Services launch#

This section gives examples for:

Databases tables creation
Buckets creation
Launching of containers

The commands are given in the order they must be performed.

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

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

General container launching parameters#

When launching a Docker container for a LUNA PLATFORM service you should specify additional parameters required for the service launching.

The parameters specific for a particular container are described in the section about this container launching.

All the parameters given in the service launching example are required for proper service launching and utilization.

When launching containers, you should specify a link to the image required for the container launching. This image will be downloaded from the VisionLabs registry. Before that, you should login to the registry.

Enter login .

docker login dockerhub.visionlabs.ru --username <username>

After running the command, you will be prompted for a password. Enter password.

The login and password are received from VisionLabs.

In the docker login command, you can enter the login and password at the same time, but this does not guarantee security because the password can be seen in the command history.

Description of launch parameters#

Common parameters for launching containers are described in this section.

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

docker run - the command for running the selected image as a new container.

dockerhub.visionlabs.ru/luna/<service-name>:<version> - the parameter specifies the image required for the container launching.

Links to download the container images you need are available in the description of the corresponding container launching.

--network=host - the parameter specifies that a network is not simulated and the server network is used. If you need to change the port for third-party party containers, you should change this string to -p 5440:5432. Where the first port 5440 is the local port and 5432 is the port used inside the container. The example is given for PostgreSQL.

--env= - the parameter specifies the environment variables required to run a container. The following general values are specified:

CONFIGURATOR_HOST=127.0.0.1 - the host where the Configurator service is running. The localhost is set in the case when the container is launched on the same server with the Configurator service.
CONFIGURATOR_PORT=5070 - the port where the Configurator service is listening. The 5070 port is used by default.
PORT=<Port_of_the_service> - the port where the service will listen.
WORKER_COUNT - specifies the number of worker processes for the service.
RELOAD_CONFIG enables auto-reload of configurations for the service when set to "1". See the "Automatic configurations reload" section in the LUNA PLATFORM 5 administrator manual.
RELOAD_CONFIG_INTERVAL specifies the configurations check period (10 seconds by default). See the "Automatic configurations reload" section in the LUNA PLATFORM 5 administrator manual.

--name=<service_container_name> - the parameter specifies the name of the launched container. The name must be unique. If there is a container with the same name, an error will occur.

--restart=always - the parameter specifies a restart policy. The daemon will always restart the container regardless of the exit status.

--detach=true - run the container in the background mode.

-v - the volume parameter enables you to mount the content of a server folder into a volume in the container. Thus their contents will synchronize. The following general data is mounted:

/etc/localtime:/etc/localtime:ro - sets the current time zone used by the system in the container.
/tmp/logs/<service>:/srv/logs/ - enables copying of the folder with service logs to your server /tmp/logs/<service> directory. You can change the directory where the logs will be saved according to your needs.

Description of database creation parameters#

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/<service>:/srv/logs/ \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/<service-name>:<version> \
python3 ./base_scripts/db_create.py --luna-config http://localhost:5070/1

The following parameters are used when containers are launched for database migration and creation procedures.

--rm - the parameter specifies if the container is deleted after all the specified scripts finish processing

python3 ./base_scripts/db_create.py - the parameter specifies Python version and a script db_create.py launched in the container. The script is used for the database structure creation. --luna-config http://localhost:5070/1 - the parameter specifies where the launched script should receive configurations. By default, the service requests configurations from the Configurator service.

Run third-party services#

This section describes the launching of databases and message queues in docker containers. They must be launched before LP services.

InfluxDB OSS 2#

InfluxDB 2.0.8-alpine is required for LP monitoring purpose with data visualization using Grafana (for more information, see the "Monitoring" section in the administrator’s manual).

Note! If you already have InfluxDB 2.0.8-alpine installed, skip this step.

