parent
cc8789d71f
commit
d269374a49
@ -8,6 +8,10 @@ Helm charts provided by [Allegro AI](https://clear.ml), ready to launch on Kuber
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For setting up Kubernetes on various platforms refer to the Kubernetes [getting started guide](http://kubernetes.io/docs/getting-started-guides/).
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### Setup a single node LOCAL Kubernetes on laptop/desktop
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For setting up Kubernetes on your laptop/desktop we suggest [kind](https://kind.sigs.k8s.io).
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### Install Helm
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Helm is a tool for managing Kubernetes charts. Charts are packages of pre-configured Kubernetes resources.
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@ -2,7 +2,7 @@ apiVersion: v2
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name: clearml
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description: MLOps platform
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type: application
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version: "2.0.0-alpha2"
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version: "2.0.0-beta1"
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appVersion: "1.0.2"
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home: https://clear.ml
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icon: https://raw.githubusercontent.com/allegroai/clearml/master/docs/clearml-logo.svg
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@ -1,6 +1,6 @@
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# ClearML Ecosystem for Kubernetes
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MLOps platform
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@ -16,8 +16,6 @@ MLOps platform
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The **clearml-server** is the backend service infrastructure for [ClearML](https://github.com/allegroai/clearml).
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It allows multiple users to collaborate and manage their experiments.
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By default, *ClearML is set up to work with the ClearML Demo Server, which is open to anyone and resets periodically.
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In order to host your own server, you will need to install **clearml-server** and point ClearML to it.
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**clearml-server** contains the following components:
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@ -27,33 +25,59 @@ In order to host your own server, you will need to install **clearml-server** an
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* Querying experiments history, logs and results
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* Locally-hosted file server for storing images and models making them easily accessible using the Web-App
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## Port Mapping
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## Local environment
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After **clearml-server** is deployed, the services expose the following node ports:
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For development/evaluation it's possible to use [kind](https://kind.sigs.k8s.io).
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After installation, following commands will create a complete ClearML insatllation:
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```
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cat <<EOF > /tmp/clearml-kind.yaml
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kind: Cluster
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apiVersion: kind.x-k8s.io/v1alpha4
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nodes:
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- role: control-plane
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extraPortMappings:
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- containerPort: 30008
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hostPort: 30008
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listenAddress: "127.0.0.1"
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protocol: TCP
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- containerPort: 30080
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hostPort: 30080
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listenAddress: "127.0.0.1"
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protocol: TCP
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- containerPort: 30081
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hostPort: 30081
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listenAddress: "127.0.0.1"
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protocol: TCP
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extraMounts:
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- hostPath: /var/folders/kind/
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containerPath: /var/local-path-provisioner
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EOF
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kind create cluster --config /tmp/clearml-kind.yaml
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helm install clearml allegroai/clearml
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```
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After deployment, the services will be exposed on localhost on the following ports:
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* API server on `30008`
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* Web server on `30080`
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* File server on `30081`
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## Accessing ClearML Server
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## Production cluster environment
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Access **clearml-server** by creating a load balancer and domain name with records pointing to the load balancer.
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In a production environment it's suggested to install an ingress controller and verify that is working correctly.
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During ClearML deployment enable `ingress` section of chart values.
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This will create 3 ingress rules:
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Once you have a load balancer and domain name set up, follow these steps to configure access to clearml-server on your k8s cluster:
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* `app.<your domain name>`
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* `files.<your domain name>`
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* `api.<your domain name>`
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1. Create domain records
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(*for example, `app.clearml.mydomainname.com`, `files.clearml.mydomainname.com` and `api.clearml.mydomainname.com`*)
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* Create 3 records to be used for Web-App, File server and API access using the following rules:
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* `app.<your domain name>`
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* `files.<your domain name>`
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* `api.<your domain name>`
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(*for example, `app.clearml.mydomainname.com`, `files.clearml.mydomainname.com` and `api.clearml.mydomainname.com`*)
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2. Point the records you created to the load balancer
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3. Configure the load balancer to redirect traffic coming from the records you created:
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* `app.<your domain name>` should be redirected to k8s cluster nodes on port `30080`
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* `files.<your domain name>` should be redirected to k8s cluster nodes on port `30081`
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* `api.<your domain name>` should be redirected to k8s cluster nodes on port `30008`
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Just pointing the domain records to the IP where ingress controller is responding will complete the deployment process.
