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Merge branch 'main' of https://github.com/allegroai/clearml-docs into enterprise

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docs/deploying_clearml/enterprise_deploy/appgw_install_compose.md
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@ -73,8 +73,8 @@ services:
Create a `runtime.env` file containing the following entries: Create a `runtime.env` file containing the following entries:
``` ```
PROXY_TAG= PROXY_TAG=1.5.1
ROUTER_TAG= ROUTER_TAG=2.6.2
ROUTER_NAME=main-router ROUTER_NAME=main-router
ROUTER__WEBSERVER__SERVER_PORT=8010 ROUTER__WEBSERVER__SERVER_PORT=8010
ROUTER_URL= ROUTER_URL=

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docs/deploying_clearml/enterprise_deploy/appgw_install_k8s.md
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@ -6,13 +6,13 @@ title: Kubernetes Deployment
The AI Application Gateway is available under the ClearML Enterprise plan. The AI Application Gateway is available under the ClearML Enterprise plan.
::: :::
This guide details the installation of the ClearML App Gateway Router. This guide details the installation of the ClearML App Gateway.
The App Gateway Router enables access to your AI workload applications (e.g. remote IDEs like VSCode and Jupyter, model API interface, etc.). The App Gateway enables access to your AI workload applications (e.g. remote IDEs like VSCode and Jupyter, model API interface, etc.).
It acts as a proxy, identifying ClearML Tasks running within its [K8s namespace](https://kubernetes.io/docs/concepts/overview/working-with-objects/namespaces/) It acts as a proxy, identifying ClearML Tasks running within its [K8s namespace](https://kubernetes.io/docs/concepts/overview/working-with-objects/namespaces/)
and making them available for network access. and making them available for network access.
:::important :::important
The App Gateway Router must be installed in the same K8s namespace as a dedicated ClearML Agent. The App Gateway must be installed in the same K8s namespace as a dedicated ClearML Agent.
It can only configure access for ClearML Tasks within its own namespace. It can only configure access for ClearML Tasks within its own namespace.
::: :::
@ -27,35 +27,31 @@ It can only configure access for ClearML Tasks within its own namespace.
## Optional for HTTPS ## Optional for HTTPS
* A valid DNS entry for the new App Gateway Router instance * A valid DNS entry for the new App Gateway instance
* A valid SSL certificate * A valid SSL certificate
## Helm ## Helm
### Login ### Login
``` ``` bash
helm repo add clearml-enterprise \ helm repo add clearml-enterprise https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages --username <GITHUB_TOKEN> --password <GITHUB_TOKEN>
https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages \
--username <GITHUB_TOKEN> \
--password <GITHUB_TOKEN>
``` ```
Replace `<GITHUB_TOKEN>` with your valid GitHub token that has access to the ClearML Enterprise Helm charts repository. Replace `<GITHUB_TOKEN>` with your valid GitHub token that has access to the ClearML Enterprise Helm charts repository.
### Prepare Values ### Prepare Values
Before installing the App Gateway Router, create a Helm override file: Before installing the App Gateway, create a Helm override `clearml-app-gateway-values.override.yaml` file:
``` ```yaml
imageCredentials: imageCredentials:
password: "" password: ""
clearml: clearml:
apiServerKey: "" apiKey: ""
apiServerSecret: "" apiSecret: ""
apiServerUrlReference: "" apiServerUrlReference: ""
authCookieName: "" authCookieName: ""
sslVerify: true
ingress: ingress:
enabled: true enabled: true
hostName: "" hostName: ""
@ -71,13 +67,12 @@ tcpSession:
**Configuration options:** **Configuration options:**
* `imageCredentials.password`: ClearML DockerHub Access Token. * `imageCredentials.password`: ClearML DockerHub Access Token.
* `clearml.apiServerKey`: ClearML server API key. * `clearml.apiKey` and `clearml.apiSecret`: [API credentials](../../webapp/settings/webapp_settings_profile.md#clearml-api-credentials) created in the ClearML web UI by an Admin user or Service
* `clearml.apiServerSecret`: ClearML server secret key. Account with admin privileges. Make sure to label these credentials clearly, so that they will not be revoked by mistake.
* `clearml.apiServerUrlReference`: ClearML API server URL starting with `https://api.`. * `clearml.apiServerUrlReference`: ClearML API server URL starting with `https://api.`.
* `clearml.authCookieName`: Cookie used by the ClearML server to store the ClearML authentication cookie. * `clearml.authCookieName`: Cookie used by the ClearML server to store the ClearML authentication cookie.