If a container with an older version of InfluxDB is running, use the delete container command:

docker container rm -f influxdb

Migration from version 1#

InfluxDB provides built-in tools for migration from version 1 to version 2. See documentation:

https://docs.influxdata.com/influxdb/v2.0/upgrade/v1-to-v2/docker/

Run InfluxDB container#

Use the docker run command with these parameters:

docker run \
-e DOCKER_INFLUXDB_INIT_MODE=setup \
-e DOCKER_INFLUXDB_INIT_BUCKET=luna_monitoring \
-e DOCKER_INFLUXDB_INIT_USERNAME=luna \
-e DOCKER_INFLUXDB_INIT_PASSWORD=password \
-e DOCKER_INFLUXDB_INIT_ORG=luna \
-e DOCKER_INFLUXDB_INIT_ADMIN_TOKEN=kofqt4Pfqjn6o0RBtMDQqVoJLgHoxxDU mmhiAZ7JS6VmEnrqZXQhxDhad8AX9tmiJH6CjM7Y1U8p5eSEocGzIA== \
-v /etc/localtime:/etc/localtime:ro \
-v /var/lib/luna/current/example-docker/influx:/var/lib/influxdb2 \
--restart=always \
--detach=true \
--network=host \
--name influxdb \
dockerhub.visionlabs.ru/luna/influxdb:2.0.8-alpine

Grafana#

Grafana is required to visualize LP monitoring. You can use it to create dashboards of the LP state (for more information, see the "LUNA Dashboards" section in the administrator manual).

To work with Grafana you need to use InfluxDB version 2.

Note! If you already have Grafana installed or are not going to use it, skip this step.

Run Grafana container#

Use the docker run command with these parameters to run Grafana:

docker run \
--restart=always \
--detach=true \
--network=host \
--name=grafana \
-v /etc/localtime:/etc/localtime:ro \
dockerhub.visionlabs.ru/luna/luna-dashboards:v.0.0.5

When you launch Grafana, LP dashboards are automatically created.

Use "http://IP_ADDRESS:3000" to go to the Grafana web interface when the Grafana and Influx containers are running.

Grafana Loki#

Grafana Loki is a log aggregation system that enables you to flexibly work with LUNA PLATFORM logs. The Promtail agent is used to deliver LUNA PLATFORM logs to Grafana Loki (for more information, see the "Grafana Loki" section in the administrator manual).

Note! Grafana Loki requires Grafana to be running. If you already have Grafana Loki installed or are not going to use it, skip this step.

Run Grafana Loki container#

Use the docker run command with these parameters to run Grafana Loki:

docker run \
--name=grafana-loki \
--restart=always \
--detach=true \
--network=host \
-v /etc/localtime:/etc/localtime:ro \
dockerhub.visionlabs.ru/luna/loki:2.7.1

Run Promtail container#

Use the docker run command with these parameters to run Promtail:

docker run \
-v /var/lib/luna/current/extras/utils/promtail/promtail.yml:/etc/promtail/luna.yml \
-v /var/lib/docker/containers:/var/lib/docker/containers \
-v /etc/localtime:/etc/localtime:ro \
--name=promtail \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/promtail:2.7.1 \
-config.file=/etc/promtail/luna.yml -client.url=http://127.0.0.1:3100/loki/api/v1/push -client.external-labels=job=containerlogs,pipeline_id=,job_id=,version=

-v /var/lib/luna/current/extras/utils/promtail/promtail.yml:/etc/promtail/luna.yml - mounting the configuration file to the Promtail container

-config.file=/etc/promtail/luna.yml - flag with the address of the configuration file

-client.url=http://127.0.0.1:3100/loki/api/v1/push - flag with the address of deployed Grafana Loki

-client.external-labels=job=containerlogs,pipeline_id=,job_id=,version= - static labels to add to all logs sent to Grafana Loki

PostgreSQL#

If you already have PostgreSQL installed, skip this step.