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## Additional Configuration for ClearML Server
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@ -81,28 +105,50 @@ For detailed instructions, see the [Optional Configuration](https://github.com/a
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| Key | Type | Default | Description |
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|-----|------|---------|-------------|
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| agentGroups.agent-group0.affinity | object | `{}` | |
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| agentGroups.agent-group0.agentVersion | string | `""` | |
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| agentGroups.agent-group0.awsAccessKeyId | string | `nil` | |
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| agentGroups.agent-group0.awsDefaultRegion | string | `nil` | |
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| agentGroups.agent-group0.awsSecretAccessKey | string | `nil` | |
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| agentGroups.agent-group0.azureStorageAccount | string | `nil` | |
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| agentGroups.agent-group0.azureStorageKey | string | `nil` | |
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| agentGroups.agent-group0.clearmlAccessKey | string | `nil` | |
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| agentGroups.agent-group0.clearmlConfig | string | `"sdk {\n}"` | |
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| agentGroups.agent-group0.clearmlGitPassword | string | `nil` | |
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| agentGroups.agent-group0.clearmlGitUser | string | `nil` | |
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| agentGroups.agent-group0.clearmlSecretKey | string | `nil` | |
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| agentGroups.agent-group0.image.pullPolicy | string | `"IfNotPresent"` | |
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| agentGroups.agent-group0.image.repository | string | `"nvidia/cuda"` | |
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| agentGroups.agent-group0.image.tag | string | `"11.0-base-ubuntu18.04"` | |
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| agentGroups.agent-group0.name | string | `"agent-group0"` | |
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| agentGroups.agent-group0.nodeSelector | object | `{}` | |
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| agentGroups.agent-group0.nvidiaGpusPerAgent | int | `1` | |
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| agentGroups.agent-group0.podAnnotations | object | `{}` | |
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| agentGroups.agent-group0.queues | string | `"default"` | |
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| agentGroups.agent-group0.replicaCount | int | `0` | |
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| agentGroups.agent-group0.tolerations | list | `[]` | |
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| agentGroups.agent-group-cpu.affinity | object | `{}` | |
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| agentGroups.agent-group-cpu.agentVersion | string | `""` | |
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| agentGroups.agent-group-cpu.awsAccessKeyId | string | `nil` | |
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| agentGroups.agent-group-cpu.awsDefaultRegion | string | `nil` | |
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| agentGroups.agent-group-cpu.awsSecretAccessKey | string | `nil` | |
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| agentGroups.agent-group-cpu.azureStorageAccount | string | `nil` | |
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| agentGroups.agent-group-cpu.azureStorageKey | string | `nil` | |
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| agentGroups.agent-group-cpu.clearmlAccessKey | string | `nil` | |
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| agentGroups.agent-group-cpu.clearmlConfig | string | `"sdk {\n}"` | |
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| agentGroups.agent-group-cpu.clearmlGitPassword | string | `nil` | |
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| agentGroups.agent-group-cpu.clearmlGitUser | string | `nil` | |
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| agentGroups.agent-group-cpu.clearmlSecretKey | string | `nil` | |
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| agentGroups.agent-group-cpu.image.pullPolicy | string | `"IfNotPresent"` | |
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| agentGroups.agent-group-cpu.image.repository | string | `"ubuntu"` | |
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| agentGroups.agent-group-cpu.image.tag | string | `"18.04"` | |
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| agentGroups.agent-group-cpu.name | string | `"agent-group-cpu"` | |
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| agentGroups.agent-group-cpu.nodeSelector | object | `{}` | |
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| agentGroups.agent-group-cpu.nvidiaGpusPerAgent | int | `0` | |
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| agentGroups.agent-group-cpu.podAnnotations | object | `{}` | |
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| agentGroups.agent-group-cpu.queues | string | `"default"` | |
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| agentGroups.agent-group-cpu.replicaCount | int | `1` | |
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| agentGroups.agent-group-cpu.tolerations | list | `[]` | |
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| agentGroups.agent-group-gpu.affinity | object | `{}` | |
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| agentGroups.agent-group-gpu.agentVersion | string | `""` | |
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| agentGroups.agent-group-gpu.awsAccessKeyId | string | `nil` | |
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| agentGroups.agent-group-gpu.awsDefaultRegion | string | `nil` | |
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| agentGroups.agent-group-gpu.awsSecretAccessKey | string | `nil` | |
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| agentGroups.agent-group-gpu.azureStorageAccount | string | `nil` | |
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| agentGroups.agent-group-gpu.azureStorageKey | string | `nil` | |
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| agentGroups.agent-group-gpu.clearmlAccessKey | string | `nil` | |
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| agentGroups.agent-group-gpu.clearmlConfig | string | `"sdk {\n}"` | |
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| agentGroups.agent-group-gpu.clearmlGitPassword | string | `nil` | |
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| agentGroups.agent-group-gpu.clearmlGitUser | string | `nil` | |
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| agentGroups.agent-group-gpu.clearmlSecretKey | string | `nil` | |
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| agentGroups.agent-group-gpu.image.pullPolicy | string | `"IfNotPresent"` | |
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| agentGroups.agent-group-gpu.image.repository | string | `"nvidia/cuda"` | |
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| agentGroups.agent-group-gpu.image.tag | string | `"11.0-base-ubuntu18.04"` | |
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| agentGroups.agent-group-gpu.name | string | `"agent-group-gpu"` | |
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| agentGroups.agent-group-gpu.nodeSelector | object | `{}` | |
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| agentGroups.agent-group-gpu.nvidiaGpusPerAgent | int | `1` | |
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| agentGroups.agent-group-gpu.podAnnotations | object | `{}` | |
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| agentGroups.agent-group-gpu.queues | string | `"default"` | |
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| agentGroups.agent-group-gpu.replicaCount | int | `0` | |
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| agentGroups.agent-group-gpu.tolerations | list | `[]` | |
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| agentservices.affinity | object | `{}` | |
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| agentservices.agentVersion | string | `""` | |
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| agentservices.awsAccessKeyId | string | `nil` | |
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@ -13,8 +13,6 @@
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The **clearml-server** is the backend service infrastructure for [ClearML](https://github.com/allegroai/clearml).