* `clearml.sslVerify`: Enable or disable SSL certificate validation on `apiserver` calls check. * `ingress.hostName`: Hostname of App Gateway used by the ingress controller to access it.
* `ingress.hostName`: Hostname of router used by the ingress controller to access it. * `tcpSession.routerAddress`: The external App Gateway address (can be an IP, hostname, or load balancer address) depending on your network setup. Ensure this address is accessible for TCP connections.
* `tcpSession.routerAddress`: The external router address (can be an IP, hostname, or load balancer address) depending on your network setup. Ensure this address is accessible for TCP connections.
* `tcpSession.service.type`: Service type used to expose TCP functionality, default is `NodePort`. * `tcpSession.service.type`: Service type used to expose TCP functionality, default is `NodePort`.
* `tcpSession.portRange.start`: Start port for the TCP Session feature. * `tcpSession.portRange.start`: Start port for the TCP Session feature.
* `tcpSession.portRange.end`: End port for the TCP Session feature. * `tcpSession.portRange.end`: End port for the TCP Session feature.
@ -85,33 +80,28 @@ tcpSession:
The full list of supported configuration is available with the command: The full list of supported configuration is available with the command:
``` ``` bash
helm show readme allegroai-enterprise/clearml-enterprise-task-traffic-router helm show readme clearml-enterprise/clearml-enterprise-app-gateway
``` ```
### Install ### Install
To install the App Gateway Router component via Helm use the following command: To install the App Gateway component via Helm use the following command:
``` ``` bash
helm upgrade --install \ helm upgrade --install <RELEASE_NAME> -n <WORKLOAD_NAMESPACE> clearml-enterprise/clearml-enterprise-app-gateway --version <CHART_VERSION> -f clearml-app-gateway-values.override.yaml
<RELEASE_NAME> \
-n <WORKLOAD_NAMESPACE> \
allegroai-enterprise/clearml-enterprise-task-traffic-router \
--version <CHART_VERSION> \
-f override.yaml
``` ```
Replace the placeholders with the following values: Replace the placeholders with the following values:
* `<RELEASE_NAME>` - Unique name for the App Gateway Router within the K8s namespace. This is a required parameter in * `<RELEASE_NAME>` - Unique name for the App Gateway within the K8s namespace. This is a required parameter in
Helm, which identifies a specific installation of the chart. The release name also defines the router’s name and Helm, which identifies a specific installation of the chart. The release name also defines the App Gateway's name and
appears in the UI within AI workload application URLs (e.g. Remote IDE URLs). This can be customized to support multiple installations within the same appears in the UI within AI workload application URLs (e.g. Remote IDE URLs). This can be customized to support multiple installations within the same
namespace by assigning different release names. namespace by assigning different release names.
* `<WORKLOAD_NAMESPACE>` - [Kubernetes Namespace](https://kubernetes.io/docs/concepts/overview/working-with-objects/namespaces/) * `<WORKLOAD_NAMESPACE>` - [Kubernetes Namespace](https://kubernetes.io/docs/concepts/overview/working-with-objects/namespaces/)
where workloads will be executed. This namespace must be shared between a dedicated ClearML Agent and an App where workloads will be executed. This namespace must be shared between a dedicated ClearML Agent and an App
Gateway Router. The agent is responsible for monitoring its assigned task queues and spawning workloads within this Gateway. The agent is responsible for monitoring its assigned task queues and spawning workloads within this
namespace. The router monitors the same namespace for AI workloads (e.g. remote IDE applications). The router has a namespace. The App Gateway monitors the same namespace for AI workloads (e.g. remote IDE applications). The App Gateway has a
namespace-limited scope, meaning it can only detect and manage tasks within its namespace-limited scope, meaning it can only detect and manage tasks within its
assigned namespace. assigned namespace.
* `<CHART_VERSION>` - Version recommended by the ClearML Support Team. * `<CHART_VERSION>` - Version recommended by the ClearML Support Team.

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docs/deploying_clearml/enterprise_deploy/k8s.md
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@ -2,408 +2,168 @@
title: Kubernetes title: Kubernetes
--- ---
This guide provides step-by-step instructions for installing the ClearML Enterprise Server (control-plane) in a Kubernetes cluster.
This guide provides step-by-step instructions for installing the ClearML Enterprise setup in a Kubernetes cluster. The ClearML Enterprise Server includes the ClearML `apiserver`, `fileserver`, and `webserver` components.