Use the following command to launch PostgreSQL.

docker run \
--env=POSTGRES_USER=luna \
--env=POSTGRES_PASSWORD=luna \
--shm-size=1g \
-v /var/lib/luna/current/example-docker/postgresql/data/:/var/lib/postgresql/data/ \
-v /var/lib/luna/current/example-docker/postgresql/entrypoint-initdb.d/:/docker-entrypoint-initdb.d/ \
-v /etc/localtime:/etc/localtime:ro \
--name=postgres \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/postgis-vlmatch:12

-v /var/lib/luna/current/example-docker/postgresql/entrypoint-initdb.d/:/docker-entrypoint-initdb.d/ \ - the "docker-entrypoint-initdb.d" script includes the commands for the creation of services databases. During database creation, a default username and password are automatically used.

-v /var/lib/luna/current/example-docker/postgresql/data/:/var/lib/postgresql/data/ - the volume command enables you to mount the "data" folder to the PostgreSQL container. The folder on the server and the folder in the container will be synchronized. The PostgreSQL data from the container will be saved to this directory.

--network=host - if you need to change the port for PotgreSQL, you should change this string to -p 5440:5432. Where the first port 5440 is the local port and 5432 is the port used inside the container.

Note! You should create all the databases for LP services manually if you are going to use an already installed PostgreSQL.

Redis#

If you already have Redis installed, skip this step.

Use the following command to launch Redis.

docker run \
-v /etc/localtime:/etc/localtime:ro \
--name=redis \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/redis:7.0.5-alpine3.16

Configurator#

Optional services usage#

The listed below services are not mandatory for LP. You can disable them if their functionality is not required for your tasks.

Use the "ADDITIONAL_SERVICES_USAGE" section in the API service settings in the Configurator service to disable unnecessary services.

Optional services

Service	Dependent services
Events	API, Admin, Handlers, Tasks.
Tasks	API, Admin, Handlers
Sender	API, Admin, Handlers
Python Matcher Proxy (disabled by default)	API, Admin, Handlers, Tasks.

The API service does not depend on the state of the Admin, Backport3, Backport4, User Interface 3 and User Interface 4 services. These services do not need to be changed in the Configurator service, it is enough just not to launch them.

You can use the dump file provided in the distribution package to enable/disable services from the "Optional services" table before Configurator launch.

vi /var/lib/luna/current/extras/conf/platform_settings.json

You must restart a dependent service after changing its parameters if the service was already launched.

Configurator database migration#

Migration from the previous LP build to LP build v.5.35.0 is described in this section.

The following instruction for Configurator DB migration assumes that you already have settings migration revision set in your database. This revision is set using the configs.migrate head script. This script is included in the installation manuals of LP, starting with build 5.1.1. If you have performed installation according to the manual, you do not need to perform additional actions.Settings migration will be performed automatically.

If there is no revision, you should recreate the database structure. See the LP 5 installation manual section "Configurator DB tables creation" for instructions. Then you should specify all the required settings manually.

The migration from version 5.1.0 is described in "LP_Docker_Upgrade_Manual.html" in the distribution package of version 5.1.1. You can update your Configurator database using this instruction and distribution package of version 5.1.1. Otherwise, you should recreate the database structure for the Configurator service and specify all the required settings manually. See the LP 5 installation manual section "Configurator DB tables creation" for instructions.

Migration from pre-release builds (builds before v.5.1.0) of LP is not provided. You should transfer all the required settings to the Configurator DB of 5.1.1 build manually.

Configurator DB tables creation#

When upgrading the Configurator database with existing settings, you should perform database structure migration and saved settings migration.

Your current database should already have settings migration revision.

Use the docker run command with these parameters to create the Configurator database tables.

docker run \
-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 \
--network=host \
-v /tmp/logs/configurator:/srv/logs \
--rm \
--entrypoint bash \
dockerhub.visionlabs.ru/luna/luna-configurator:v.2.0.78 \
-c "alembic upgrade head; cd /srv/luna_configurator/configs/configs/; python3 -m configs.migrate --config /srv/luna_configurator/configs/config.conf head;"

alembic upgrade head; - upgrades already existing database structure.

python3 -m configs.migrate head; - performs settings migrations in Configurator DB and sets revision for migration. The revision will be required during the upgrade to the new LP5 build.

