Services launch#

This section provides examples of commands for launching LUNA PLATFORM services.

LUNA PLATFORM services must be launched in the following sequence:

Databases, Balancers, HASP service and other third-party party software.
Configurator
Image Store
Accounts
Licenses
Faces
Events
Python Matcher
Python Matcher Proxy. The service is disabled by default
Remote SDK
Handlers
Tasks
Sender
API
Admin

The following service are used when emulation of LUNA PLATFORM 3 is required only:

The following service are used when emulation of LUNA PLATFORM 4 is required only:

It is recommended to launch containers one by one and wait for the container status to become "up" (use the docker ps command).

Some of these services are optional and you can disable their use. It is recommended to use Events, Tasks, Sender and Admin services by default. See the "Optional services usage" section for details.

When launching each service, certain parameters are used, for example, --detach, --network, etc. See the section "Launching parameters description" for more detailed information about all launch parameters of LUNA PLATFORM services and databases.

See the "Docker commands" section for details about working with containers.

Configurator#

Run Configurator container#

Note: Configurator service configurations are not automatically migrated, unlike all other service configurations. If the configurations of the Configurator service were changed in the previous version of LP and you need to save custom values, then in the command below you need to replace the path /var/lib/luna/current/example-docker/luna_configurator/configs/luna_configurator_postgres.conf with the path with a backup copy of the configurations Configurator service /var/lib/luna/BACKUP_luna_configurator_postgres.conf (see "Save user configurations of the Configurator" section).

Use the docker run command with these parameters to launch Configurator:

docker run \
--env=PORT=5070 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /var/lib/luna/current/example-docker/luna_configurator/configs/luna_configurator_postgres.conf:/srv/luna_configurator/configs/config.conf \
-v /tmp/logs/configurator:/srv/logs \
--name=luna-configurator \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-configurator:v.2.2.28

At this stage, you can activate logging to file if you need to save them on the server (see the "Logging to server" section).

Image Store#

Image Store container launch#

Note: If you are not going to use the Image Store service, do not launch this container and disable the service utilization in Configurator. See section "Optional services usage".

Use the following command to launch the Image Store service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5020 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /var/lib/luna/image_store/:/srv/local_storage/ \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/image-store:/srv/logs \
--name=luna-image-store \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-image-store:v.3.14.10

Here -v /var/lib/luna/image_store/:/srv/local_storage/ is the data from the specified folder is added to the Docker container when it is launched. All the data from the specified Docker container folder is saved to this directory.

If you already have a directory with LP buckets you should specify it instead of /var/lib/luna/image_store/.

Accounts#

Accounts container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5170 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/accounts:/srv/logs \
--name=luna-accounts \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-accounts:v.0.3.17

Licenses#

Note: To use a trial license, it is required to launch the Licenses service on the same server where trial license is being used.

Specify license settings using Configurator#

Follow the steps below to set the settings for HASP-key or Guardant-key.

Specify HASP license settings#

Note: Perform these actions only if the HASP key is used. See the "Specify Guardant license settings" section if the Guardant key is used.

To set the license server address, follow these steps:

Go to the Configurator service interface http://<configurator_server_ip>:5070/.
Specify the "LICENSE_VENDOR" value in the "Setting name" field and click "Apply Filters".
Set the IP address of the server with your HASP key in the field "server_address" in the format "127.0.0.1".
Click "Save".

If the license is activated using the HASP key, then two parameters "vendor" and "server_address" must be specified. If you want to change the HASP protection to Guardant, then you need to add the "license_id" field.

Specify Guardant license settings#

Note: Perform these actions only if the Guardant key is used. See the "Specify HASP license settings" section if the HASP key is used.

To set the license server address, follow these steps:

Go to the Configurator service interface http://<configurator_server_ip>:5070/.
Enter the value "LICENSE_VENDOR" in the "Setting name" field and click "Apply Filters".
Set the IP address of the server with your Guardant key in the "server_address" field.
Set the license ID in the format 0x<your_license_id>, obtained in the section "Save license ID" in the License activation manual, in the "license_id" field.
Click "Save".

If the license is activated using the Guardant key, then three parameters "vendor", "server_address" and "license_id" must be specified. If you want to change the Guardant protection to HASP, then you need to delete the "license_id" field.

Licenses container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5120 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/licenses:/srv/logs \
--name=luna-licenses \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-licenses:v.0.10.28

Faces#

Faces container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5030 \
--env=WORKER_COUNT=2 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/faces:/srv/logs \
--name=luna-faces \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-faces:v.4.11.17

Events#

Events container launch#

Note: If you are not going to use the Events service, do not launch this container and disable the service utilization in Configurator. See section "Optional services usage".