The package also includes MongoDB, ElasticSearch, and Redis as Helm dependencies.
## Prerequisites ## Prerequisites
To deploy a ClearML Server, ensure the following components and configurations are in place:
* A Kubernetes cluster - Kubernetes Cluster: A standard Kubernetes cluster is preferred for optimal GPU support.
* An ingress controller (e.g. `nginx-ingress`) and the ability to create LoadBalancer services (e.g. MetalLB) if needed - CLI Tools: `kubectl` and `helm` must be installed and configured.
to expose ClearML - Ingress Controller: An Ingress controller (e.g., `nginx-ingress`) is required. If exposing services externally, a
* Credentials for ClearML Enterprise GitHub Helm chart repository LoadBalancer-capable solution (e.g. `MetalLB`) should also be configured.
* Credentials for ClearML Enterprise DockerHub repository - Server and workers that communicate on HTTP/S (ports 80 and 443). Additionally, the TCP session feature requires a
* URL for downloading the ClearML Enterprise applications configuration range of ports for TCP traffic based on your configuration (see [AI App Gateway installation](appgw_install_k8s.md)).
- DNS Configuration: A domain with subdomain support is required, ideally with trusted TLS certificates. All entries must
be resolvable by the Ingress controller. Example subdomains:
- Server:
- `api.<BASE_DOMAIN>`
- `app.<BASE_DOMAIN>`
- `files.<BASE_DOMAIN>`
- Worker:
- `router.<BASE_DOMAIN>`
- `tcp-router.<BASE_DOMAIN>` (optional, for TCP sessions)
- Storage: A configured StorageClass and an accessible storage backend.
- ClearML Enterprise Access:
- Helm repository credentials (`<HELM_REPO_TOKEN>`)
- DockerHub registry credentials (`<CLEARML_DOCKERHUB_TOKEN>`)
### Recommended Cluster Specifications
## Control Plane Installation For optimal performance, a Kubernetes cluster with at least 3 nodes is recommended, each having:
- 8 vCPUs
- 32 GB RAM
- 500 GB storage
The following steps cover installing the control plane (server and required charts) and will ## Installation
require some or all of the tokens/deliverables mentioned above.
### Add the Helm Repo Locally
### Requirements Add the ClearML Helm repository:
``` bash
helm repo add clearml-enterprise https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages --username <HELM_REPO_TOKEN> --password <HELM_REPO_TOKEN>
```
* Add the ClearML Enterprise repository: Update the repository locally:
``` bash
helm repo update
```
### Prepare Values
``` Create a `clearml-values.override.yaml` file with the following content:
helm repo add clearml-enterprise https://raw.githubusercontent.com/clearml/clearml-enterprise-helm-charts/gh-pages --username <clearmlenterprise_GitHub_TOKEN> --password <clearmlenterprise_GitHub_TOKEN>
```
* Update the repository locally:
```
helm repo update
```
### Install ClearML Enterprise Chart
#### Configuration
The Helm Chart must be installed with an `overrides.yaml` overriding values as follows:
:::note :::note
In the following configuration, replace `<BASE_DOMAIN>` with a valid domain In the following configuration, replace the `<BASE_DOMAIN>` placeholders with a valid domain that will have records
that will have records pointing to the cluster’s ingress controller (see ingress details in the values below). pointing to the cluster's Ingress Controller. This will be the base domain for reaching your ClearML installation.
::: :::
``` yaml
```yaml
imageCredentials: imageCredentials:
password: "<clearml_enterprise_DockerHub_TOKEN>" password: "<CLEARML_DOCKERHUB_TOKEN>"
clearml: clearml:
cookieDomain: "<BASE_DOMAIN>" cookieDomain: "<BASE_DOMAIN>"
# Set values for improved security
apiserverKey: "<GENERATED_API_SERVER_KEY>"
apiserverSecret: "<GENERATED_API_SERVER_SECRET>"
fileserverKey: "<GENERATED_FILE_SERVER_KEY>"
fileserverSecret: "<GENERATED_FILE_SERVER_SECRET>"
secureAuthTokenSecret: "<GENERATED_AUTH_TOKEN_SECRET>"
testUserKey: "<GENERATED_TEST_USER_KEY>"
testUserSecret: "<GENERATED_TEST_USER_SECRET>"
apiserver: apiserver:
ingress: ingress:
enabled: true enabled: true
hostName: "api.<BASE_DOMAIN>" hostName: "api.<BASE_DOMAIN>"
service: service:
type: ClusterIP type: ClusterIP
fileserver: fileserver:
ingress: ingress:
enabled: true enabled: true
hostName: "file.<BASE_DOMAIN>" hostName: "files.<BASE_DOMAIN>"
service: service:
type: ClusterIP type: ClusterIP
webserver: webserver:
ingress: ingress:
enabled: true enabled: true
hostName: "app.<BASE_DOMAIN>" hostName: "app.<BASE_DOMAIN>"
service: service:
type: ClusterIP type: ClusterIP
clearmlApplications: clearmlApplications:
enabled: true enabled: true
``` ```
#### Additional Configuration Options ### Install the Chart
##### Fixed Users (Simple Login)
Install the ClearML Enterprise Helm chart using the previous values override file.