Run Configurator container#

Note. If you need to save the old configuration of the Configurator service, replace /var/lib/luna/current/example-docker/luna_configurator/configs/luna_configurator_postgres.conf with the absolute path to your previous luna_configurator_postgres.conf backup file (see "Upgrade notes" 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.2.0.78

Configuring InfluxDB#

If you are going to use InfluxDB OSS 2, then you need to update the monitoring settings in Configurator service.

There are the following settings for InfluxDB OSS 2:

"send_data_for_monitoring": 1,
"use_ssl": 0,
"flushing_period": 1,
"host": "127.0.0.1",
"port": 8086,
"organization": "<ORGANIZATION_NAME>",
"token": "<TOKEN>",
"bucket": "<BUCKET_NAME>",
"version": <DB_VERSION>

You can update InfluxDB settings in the Configurator service by following these steps:

Open /var/lib/luna/current/extras/conf/influx2.json.
Set required data in "organization", "token", "bucket", "version" fields.
Save changes.
Copy the file to the influxDB container:

docker cp /var/lib/luna/current/extras/conf/influx2.json luna-configurator:/srv/

Update settings in the Configurator.

docker exec -it luna-configurator python3 ./base_scripts/db_create.py --dump-file /srv/influx2.json

You can also manually update settings in the Configurator service user interface.

Image Store#

Image Store container launch#

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/current/example-docker/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.3.7.0

-v /var/lib/luna/current/example-docker/image_store/:/srv/local_storage/ - 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/current/example-docker/image_store/.

Buckets creation#

Buckets are required to store data in Image Store. The Image Store service should be launched before the commands execution.

When upgrading from the previous version, it is recommended to launch the bucket creation commands one more time. Hence you make sure that all the required buckets were created.

If the "error_code":13006,"desc":"Unique constraint error","detail":"Bucket with name 'task-result' already exist"} error appears during launching of the listed above commands, the bucket is already created.

There are two ways to create buckets in LP.

You can run the listed above scripts to create buckets.

Run this script to create general buckets:

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/api:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-api:v.6.10.0 \
python3 ./base_scripts/lis_bucket_create.py -ii --luna-config http://localhost:5070/1

If you are going to use the Tasks service, use the following command to additionally create the "task-result" in the Image Store service:

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/tasks:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-tasks:v.3.13.2 \
python3 ./base_scripts/lis_bucket_create.py -ii --luna-config http://localhost:5070/1

If you are going to use the portraits, use the following command to additionally create the "portraits".

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/api:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-backport3:v.0.6.9 \
python3 ./base_scripts/lis_bucket_create.py -ii --luna-config http://localhost:5070/1

You can use direct requests to create required buckets.

The curl utility is required for the following requests.

The "visionlabs-samples" bucket is used for face samples storage. The bucket is required for LP utilization.

curl -X POST http://127.0.0.1:5020/1/buckets?bucket=visionlabs-samples

The "portraits" bucket is used for portraits storage. The bucket is required for Backport 3 utilization.

curl -X POST http://127.0.0.1:5020/1/buckets?bucket=portraits

The "visionlabs-bodies-samples" bucket is used for human bodies samples storage. The bucket is required for LP utilization.

curl -X POST http://127.0.0.1:5020/1/buckets?bucket=visionlabs-bodies-samples

The "visionlabs-image-origin" bucket is used for source images storage. The bucket is required for LP utilization.

curl -X POST http://127.0.0.1:5020/1/buckets?bucket=visionlabs-image-origin

The "visionlabs-objects" bucket is used for objects storage. The bucket is required for LP utilization.

curl -X POST http://127.0.0.1:5020/1/buckets?bucket=visionlabs-objects

The "task-result" bucket for the Tasks service. Do not use it if you are not going to use the Tasks service.

curl -X POST http://127.0.0.1:5020/1/buckets?bucket=task-result

Accounts#

Accounts DB tables creation#

Note! Accounts migration (upgrading from 5.2.0...5.28.0 only). Perform the steps below only if you are upgrading from previous version, where the Admin service was not used. If you have used the Admin service before, skip this section and make sure you have completed the steps in the "Accounts database migration" section.