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5040 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/events:/srv/logs \
--name=luna-events \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-events:v.4.12.17

Python Matcher services#

For matching tasks, you can use either only the Python Matcher service, or additionally use the Python Matcher Proxy service, which redirects matching requests to either the Python Matcher service or matching plugins. This section describes how to use Python Matcher without Python Matcher Proxy.

You need to use the Python Matcher Proxy service only if you are going to use matching plugins. Using Python Matcher Proxy and running the corresponding docker container are described in the "Use Python Matcher with Python Matcher Proxy" section.

See the description and usage of matching plugins in the administrator manual.

Use Python Matcher without Python Matcher Proxy#

The Python Matcher service with matching by the Faces DB is enabled by default after launching.

The Python Matcher service with matching by the Events is also enabled by default. You can disable it by specifying "USE_LUNA_EVENTS = 0" in the "ADDITIONAL_SERVICES_USAGE" settings of Configurator (see "Optional services usage" section). Thus, the Events service will not be used for LUNA PLATFORM.

The Python Matcher that matches using the matcher library is enabled when "CACHE_ENABLED" is set to "true" in the "DESCRIPTORS_CACHE" setting.

A single image is downloaded for the Python Matcher service and the Python Matcher Proxy service.

Python Matcher container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5100 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/python-matcher:/srv/logs \
--name=luna-python-matcher \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-python-matcher:v.1.9.17

Remote SDK#

Change the neural network model for extracting descriptors#

Some builds of LUNA PLATFORM remove the neural network models for extracting descriptors of faces and bodies, and also change the default settings for using models.

If you are upgrading from a version where neural networks were removed, and in the previous build one of the deleted models was specified in the "DEFAULT_FACE_DESCRIPTOR_VERSION" or "DEFAULT_HUMAN_DESCRIPTOR_VERSION" settings, then the Remote SDK service will not start unless you do one of the following actions:

request old neural network model from VisionLabs specialists and transfer it to new container
switch to new version of the neural network, having previously completed the Additional extraction task to re-extract existing descriptors using the new version of the neural network for their further use
switch to new version of the neural network with cessation of the use of old descriptors

See "Prepare to change the neural network version" for details.

Remote SDK container launch#

You can run the Remote SDK service utilizing CPU (set by default) or GPU.

By default, the Remote SDK service is launched with all estimators and detectors enabled. If necessary, you can disable the use of some estimators or detectors when launching the Remote SDK container. Disabling unnecessary estimators enables you to save RAM or GPU memory, since when the Remote SDK service launches, the possibility of performing these estimates is checked and neural networks are loaded into memory. If you disable the estimator or detector, you can also remove its neural network from the Remote SDK container. See the "Enable/disable several estimators and detectors" section of the administrator manual for more information.

Run the Remote SDK service using one of the following commands according to the utilized processing unit.

Run Remote SDK utilizing CPU#

Use the following command to launch the Remote SDK service using CPU:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5220 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/remote-sdk:/srv/logs \
--network=host \
--name=luna-remote-sdk \
--restart=always \
--detach=true \
dockerhub.visionlabs.ru/luna/luna-remote-sdk:v.0.6.8

Run Remote SDK utilizing GPU#

The Remote SDK service does not utilize GPU by default. If you are going to use the GPU, then you should enable its use for the Remote SDK service in the Configurator service.

If you need to use the GPU for all estimators and detectors at once, then you need to use the "global_device_class" parameter in the "LUNA_REMOTE_SDK_RUNTIME_SETTINGS" section. All estimators and detectors will use the value of this parameter if the "device_class" parameter of their settings like "LUNA_REMOTE_SDK__SETTINGS.runtime_settings" is set to "global" (by default for all estimators and detectors).

If you need to use the GPU for a specific estimator or detector, then you need to use the "device_class" parameter in sections like "LUNA_REMOTE_SDK__SETTINGS.runtime_settings".

See section "Calculations using GPU" for additional requirements for GPU utilization.

Use the following command to launch the Remote SDK service using GPU:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5220 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
--gpus device=0 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/remote-sdk:/srv/logs \
--network=host \
--name=luna-remote-sdk \
--restart=always \
--detach=true \
dockerhub.visionlabs.ru/luna/luna-remote-sdk:v.0.6.8

Here --gpus device=0 is the parameter specifies the used GPU device and enables GPU utilization. A single GPU can be utilized per Remote SDK instance. Multiple GPU utilization per instance is not available.