Enable static login with username and password in `overrides.yaml`. ``` bash
helm upgrade -i -n clearml clearml clearml-enterprise/clearml-enterprise --create-namespace -f clearml-values.override.yaml
This is an optional step in case SSO (Identity provider) configuration will not be performed.
```
apiserver:
additionalConfigs:
apiserver.conf: |
auth {
fixed_users {
enabled: true
pass_hashed: false
users: [
{
username: "my_user"
password: "my_password"
name: "My User"
admin: true
},
]
}
}
``` ```
## Additional Configuration Options
##### SSO (Identity Provider) :::note
You can view the full set of available and documented values of the chart by running the following command:
```bash
The following examples (Auth0 and Keycloak) show how to configure an identity provider on the ClearML server. helm show readme clearml-enterprise/clearml-enterprise
# or
helm show values clearml-enterprise/clearml-enterprise
Add the following values configuring `extraEnvs` for `apiserver` in the `clearml-enterprise` values `override.yaml` file.
Substitute all `<PLACEHOLDER>`s with the correct value for your configuration.
##### Auth0 Identity Provider
```yaml
apiserver:
extraEnvs:
- name: CLEARML__secure__login__sso__oauth_client__auth0__client_id
value: "<SSO_CLIENT_ID>"
- name: CLEARML__secure__login__sso__oauth_client__auth0__client_secret
value: "<SSO_CLIENT_SECRET>"
- name: CLEARML__services__login__sso__oauth_client__auth0__base_url
value: "<SSO_CLIENT_URL>"
- name: CLEARML__services__login__sso__oauth_client__auth0__authorize_url
value: "<SSO_CLIENT_AUTHORIZE_URL>"
- name: CLEARML__services__login__sso__oauth_client__auth0__access_token_url
value: "<SSO_CLIENT_ACCESS_TOKEN_URL>"
- name: CLEARML__services__login__sso__oauth_client__auth0__audience
value: "<SSO_CLIENT_AUDIENCE>"
``` ```
:::
### Default Secret Values
##### Keycloak Identity Provider For improved security, all the internal credentials are auto-generated randomly and stored in a Secret in
Kubernetes.
If you need to define your own credentials to be used instead, replace the default key and secret values in `clearml-values.override.yaml`.
```yaml ``` yaml
apiserver:
extraEnvs:
- name: CLEARML__secure__login__sso__oauth_client__keycloak__client_id
value: "<KC_CLIENT_ID>"
- name: CLEARML__secure__login__sso__oauth_client__keycloak__client_secret
value: "<KC_SECRET_ID>"
- name: CLEARML__services__login__sso__oauth_client__keycloak__base_url
value: "<KC_URL>/realms/<REALM_NAME>/"
- name: CLEARML__services__login__sso__oauth_client__keycloak__authorize_url
value: "<KC_URL>/realms/<REALM_NAME>/protocol/openid-connect/auth"
- name: CLEARML__services__login__sso__oauth_client__keycloak__access_token_url
value: "<KC_URL>/realms/<REALM_NAME>/protocol/openid-connect/token"
- name: CLEARML__services__login__sso__oauth_client__keycloak__idp_logout
value: "true"
```
#### Installing the Chart
```
helm install -n clearml \
clearml \
clearml-enterprise/clearml-enterprise \
--create-namespace \
-f overrides.yaml
```
### Install ClearML Agent Chart
#### Configuration
To configure the agent you will need to choose a Redis password and use that when setting up Redis as well
(see [Shared Redis installation](multi_tenant_k8s.md#shared-redis-installation)).