Use the following command to create Accounts DB tables:

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/accounts:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-accounts:v.0.0.19 \
python3 ./base_scripts/db_create.py --luna-config http://localhost:5070/1

Accounts database migration#

You need to execute migration scripts to update your Accounts database structure.

It is recommended to create the back up of your database before applying any changes.

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/accounts:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-accounts:v.0.0.19 \
alembic -x luna-config=http://127.0.0.1:5070/1 upgrade head

Admin DB transformation#

Note! Accounts migration (upgrading from 5.2.0...5.28.0 only). In LUNA PLATFORM 5.30.0, the database that stores information about accounts has changed. In LUNA PLATFORM versions 5.2.0...5.28.0, information was stored in the Admin database (luna_admin database), and in versions 5.30.0 and higher, information is stored in the Accounts database (luna_accounts database). If you are upgrading from versions 5.2.0...5.28.0 to the current version, then the script above will transform the luna_admin database to work with new accounts (the database name will remain the same).

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.0.0.19

Licenses#

Licenses container launch#

Make sure that you have specified the license server address in the "hasp_30147.ini" file. See section "Specify license server address for LP".

Add the access right for the "luna" user to the "hasp_redirect" directory.

chown -R 1001:0 /var/lib/luna/current/example-docker/hasp_redirect/

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 \
-v /var/lib/luna/current/example-docker/hasp_redirect/hasp_30147.ini:/home/luna/.hasplm/hasp_30147.ini \
--name=luna-licenses \
--restart=always \
--detach=true \
--network=host \
dockerhub.visionlabs.ru/luna/luna-licenses:v.0.3.85

Faces#

Faces database migration#

You need to execute migration scripts to update your Faces database structure.

It is recommended to create the back up of your database before applying any changes.

Run the following command to perform the Faces DB migration.

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/faces:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-faces:v.4.7.0 \
alembic -x luna-config=http://127.0.0.1:5070/1 upgrade head

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.4.7.0

Events#

Events database migration#

You need to execute migration scripts to update your Events database structure.

It is recommended to create the back up of your database before applying any changes.

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/events:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-events:v.4.5.3 \
alembic -x luna-config=http://127.0.0.1:5070/1 upgrade head

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.4.5.3

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.

Note. 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 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.

Note. 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.1.3.0

Handlers#

Changing the neural network model for extracting descriptors#

Note. If you are upgrading from a 5.34.0 version of LUNA PLATFORM, skip the steps below.

Note. In the LUNA PLATFORM 5.34.0 build, the neural network models 54, 56, 57, 104 and 106 for extracting face and body descriptors were removed from the Handlers container. In addition, the neural network model for extracting body descriptor by default has changed from 104 to 107. If you are upgrading from builds 5.2.0 higher and any of listed models were used in previous builds, then the launch of the Handlers service will fail if you do not perform the additional steps described below.

There are available models of neural networks for extracting descriptors in the current LUNA PLATFORM build:

Object from which descriptor is extracted	Neural network models	Default model
Face	58, 59, 60	59
Body	102, 105, 107	107

Before launching the Handlers container, you need to make sure that the "DEFAULT_FACE_DESCRIPTOR_VERSION" and "DEFAULT_HUMAN_DESCRIPTOR_VERSION" parameters of the Handlers service are set to the neural network models that exist in the Handlers container.

This can be done using the following steps:

go to the Configurator service interface http://<configurator_server_ip>:5070/
enter the value "DEFAULT_FACE_DESCRIPTOR_VERSION" in the "Setting name" field and click "Apply Filters"
make sure that the neural network model for extracting descriptors of faces that exist in the Handlers container is used (see the table above)
enter the value "DEFAULT_HUMAN_DESCRIPTOR_VERSION" in the "Setting name" field and click "Apply Filters"
make sure that the neural network model for extracting descriptors of bodies that exist in the Handlers container is used (see the table above)

If the neural network models are set in the settings, that exist in the Handlers container of the current version, then go to the "Handlers database migration" section.

