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Update server Kubernetes deployment/upgrade instructions (#231)
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@ -58,6 +58,6 @@ When necessary, upgrade your ClearML Server on any of the available formats:
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* [Google Cloud Platform](upgrade_server_gcp.md)
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* [Linux or MacOS](upgrade_server_linux_mac.md)
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* [Windows 10](upgrade_server_win.md)
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* [Kubernetes using Helm](upgrade_server_kubernetes_helm.md)
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* [Kubernetes](upgrade_server_kubernetes_helm.md)
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If you are using v0.15 or Older, [upgrade to ClearML Server](clearml_server_es7_migration.md).
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@ -2,146 +2,33 @@
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title: Kubernetes
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---
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:::important
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**This documentation page is being updated.** Please see the new and improved **[ClearML Helm Charts repository](https://github.com/allegroai/clearml-helm-charts)**
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for the most updated instructions.
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:::
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To upgrade an existing ClearML Server Kubernetes deployment, see [here](upgrade_server_kubernetes_helm.md).
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:::warning
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If **ClearML Server** is being reinstalled, we recommend clearing browser cookies for **ClearML Server**. For example,
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:::info
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If ClearML Server is being reinstalled, we recommend clearing browser cookies for ClearML Server. For example,
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for Firefox, go to Developer Tools > Storage > Cookies, and for Chrome, go to Developer Tools > Application > Cookies,
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and delete all cookies under the **ClearML Server** URL.
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and delete all cookies under the ClearML Server URL.
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:::
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For information about upgrading **ClearML Server** in Kubernetes Clusters using Help, see [here](upgrade_server_kubernetes_helm.md).
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## Prerequisites
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* A Kubernetes cluster.
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* `kubectl` installed and configured (see [Install and Set Up kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/) in the Kubernetes documentation).
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* `helm` is installed (see [Installing Helm](https://helm.sh/docs/using_helm.html#installing-helm) in the Helm documentation).
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* One node labeled `app=clearml`.
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* Set up a Kubernetes cluster - For setting up Kubernetes on various platforms refer to the Kubernetes [getting started guide](https://kubernetes.io/docs/setup).
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* Set up a single node LOCAL Kubernetes on laptop / desktop - For setting up Kubernetes on your laptop/desktop, we suggest [kind](https://kind.sigs.k8s.io).
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* Install `helm` - Helm is a tool for managing Kubernetes charts. Charts are packages of pre-configured Kubernetes resources.
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To install Helm, refer to the [Helm installation guide](https://helm.sh/docs/using_helm.html#installing-helm) in the Helm documentation.
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Ensure that the `helm` binary is in the PATH of your shell.
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:::warning
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ClearML Server deployment uses node storage. If more than one node is labeled as ``app=clearml``, and the server is later
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redeployed or updated, then **ClearML Server** may not locate all the data.
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:::
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## Deployment
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## Deploying
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You will create a multi-node Kubernetes cluster using Helm, and then install ClearML in your cluster. For deployment
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instructions with up-to-date Helms charts, see the [clearml-helm-charts repository](https://github.com/allegroai/clearml-helm-charts/tree/main/charts/clearml#local-environment).
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:::warning
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By default, **ClearML Server** launches with unrestricted access. To restrict **ClearML Server** access, follow the
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:::warning Server Access
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By default, ClearML Server launches with unrestricted access. To restrict ClearML Server access, follow the
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instructions in the [Security](clearml_server_security.md) page.
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:::
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### Step 1: Modify Elasticsearch Default Values in the Docker Configuration File
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Before deploying **ClearML Server** in a Kubernetes cluster, modify several Elasticsearch settings in the Docker configuration.
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For more information, see [Install Elasticsearch with Docker](https://www.elastic.co/guide/en/elasticsearch/reference/master/docker.html#_notes_for_production_use_and_defaults)
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in the Elasticsearch documentation and [Daemon configuration file](https://docs.docker.com/config/daemon/) in the Docker documentation.
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**To modify Elasticsearch default values in the Docker configuration file:**
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1. Connect to the node in the Kubernetes cluster labeled `app=clearml`.