The Helm Chart must be installed with `overrides.yaml`:
```yaml
imageCredentials:
password: "<CLEARML_DOCKERHUB_TOKEN>"
clearml: clearml:
agentk8sglueKey: "<ACCESS_KEY>" # Replace the following values to use custom internal credentials.
agentk8sglueSecret: "<SECRET_KEY>" apiserverKey: ""
agentk8sglue: apiserverSecret: ""
apiServerUrlReference: "https://api.<BASE_DOMAIN>" fileserverKey: ""
fileServerUrlReference: "https://files.<BASE_DOMAIN>" fileserverSecret: ""
webServerUrlReference: "https://app.<BASE_DOMAIN>" secureAuthTokenSecret: ""
defaultContainerImage: "python:3.9" testUserKey: ""
testUserSecret: ""
``` ```
In a shell, if `openssl` is installed, you can use this simple command to generate random strings suitable as keys and secrets:
#### Installing the Chart ``` bash
openssl rand -hex 16
```bash
helm install -n <WORKLOAD_NAMESPACE> \
clearml-agent \
clearml-enterprise/clearml-enterprise-agent \
--create-namespace \
-f overrides.yaml
``` ```
### Fixed Users
To create a queue by API: Enable and configure simple login with username and password in `clearml-values.override.yaml`. This is useful for simple PoC
installations. This is an optional step in case the SSO (Identity provider) configuration is not performed.
Please note that this setup is not ideal for multi-tenant setups as fixed users will only be associated with the default tenant.
```bash ``` yaml
curl $APISERVER_URL/queues.create \ apiserver:
-H "Content-Type: application/json" \ additionalConfigs:
-H "X-Clearml-Impersonate-As:<USER_ID>" \ apiserver.conf: |
-u $APISERVER_KEY:$APISERVER_SECRET \ auth {
-d '{"name":"default"}' fixed_users {
enabled: true
pass_hashed: false
users: [
{
username: "my_user"
password: "my_password"
name: "My User"
admin: true
},
]
}
}
``` ```
## Next Steps
## ClearML AI Application Gateway Installation Once the ClearML Enterprise Server is up and running, proceed with installing the ClearML Enterprise Agent and
[AI App Gateway](appgw_install_k8s.md).
### Configuring Chart
The Helm Chart must be installed with `overrides.yaml`:
```yaml
imageCredentials:
password: "<DOCKERHUB_TOKEN>"
clearml:
apiServerKey: ""
apiServerSecret: ""
apiServerUrlReference: "https://api."
authCookieName: ""
ingress:
enabled: true
hostName: "task-router.dev"
tcpSession:
routerAddress: "<NODE_IP OR EXTERNAL_NAME>"
portRange:
start: <START_PORT>
end: <END_PORT>
```
**Configuration options:**
* **`clearml.apiServerUrlReference`:** URL usually starting with `https://api.`
* **`clearml.apiServerKey`:** ClearML server API key
* **`clearml.apiServerSecret`:** ClearML server secret key
* **`ingress.hostName`:** URL of the router we configured previously for load balancer starting with `https://`
* **`clearml.sslVerify`:** Enable or disable SSL certificate validation on apiserver calls check
* **`clearml.authCookieName`:** Value from `value_prefix` key starting with `allegro_token` in `envoy.yaml` file in ClearML server installation.
* **`tcpSession.routerAddress`**: Router external address can be an IP or the host machine or a load balancer hostname, depends on the network configuration
* **`tcpSession.portRange.start`**: Start port for the TCP Session feature
* **`tcpSession.portRange.end`**: End port for the TCP Session feature
### Installing the Chart
```bash
helm install -n <WORKLOAD_NAMESPACE> \
clearml-ttr \
clearml-enterprise/clearml-enterprise-task-traffic-router \
--create-namespace \
-f overrides.yaml
```
## Applications Installation
To install the ClearML Applications on the newly installed ClearML Enterprise control-plane, download the applications
package using the URL provided by the ClearML staff.
### Download and Extract
```
wget -O apps.zip "<ClearML enterprise applications configuration download url>"
unzip apps.zip
```
### Adjust Application Docker Images Location (Air-Gapped Systems)
ClearML applications use pre-built docker images provided by ClearML on the ClearML DockerHub
repository. If you are using an air-gapped system, these images must be available as part of your internal docker
registry, and the correct docker images location must be specified before installing the applications.