If the neural network models are set in the settings, that not exist in the Handlers container of the current version, then do one of the following:

Operation 1. Manually change the setting value "DEFAULT_FACE_DESCRIPTOR_VERSION" or "DEFAULT_HUMAN_DESCRIPTOR_VERSION". To do this, go to the found field in the settings (see above), set the existing model and click "Save". After changing the neural network model for extracting face/body descriptors, you must run the "Additional extraction" task after starting the Admin service (see the "Launch re-extraction task" section in the administrator manual). Otherwise, search and matching by old descriptors will not be available.

Operation 2. Request an old neural network model from VisionLabs and transfer it to the Handlers container according to the instructions described in the section "Use non-delivery neural network model" of the administrator manual.

Operation 3 (relevant for neural networks of bodies). Disable the use of a neural network to extract a body descriptor using the following command when starting the Handlers container:

docker run \
...
--env=EXTEND_CMD="--enable-body-descriptor-estimator=0" \
...

This command does not prohibit the estimation of body parameters (upper/lower body, sleeve length, presence of a backpack, etc.). See "Enable/disable several estimators and detectors" section of the administrator manual for details.

Handlers database migration#

You need to execute migration scripts to update your Handlers database structure.

It is recommended to create the back up of your database before applying any changes.

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/handlers:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-handlers:v.2.13.2 \
alembic -x luna-config=http://127.0.0.1:5070/1 upgrade head

Handlers container launch#

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

By default, the Handlers service is launched with all estimators and detectors enabled. If necessary, you can disable the use of some estimators or detectors when launching the Handlers container. Disabling unnecessary estimators enables you to save RAM or GPU memory, since when the Handlers 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 Handlers container. See the "Enable/disable several estimators and detectors" section of the administrator manual for more information.

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

Run Handlers utilizing CPU#

Use the following command to launch the Handlers service using CPU:

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.2.13.2

Run Handlers utilizing GPU#

The Handlers service does not utilize GPU by default. If you are going to use the GPU, then you should enable its use for the Handlers 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_HANDLERS_RUNTIME_SETTINGS" section. All estimators and detectors will use the value of this parameter if the device_class parameter of their settings like "LUNA_HANDLERS__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_HANDLERS__SETTINGS.runtime_settings".

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

Use the following command to launch the Handlers service using GPU:

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 \
--gpus device=0 \
-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.2.13.2

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

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 database migration#

You need to execute migration scripts to update your Tasks database structure.

It is recommended to create the back up of your database before applying any changes.

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/tasks:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-tasks:v.3.13.2 \
alembic -x luna-config=http://127.0.0.1:5070/1 upgrade head

Tasks and Tasks worker containers launch#

Luna Tasks Docker image includes the Tasks service and the Tasks worker. They both must be launched.

The "task-result" bucket should be created for the Tasks service before the service launch. The buckets creation is described in the "Buckets creation".

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.3.13.2

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.3.13.2

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.2.5.8

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.6.10.0

Account creation using API service#

The account is created using an HTTP request to the "create account" resource of the API service.

You can also create an account using the Admin service. This method requires an existing login and password (or the default login and password) and enables you to create an "admin" account. See the "Admin service" section of the administrator manual for details.

To create the account using a request to the API service, you need to provide the following mandatory data:

login — email address
password — password
account_type — account type ("user" or "advanced_user")

Create the account using your authentication details.

Note! Accounts migration (upgrading from 5.2.0...5.28.0 only). If you want to keep the ability to use the "account_id" that was used as the "Luna-Account-Id" header in versions 5.2.0...5.28.0 (without creating an account in the Admin service), then you need to link the old "account_id" to the account being created.

Example of CURL-request to the "create account" resource:

curl --location --request POST 'http://127.0.0.1:5000/6/accounts' \
--header 'Content-Type: application/json' \
--header 'Luna-Account-Id: <your_old_account_id>' \
--data '{
  "login": "user@mail.com",
  "password": "password",
  "account_type": "user",
  "description": "description"
}'

It is necessary to replace the authentication data from the example with your own.