Run slim version of Remote SDK#

You can run a slim version of the Remote SDK service that contains only configuration files without neural networks. It is assumed that the user himself will add the neural networks he needs to the container.

The launch of the slim version of the Remote SDK service is intended for advanced users.

To successfully launch the Remote SDK container with a custom set of neural networks, you need to perform the following actions:

Request the required neural networks from VisionLabs.
Place neural networks in a folder with LUNA PLATFORM installed.
Assign appropriate rights to neural network files.
Mount neural network files to the /srv/fsdk/data folder of the Remote SDK container.
Using the arguments of the variable "EXTEND_CMD" to explicitly specify which of the neural networks should be used.

Using the "enable-all-estimators-by-default" flag for the "EXTEND_CMD" variable, you can disable the use of all neural networks (estimators) by default, and then use special flags to explicitly specify which neural networks should be used. If you do not specify this flag or set the value "--enable-all-estimators-by-default=1", the Remote SDK service will try to find all neural networks in the container. If one of the neural networks is not found, the Remote SDK service will not start.

List of available estimators:

Argument	Description
--enable-all-estimators-by-default	Enable all estimators by default.
--enable-human-detector	Simultaneous detector of bodies and bodies.
--enable-face-detector	Face detector.
--enable-body-detector	Body detector.
--enable-face-landmarks5-estimator	Face landmarks5 estimator.
--enable-face-landmarks68-estimator	Face landmarks68 estimator.
--enable-head-pose-estimator	Head pose estimator.
--enable-liveness-estimator	Liveness estimator.
--enable-fisheye-estimator	FishEye effect estimator.
--enable-face-detection-background-estimator	Image background estimator.
--enable-face-warp-estimator	Face sample estimator.
--enable-body-warp-estimator	Body sample estimator.
--enable-quality-estimator	Image quality estimator.
--enable-image-color-type-estimator	Face color type estimator.
--enable-face-natural-light-estimator	Natural light estimator.
--enable-eyes-estimator	Eyes estimator.
--enable-gaze-estimator	Gaze estimator.
--enable-mouth-attributes-estimator	Mouth attributes estimator.
--enable-emotions-estimator	Emotions estimator.
--enable-mask-estimator	Mask estimator.
--enable-glasses-estimator	Glasses estimator.
--enable-eyebrow-expression-estimator	Eyebrow estimator.
--enable-red-eyes-estimator	Red eyes estimator.
--enable-headwear-estimator	Headwear estimator.
--enable-basic-attributes-estimator	Basic attributes estimator.
--enable-face-descriptor-estimator	Face descriptor extraction estimator.
--enable-body-descriptor-estimator	Body descriptor extraction estimator.
--enable-body-attributes-estimator	Body attributes estimator.
--enable-people-count-estimator	People count estimator.
--enable-deepfake-estimator	Deepfake estimator.

See the detailed information on enabling and disabling certain estimators in the section "Enable/disable several estimators and detectors " of the administrator manual.

Below is an example of a command to assign rights to a neural network file:

chown -R 1001:0 /var/lib/luna/current/<neural_network_name>.plan

Example of a command to run Remote SDK container with mounting neural networks for face detection and face descriptor extraction:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5220 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
--env=EXTEND_CMD="--enable-all-estimators-by-default=0 --enable-face-detector=1 --enable-face-descriptor-estimator=1" \
-v /var/lib/luna/current/cnn59b_cpu-avx2.plan:/srv/fsdk/data/cnn59b_cpu-avx2.plan \
-v /var/lib/luna/current/FaceDet_v3_a1_cpu-avx2.plan:/srv/fsdk/data/FaceDet_v3_a1_cpu-avx2.plan \
-v /var/lib/luna/current/FaceDet_v3_redetect_v3_cpu-avx2.plan:/srv/fsdk/data/FaceDet_v3_redetect_v3_cpu-avx2.plan \
-v /var/lib/luna/current/slnet_v3_cpu-avx2.plan:/srv/fsdk/data/slnet_v3_cpu-avx2.plan \
-v /var/lib/luna/current/LNet_precise_v2_cpu-avx2.plan:/srv/fsdk/data/LNet_precise_v2_cpu-avx2.plan \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/remote-sdk:/srv/logs \
--network=host \
--name=luna-remote-sdk \
--restart=always \
--detach=true \
dockerhub.visionlabs.ru/luna/luna-remote-sdk:v.0.6.8

Handlers#

Note: If you are not going to use the Handlers service, do not launch this container and disable the service utilization in Configurator. See section "Optional services usage".