Use the following script to adjust the applications packages accordingly before installing the applications:
```
python convert_image_registry.py \
--apps-dir /path/to/apps/ \
--repo local_registry/clearml-apps
```
The script will change the application zip files to point to the new registry, and will output the list of containers
that need to be copied to the local registry. For example:
```
make sure allegroai/clearml-apps:hpo-1.10.0-1062 was added to local_registry/clearml-apps
```
### Install Applications
Use the `upload_apps.py` script to upload the application packages to the ClearML server:
```
python upload_apps.py \
--host $APISERVER_ADDRESS \
--user $APISERVER_USER --password $APISERVER_PASSWORD \
--dir apps -ml
```
## Configuring Shared Memory for Large Model Deployment
Deploying large models may fail due to shared memory size limitations. This issue commonly arises when the allocated
`/dev/shm` space is insufficient.:
```
> 3d3e22c3066f:168:168 [0] misc/shmutils.cc:72 NCCL WARN Error: failed to extend /dev/shm/nccl-UbzKZ9 to 9637892 bytes
> 3d3e22c3066f:168:168 [0] misc/shmutils.cc:113 NCCL WARN Error while creating shared memory segment /dev/shm/nccl-UbzKZ9 (size 9637888)
> 3d3e22c3066f:168:168 [0] NCCL INFO transport/shm.cc:114 -> 2
> 3d3e22c3066f:168:168 [0] NCCL INFO transport.cc:33 -> 2
> 3d3e22c3066f:168:168 [0] NCCL INFO transport.cc:113 -> 2
> 3d3e22c3066f:168:168 [0] NCCL INFO init.cc:1263 -> 2
> 3d3e22c3066f:168:168 [0] NCCL INFO init.cc:1548 -> 2
> 3d3e22c3066f:168:168 [0] NCCL INFO init.cc:1799 -> 2
```
To configure a proper SHM size you can use the following configuration in the agent `overrides.yaml`.
Replace `<SIZE>` with the desired memory allocation in GiB, based on your model requirements.
This example configures a specific queue, but you can include this setting in the `basePodTemplate` if you need to
apply it to all tasks.
```yaml
agentk8sglue:
queues:
GPUshm:
templateOverrides:
env:
- name: VLLM_SKIP_P2P_CHECK
value: "1"
volumeMounts:
- name: dshm
mountPath: /dev/shm
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: <SIZE>Gi
```

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@ -154,7 +154,7 @@ should be reviewed and modified prior to the server installation
fixed_users { fixed_users {
enabled: true, enabled: true,
users: [ users: [
{username: "support", password: "<enter password here>", admin: true, name: "allegro.ai Support User"}, {username: "support", password: "<enter password here>", admin: true, name: "ClearML Support User"},
] ]
} }
} }

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@ -2,26 +2,6 @@
title: Version 2.0 title: Version 2.0
--- ---
### ClearML Server 2.0.1
**New Features**
* New UI task creation options
* Support bash as well as python scripts
* Support file upload
**Bug Fixes**
* Fix ctrl-f does not open a search bar in UI editor modals ([ClearML Web GitHub issue #99](https://github.com/clearml/clearml-web/issues/99))
* Fix UI smoothed plots are dimmer than original plots in dark mode ([ClearML Server GitHub issue #270](https://github.com/clearml/clearml-server/issues/270))
* Fix webserver configuration environment variables don't load with single-quoted strings ([ClearML Server GitHub issue #271](https://github.com/clearml/clearml-server/issues/271))
* Fix image plots sometimes not rendered in UI
* Fix "All" tag filter not working in UI model selection modal in comparison pages
* Fix manual refresh function sometimes does not work in UI task
* Fix UI embedded plot colors do not change upon UI theme change
* Fix deleting a parameter in the UI task creation modal incorrectly removes another parameter
* Fix UI global search displays aborted tasks as completed
* Fix can't show/hide specific UI plot variants
* Fix UI breadcrumbs sometimes does not display project name
### ClearML Server 2.0.0 ### ClearML Server 2.0.0
**Breaking Changes** **Breaking Changes**

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@ -81,7 +81,7 @@ The ClearML UI provides two search options on most pages:
on the top banner of every page searches the whole WebApp for objects that match the queries as specified above and on the top banner of every page searches the whole WebApp for objects that match the queries as specified above and
returns results grouped by object (projects, tasks, models, etc.). returns results grouped by object (projects, tasks, models, etc.).
To use regular expressions, click the .* icon in the search bar. To use regular expressions, click the `.*` icon in the search bar.
![WebApp Search options](../img/webapp_search_options.png#light-mode-only) ![WebApp Search options](../img/webapp_search_options.png#light-mode-only)
![WebApp Search options](../img/webapp_search_options_dark.png#dark-mode-only) ![WebApp Search options](../img/webapp_search_options_dark.png#dark-mode-only)