To work with tokens, you must have an account.

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.4.8.0

Monitoring data about the number of executed requests is saved in the luna-admin bucket of the InfluxDB. To enable data saving use the following command:

docker exec -it luna-admin python3 ./base_scripts/influx2_cli.py create_usage_task --luna-config http://127.0.0.1:5070/1

Backport 3#

The section describes launching of Backport 3 service.

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

Backport 3 database migration#

You need to execute migration scripts to update your Backport 3 DB structure.

It is recommended to create the back up of your database before applying any changes.

Run the following command to perform the Backport 3 DB migration.

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/backport3:/srv/logs \
--rm \
--network=host \
dockerhub.visionlabs.ru/luna/luna-backport3:v.0.6.9 \
alembic -x luna-config=http://127.0.0.1:5070/1 upgrade head

Accounts and tokens migration#

Note! Accounts migration (upgrading from 5.2.0...5.28.0 only). Use the following command to migrate existing accounts and tokens from Backport 3 previous version:

docker run \
-v /etc/localtime:/etc/localtime:ro \
-v /tmp/logs/backport3:/srv/logs \
--rm \
--network=host \
--entrypoint bash dockerhub.visionlabs.ru/luna/luna-backport3:v.0.6.9 -c "cd ./base_scripts/migrate_accounts/ && pip3 install -r requirements-postgres.txt && python3 ./run.py --backport_db_url postgres://luna:luna@127.0.0.1:5432/luna_backport3 --accounts_db_url postgres://luna:luna@127.0.0.1:5432/luna_admin"

python3 ./run.py - running the script for migrating accounts and tokens

--backport_db_url postgres://luna:luna@127.0.0.1:5432/luna_backport3 - luna_backport3 DB address flag

--accounts_db_url postgres://luna:luna@127.0.0.1:5432/luna_admin - luna_admin DB address flag

When migrating API and Faces service databases, all Backport 3 accounts will be migrated and stored in the database of the Accounts service. All migrated accounts will be of type "user". The fields "password", "email" and "organization_name" will be transferred from the "account" table of the Backport 3 database to the "account" table of the Accounts database under new names - "password", "login" and "description" respectively. Tokens will remain stored in the Backport3 database, but their identifier will also be entered in the Accounts database, where the necessary permissions will be automatically set.

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.0.6.9

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.0.5.6

--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.

Note. 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.1.2.71

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.0.1.0

--env=PORT - specifies 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 - specifies 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).

Services launch#

General container launching parameters#

Login to registry#

Description of launch parameters#

Description of database creation parameters#

Run third-party services#

InfluxDB OSS 2#

Migration from version 1#

Run InfluxDB container#

Grafana#

Run Grafana container#

Grafana Loki#

Run Grafana Loki container#

Run Promtail container#

PostgreSQL#

Redis#

Configurator#

Optional services usage#

Configurator database migration#

Configurator DB tables creation#

Run Configurator container#

Configuring InfluxDB#

Image Store#

Image Store container launch#

Buckets creation#

Accounts#

Accounts DB tables creation#

Accounts database migration#

Admin DB transformation#

Accounts container launch#

Licenses#

Licenses container launch#

Faces#

Faces database migration#

Faces container launch#

Events#

Events database migration#

Events container launch#

Matcher services#

Use Python Matcher without Python Matcher Proxy#

Python Matcher container launch#

Handlers#

Changing the neural network model for extracting descriptors#

Handlers database migration#

Handlers container launch#

Run Handlers utilizing CPU#

Run Handlers utilizing GPU#

Tasks#

Tasks database migration#

Tasks and Tasks worker containers launch#

Tasks Worker launch#

Tasks launch#

Sender#

Sender container launch#

API#

API container launch#

Account creation using API service#

Admin#

Admin container launch#

Backport 3#

Backport 3 database migration#

Accounts and tokens migration#

Backport 3 container launch#

User Interface 3#

User Interface 3 container launch#

Backport 4#

Backport 4 container launch#

User Interface 4#

User Interface 4 container launch#