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10
docs/deploying_clearml/clearml_server_aws_ec2_ami.md
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@@ -35,7 +35,7 @@ in the [Security](clearml_server_security.md) page.
The minimum recommended amount of RAM is 8 GB. For example, a t3.large or t3a.large EC2 instance type would accommodate the recommended RAM size.
### AWS community AMIs
### AWS Community AMIs
**To launch a ClearML Server AWS community AMI:**
@@ -106,7 +106,7 @@ Once deployed, **ClearML Server** exposes the following services:
If needed, modify the default login behavior to match workflow policy, see [Configuring Web Login Authentication](clearml_server_config.md#web-login-authentication)
on the "Configuring Your Own ClearML Server" page.
## Storage configuration
## Storage Configuration
The pre-built **ClearML Server** storage configuration is the following:
@@ -115,7 +115,7 @@ The pre-built **ClearML Server** storage configuration is the following:
* File Server: `/mnt/fileserver/`
## Backing up and restoring data and configuration
## Backing Up and Restoring Data and Configuration
:::note
If data is being moved between a **Trains Server** and a **ClearML Server** installation, make sure to use the correct paths
@@ -147,13 +147,13 @@ sudo tar czvf ~/clearml_backup_config.tgz -C /opt/clearml/config .
```
## ClearML Server AWS community AMIs
## ClearML Server AWS Community AMIs
The following section contains a list of AMI Image IDs per region for the latest **ClearML Server** version.
### Latest version
### Latest Version
#### v1.1.1

22
docs/deploying_clearml/clearml_server_config.md
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@@ -20,11 +20,11 @@ For all configuration options, see the [ClearML Configuration Reference](../conf
We recommend using the latest version of **ClearML Server**.
:::
## ClearML Server deployment configuration
## ClearML Server Deployment Configuration
**ClearML Server** supports two deployment configurations: single IP (domain) and sub-domains.
### Single IP (domain) configuration
### Single IP (Domain) Configuration
Single IP (domain) with the following open ports:
@@ -32,7 +32,7 @@ Single IP (domain) with the following open ports:
* API service on port `8008`
* File storage service on port `8081`
### Sub-domain configuration
### Sub-domain Configuration
Sub-domain configuration with default http/s ports (`80` or `443`):
@@ -60,7 +60,7 @@ Accessing the **ClearML Web UI** with `app.clearml.mydomain.com` will automatica
**ClearML Server** features can be configured using either configuration files or environment variables.
### Configuration files
### Configuration Files
The **ClearML Server** uses the following configuration files:
@@ -88,12 +88,12 @@ tasks {
:::
### Environment variables
### Environment Variables
The **ClearML Server** supports several fixed environment variables that affect its behavior,
as well as dynamic environment variable that can be used to override any configuration file setting.
#### Fixed environment variables
#### Fixed Environment Variables
General
@@ -109,7 +109,7 @@ Database service overrides:
* `CLEARML_REDIS_SERVICE_PORT` allows overriding the port for the Redis service
#### Dynamic environment variables
#### Dynamic Environment Variables
Dynamic environment variables can be used to override any configuration setting that appears in the configuration files.
@@ -144,11 +144,11 @@ the default secret for the system's apiserver component can be overridden by set
dynamic environment variable's key to lower-case before overriding configuration values with the environment variable value.
:::
## Configuration procedures
## Configuration Procedures
### Sub-domains and load balancers
### Sub-domains and Load Balancers
To illustrate this configuration, we provide the following example based on AWS load balancing:
@@ -189,7 +189,7 @@ To illustrate this configuration, we provide the following example based on AWS
### Opening Elasticsearch, MongoDB, and Redis for external access
### Opening Elasticsearch, MongoDB, and Redis for External Access
For improved security, the ports for **ClearML Server** Elasticsearch, MongoDB, and Redis servers are not exposed by default;
they are only open internally in the docker network. If external access is needed, open these ports (but make sure to
@@ -267,7 +267,7 @@ Without web login authentication, **ClearML Server** does not restrict access (b
1. Restart **ClearML Server**.
### Using hashed passwords
### Using Hashed Passwords
You can also use hashed passwords instead of plain-text passwords. To do that:
- Set `pass_hashed: true`
- Use a base64-encoded hashed password in the `password` field instead of a plain-text password. Assuming Jane's plain-text password is `123456`, use the following bash command to generate the base64-encoded hashed password:

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docs/deploying_clearml/clearml_server_es7_migration.md
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@@ -35,7 +35,7 @@ and **ClearML Server** needs to be installed.
* Minimum free disk space of at least 30% plus two times the size of the data.
* Python version >=2.7 or >=3.6, and Python accessible from the command-line as `python`
### Migrating the data
### Migrating the Data
**To migrate the data:**
@@ -125,13 +125,13 @@ and **ClearML Server** needs to be installed.
kubectl get jobs -n upgrade-elastic
### Finishing up
### Finishing Up
To finish up:
1. Verify the data migration
1. Conclude the upgrade.
#### Step 1. Verifying the data migration
#### Step 1. Verifying the Data Migration
Upon successful completion, the migration script renames the original **Trains Server** directory, which contains the now
migrated data, and prints a completion message:
@@ -150,7 +150,7 @@ For help in resolving migration issues, check the **allegro-clearml** [Slack Cha
[GitHub Issues](https://github.com/allegroai/clearml-server/issues), and the **ClearML Server** sections of the [FAQ](../faq.md).