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1. Create or edit (if one exists) the `/etc/docker/daemon.json` file, and add or modify the `defaults-ulimits` section as
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the following example shows:
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{
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"default-ulimits": {
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"nofile": {
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"name": "nofile",
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"hard": 65536,
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"soft": 1024
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},
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"memlock":
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{
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"name": "memlock",
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"soft": -1,
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"hard": -1
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}
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}
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}
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1. Elasticsearch requires that the `vm.max_map_count` kernel setting, which is the maximum number of memory map areas a
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process can use, be set to at least `262144`.
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For CentOS 7, Ubuntu 16.04, Mint 18.3, Ubuntu 18.04 and Mint 19.x, use the following commands to set `vm.max_map_count`:
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echo "vm.max_map_count=262144" > /tmp/99-clearml.conf
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sudo mv /tmp/99-clearml.conf /etc/sysctl.d/99-clearml.conf
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sudo sysctl -w vm.max_map_count=262144
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1. Restart docker:
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sudo service docker restart
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### Step 2. Deploy ClearML Server in the Kubernetes Using Helm
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After modifying several Elasticsearch settings in the Docker configuration (see Step 1 above), deploy **ClearML Server**.
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**To deploy ClearML Server in Kubernetes using Helm:**
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1. Add the clearml-server repository to Helm:
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helm repo add allegroai https://allegroai.github.io/clearml-helm-charts
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1. Confirm the clearml repository is now in Helm:
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helm search repo allegroai
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The helm search results must include `allegroai/clearml`.
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1. Install `clearml` on your cluster:
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helm install clearml-server allegroai/clearml -n clearml --create-namespace
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A clearml `namespace` is created in the cluster and clearml-server is deployed in it.
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## Port Mapping
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After **ClearML Server** is deployed, the services expose the following node 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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The node ports map to the following container ports:
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* `30080` maps to `clearml-webserver` container on port `8080`
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* `30008` maps to `clearml-apiserver` container on port `8008`
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* `30081` maps to `clearml-fileserver` container on port `8081`
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:::important
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We recommend using the container ports (``8080``, ``8008``, and ``8081``), or a load balancer (see the next section, [Accessing ClearML Server](#accessing-clearml-server)).
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:::
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## Accessing ClearML Server
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**To access ClearML Server:**
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* Create a load balancer and domain with records pointing to **ClearML Server** using the following rules, which **ClearML**
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uses to translate domain names:
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* The record to access the **ClearML Web UI**:
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*app.<your domain name>.*
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For example, `clearml.app.mydomainname.com` points to your node on port `30080`.
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* The record to access the ClearML API:
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*api.<your domain name>.*
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For example, `clearml.api.mydomainname.com` points to your node on port `30008`.
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* The record to access the ClearML file server:
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*files.<your domain name>.*
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For example, `clearmlfiles.mydomainname.com` points to your node on port `30081`.
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## Next Step
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* [Configuring ClearML for ClearML Server](clearml_config_for_clearml_server.md).
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@ -2,26 +2,23 @@
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title: Kubernetes
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---
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:::important
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**This documentation page is being updated.** Please see the new and improved **[ClearML Helm Charts repository](https://github.com/allegroai/clearml-helm-charts)**
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for the most updated instructions.
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:::
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:::note
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We strongly encourage to keep the **ClearML Server** up to date, by upgrading to the current release.
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**To update to the latest version of the Helms chart,** execute the following:
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```bash
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helm repo update
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helm upgrade clearml allegroai/clearml
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```
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**To change the values in an existing installation,** execute the following:
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```bash
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helm upgrade clearml allegroai/clearml --version <CURRENT CHART VERSION> -f custom_values.yaml
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```
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See the [clearml-helm-charts repository](https://github.com/allegroai/clearml-helm-charts/tree/main/charts/clearml#local-environment)
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to view the up-to-date charts.
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:::tip
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When changing values, make sure to set the chart version (`--version`) to avoid a chart update. We recommend keeping separate procedures between version and value updates to separate potential concerns.
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:::
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1. Upgrade using new or upgraded values.yaml
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helm upgrade clearml-server allegroai/clearml-server-chart -f new-values.yaml
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1. If **ClearML Server** was previously deployed, first delete old deployments using the following command:
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helm delete --purge clearml-server
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1. If upgrading from Trains Server version 0.15 or older, a data migration is required before continuing this upgrade.
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See instructions [here](clearml_server_es7_migration.md).
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1. Upgrade deployment to match repository version.
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helm upgrade clearml-server allegroai/clearml-server-chart
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