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It allows multiple users to collaborate and manage their experiments.
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By default, *ClearML is set up to work with the ClearML Demo Server, which is open to anyone and resets periodically.
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In order to host your own server, you will need to install **clearml-server** and point ClearML to it.
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**clearml-server** contains the following components:
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@ -24,33 +22,59 @@ In order to host your own server, you will need to install **clearml-server** an
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* Querying experiments history, logs and results
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* Locally-hosted file server for storing images and models making them easily accessible using the Web-App
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## Port Mapping
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## Local environment
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After **clearml-server** is deployed, the services expose the following node ports:
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For development/evaluation it's possible to use [kind](https://kind.sigs.k8s.io).
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After installation, following commands will create a complete ClearML insatllation:
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```
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cat <<EOF > /tmp/clearml-kind.yaml
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kind: Cluster
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apiVersion: kind.x-k8s.io/v1alpha4
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nodes:
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- role: control-plane
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extraPortMappings:
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- containerPort: 30008
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hostPort: 30008
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listenAddress: "127.0.0.1"
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protocol: TCP
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- containerPort: 30080
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hostPort: 30080
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listenAddress: "127.0.0.1"
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protocol: TCP
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- containerPort: 30081
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hostPort: 30081
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listenAddress: "127.0.0.1"
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protocol: TCP
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extraMounts:
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- hostPath: /var/folders/kind/
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containerPath: /var/local-path-provisioner
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EOF
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kind create cluster --config /tmp/clearml-kind.yaml
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helm install clearml allegroai/clearml
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```
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After deployment, the services will be exposed on localhost on the following ports:
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* API server on `30008`
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* Web server on `30080`
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* File server on `30081`
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## Accessing ClearML Server
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## Production cluster environment
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Access **clearml-server** by creating a load balancer and domain name with records pointing to the load balancer.
|
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In a production environment it's suggested to install an ingress controller and verify that is working correctly.
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During ClearML deployment enable `ingress` section of chart values.
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This will create 3 ingress rules:
|
||||
|
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Once you have a load balancer and domain name set up, follow these steps to configure access to clearml-server on your k8s cluster:
|
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* `app.<your domain name>`
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* `files.<your domain name>`
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* `api.<your domain name>`
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1. Create domain records
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(*for example, `app.clearml.mydomainname.com`, `files.clearml.mydomainname.com` and `api.clearml.mydomainname.com`*)
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* Create 3 records to be used for Web-App, File server and API access using the following rules:
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* `app.<your domain name>`
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* `files.<your domain name>`
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* `api.<your domain name>`
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(*for example, `app.clearml.mydomainname.com`, `files.clearml.mydomainname.com` and `api.clearml.mydomainname.com`*)
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2. Point the records you created to the load balancer
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3. Configure the load balancer to redirect traffic coming from the records you created:
|
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* `app.<your domain name>` should be redirected to k8s cluster nodes on port `30080`
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* `files.<your domain name>` should be redirected to k8s cluster nodes on port `30081`
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* `api.<your domain name>` should be redirected to k8s cluster nodes on port `30008`
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Just pointing the domain records to the IP where ingress controller is responding will complete the deployment process.
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## Additional Configuration for ClearML Server
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@ -180,8 +180,40 @@ agentservices:
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size: 50Gi
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agentGroups:
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agent-group0:
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name: agent-group0
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agent-group-cpu:
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name: agent-group-cpu
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replicaCount: 1
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nvidiaGpusPerAgent: 0
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agentVersion: "" # if set, it *MUST* include comparison operator (e.g. ">=0.16.1")
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queues: "default" # multiple queues can be specified separated by a space (e.g. "important_jobs default")
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clearmlGitUser: null
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clearmlGitPassword: null
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clearmlAccessKey: null
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clearmlSecretKey: null
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awsAccessKeyId: null
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awsSecretAccessKey: null
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awsDefaultRegion: null
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azureStorageAccount: null
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azureStorageKey: null
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clearmlConfig: |-
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sdk {
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}
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image:
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repository: "ubuntu"
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pullPolicy: IfNotPresent
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tag: "18.04"
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podAnnotations: {}
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nodeSelector: {}
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tolerations: []
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affinity: {}
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agent-group-gpu:
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name: agent-group-gpu
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replicaCount: 0
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nvidiaGpusPerAgent: 1
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agentVersion: "" # if set, it *MUST* include comparison operator (e.g. ">=0.16.1")
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