:::
#### Step 2. Completing the installation
#### Step 2. Completing the Installation
After verifying the data migration completed successfully, conclude the **ClearML Server** installation process.
@@ -205,7 +205,7 @@ For backwards compatibility, the environment variables ``TRAINS_HOST_IP``, ``TRA
If issues arise during the upgrade, see the FAQ page, [How do I fix Docker upgrade errors?](../faq#common-docker-upgrade-errors).
##### Other deployment formats
##### Other Deployment Formats
To conclude the upgrade for deployment formats other than Linux, follow their upgrade instructions:

10
docs/deploying_clearml/clearml_server_gcp.md
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@@ -20,7 +20,7 @@ for Firefox, go to Developer Tools > Storage > Cookies, and for Chrome, go to De
and delete all cookies under the **ClearML Server** URL.
:::
## Default ClearML Server service ports
## Default ClearML Server Service Ports
After deploying **ClearML Server**, the services expose the following node ports:
@@ -28,7 +28,7 @@ After deploying **ClearML Server**, the services expose the following node ports
* API server on `8008`
* File Server on `8081`
## Default ClearML Server storage paths
## Default ClearML Server Storage Paths
The persistent storage configuration:
@@ -85,7 +85,7 @@ The minimum requirements for **ClearML Server** are:
docker-compose -f /opt/clearml/docker-compose.yml up -d
## Backing up and restoring data and configuration
## Backing Up and Restoring Data and Configuration
The commands in this section are an example of how to back up and restore data and configuration .
@@ -112,11 +112,11 @@ If the data and the configuration need to be restored:
The following section contains a list of Custom Image URLs (exported in different formats) for each released **ClearML Server** version.
### Latest version - v1.0.2
### Latest Version - v1.0.2
- [https://storage.googleapis.com/allegro-files/clearml-server/clearml-server.tar.gz](https://storage.googleapis.com/allegro-files/clearml-server/clearml-server.tar.gz)
### All release versions
### All Release Versions
- v1.0.2 - [https://storage.googleapis.com/allegro-files/clearml-server/clearml-server-1-0-2.tar.gz](https://storage.googleapis.com/allegro-files/clearml-server/clearml-server-1-0-2.tar.gz)
- v1.0.1 - [https://storage.googleapis.com/allegro-files/clearml-server/clearml-server-1-0-1.tar.gz](https://storage.googleapis.com/allegro-files/clearml-server/clearml-server-1-0-1.tar.gz)

4
docs/deploying_clearml/clearml_server_kubernetes_helm.md
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@@ -39,7 +39,7 @@ instructions in the [Security](clearml_server_security.md) page.
:::
### Step 1: Modify Elasticsearch default values in the Docker configuration file
### Step 1: Modify Elasticsearch Default Values in the Docker Configuration File
Before deploying **ClearML Server** in a Kubernetes cluster, modify several Elasticsearch settings in the Docker configuration.
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)
@@ -80,7 +80,7 @@ in the Elasticsearch documentation and [Daemon configuration file](https://docs.
sudo service docker restart
### Step 2. Deploy ClearML Server in the Kubernetes using Helm
### Step 2. Deploy ClearML Server in the Kubernetes Using Helm
After modifying several Elasticsearch settings in the Docker configuration (see Step 1 above), deploy **ClearML Server**.

4
docs/deploying_clearml/clearml_server_linux_mac.md
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@@ -135,7 +135,7 @@ instructions in the [Security](clearml_server_security.md) page.
The server is now running on [http://localhost:8080](http://localhost:8080).
## Port mapping
## Port Mapping
After deploying **ClearML Server**, the services expose the following ports:
@@ -154,7 +154,7 @@ After deploying **ClearML Server**, the services expose the following ports:
## Backing up and restoring data and configuration
## Backing Up and Restoring Data and Configuration
The commands in this section are an example of how to back up and to restore data and configuration .

2
docs/deploying_clearml/clearml_server_win.md
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@@ -60,7 +60,7 @@ By default, **ClearML Server** launches with unrestricted access. To restrict **
The server is now running on [http://localhost:8080](http://localhost:8080).
## Port mapping
## Port Mapping
After deploying **ClearML Server**, the services expose the following node ports:

4
docs/deploying_clearml/upgrade_server_aws_ec2_ami.md
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@@ -13,7 +13,7 @@ For upgrade purposes, the terms **Trains Server** and **ClearML Server** are int
The sections below contain the steps to upgrade **ClearML Server** on the [same AWS instance](#upgrading-on-the-same-aws-instance), and
to upgrade and migrate to a [new AWS instance](#upgrading-and-migrating-to-a-new-aws-instance).
### Upgrading on the same AWS instance
### Upgrading on the Same AWS Instance
This section contains the steps to upgrade **ClearML Server** on the same AWS instance.
@@ -48,7 +48,7 @@ Some legacy **Trains Server** AMIs provided an auto-upgrade on restart capabilit
docker-compose -f /opt/clearml/docker-compose.yml pull
docker-compose -f docker-compose.yml up -d
### Upgrading and migrating to a new AWS instance
### Upgrading and Migrating to a New AWS Instance
This section contains the steps to upgrade **ClearML Server** on the new AWS instance.