Handlers container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5090 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/handlers:/srv/logs \
--name=luna-handlers \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-handlers:v.3.7.1

Tasks#

Note: If you are not going to use the Tasks service, do not launch the Tasks container and the Tasks Worker container. Disable the service utilization in Configurator. See section "Optional services usage".

Tasks and Tasks Worker containers launch#

Tasks service image includes the Tasks service and the Tasks Worker. They both must be launched.

If it is necessary to use the Estimator task using a network disk, then you should first mount the directory with images from the network disk into special directories of Tasks and Tasks Worker containers. See the "Estimator task" section in the administrator manual for details.

Tasks Worker launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5051 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
--env=SERVICE_TYPE="tasks_worker" \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/tasks-worker:/srv/logs \
--name=luna-tasks-worker \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-tasks:v.3.22.9

Tasks launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5050 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/tasks:/srv/logs \
--name=luna-tasks \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-tasks:v.3.22.9

Sender#

Sender container launch#

Note: If you are not going to use the Sender service, do not launch this container and disable the service utilization in Configurator. See section "Optional services usage".

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5080 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/sender:/srv/logs \
--name=luna-sender \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-sender:v.2.12.2

API#

API container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5000 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
--name=luna-api \
--restart=always \
--detach=true \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/api:/srv/logs \
--network=host \
dockerhub.visionlabs.ru/luna/luna-api:v.6.31.6

See the example command for creating a new account in the "Account creation" section.

It is recommended that you create a schedule for the garbage collection task if you have not already created one. See "Create GC task schedule" for an example command.

Admin#

Admin container launch#

Note: If you are not going to use the Admin service, do not launch this container.

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5010 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/admin:/srv/logs \
--name=luna-admin \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-admin:v.5.7.9

Backport 3#

The section describes launching of Backport 3 service.

The service is not mandatory for utilizing LP5 and is required for emulation of LP 3 API only.

Backport 3 container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5140 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
--name=luna-backport3 \
--restart=always \
--detach=true \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/backport3:/srv/logs \
--network=host \
dockerhub.visionlabs.ru/luna/luna-backport3:v.0.11.17

User Interface 3#

The User Interface 3 is used with the Backport 3 service only.

User Interface 3 container launch#

Use the following command to launch the service:

docker run \
--env=PORT=4100 \
--env=LUNA_API_URL=http://127.0.0.1:5140 \
--name=luna-ui-3 \
--restart=always \
--detach=true \
--network=host \
-v /etc/localtime:/etc/localtime:ro \
dockerhub.visionlabs.ru/luna/luna3-ui:v.0.5.13

Here:

--env=LUNA_API_URL — Specifies the URL of the Backport 3 service.
--env=PORT — Specifies the port of the User Interface 3 service.

Backport 4#

The section describes launching of Backport 4 service.

The service is not mandatory for utilizing LP5 and is required for emulation of LP 4 API only.

Backport 4 container launch#

Use the following command to launch the service:

docker run \
--env=CONFIGURATOR_HOST=127.0.0.1 \
--env=CONFIGURATOR_PORT=5070 \
--env=PORT=5130 \
--env=WORKER_COUNT=1 \
--env=RELOAD_CONFIG=1 \
--env=RELOAD_CONFIG_INTERVAL=10 \
--name=luna-backport4 \
--restart=always \
--detach=true \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/backport4:/srv/logs \
--network=host \
dockerhub.visionlabs.ru/luna/luna-backport4:v.1.5.17

User Interface 4#

The User Interface 4 is used with the Backport 4 service only.

User Interface 4 container launch#

Note: You should have the account with account type user before launching the User Interface 4 container. Its login and password in Base64 format will be used to work with the user interface.

Use the following command to launch the service:

docker run \
--env=PORT=4200 \
--env=LUNA_API_URL=http://<server_external_ip>:5130 \
--env=BASIC_AUTH=dXNlckBtYWlsLmNvbTpwYXNzd29yZA== \
--name=luna-ui-4 \
--restart=always \
--detach=true \
--network=host \
-v /etc/localtime:/etc/localtime:ro \
dockerhub.visionlabs.ru/luna/luna4-ui:v.0.1.8

Here:

--env=PORT — Sets the port for running User Interface 4.
--env=BASIC_AUTH — Sets the Basic authorization for the account which data is displayed in the user interface.
--env=LUNA_API_URL — Sets the URL of the Backport 4 service.

You should use the external IP of the service, not localhost.

You should specify the Backport 4 service port ("5130" is set by default).