Before upgrade#
Make sure that you are the root user before upgrade!
Before upgrading the LUNA PLATFORM, you must perform the following actions:
- See key changes from previous versions if you are upgrading from a version other than LUNA PLATFORM 5.59.0.
- Create backups.
- Prepare to change the version of the neural network to extract descriptors if necessary.
- Delete old symbolic link.
- Unpack the distribution of the new version of LUNA PLATFORM.
- Create new symbolic link.
- Change group and owner for new directories.
- Save user configurations of the Configurator service if they have changed.
- Create log directories for new services if you have previously used logging to file.
- Update license if necessary.
- Set up GPU computing if you plan to use GPU.
- Remove old containers if necessary.
Key changes from previous versions#
Note: When updating LUNA PLATFORM from a previous version, skip this section.
The following are the key changes from previous versions that you should pay attention to when updating from older versions of LUNA PLATFORM. Some of these changes require mandatory actions to be performed, otherwise the LUNA PLATFORM may not start or function incorrectly.
Not all changes are listed in the table below. See the LUNA PLATFORM release notes for details on all changes.
Version | Changes | Mandatory actions |
---|---|---|
5.62.3 | Now, by default, the neural network model 62 for extracting face descriptors is used. | Read the information described in the section "Prepare to change the neural network version", and perform certain actions before launching Remote SDK, because the default version has changed. |
5.53.0 | The VisionLabs image for PostgreSQL has been updated from version 12 to version 16. | If this image was previously used, then you need to perform the migration yourself according to official documentation. |
Create backups#
It is recommended to create the following backups:
- Backups of all databases used with LUNA PLATFORM.
- Backup of Image Store buckets.
- Backup of LUNA PLATFORM services configurations.
Creating backups will enable you to restore in case of any problems during the migration process.
Backup of PostgreSQL DMBS#
A PostgreSQL database backup is performed using the pg_dumpall or pg_dump utilities.
Use the official instructions to perform a backup.
Backup of Influx database#
An InfluxDB backup is performed using the influxd backup command.
Use the official instructions to perform a backup.
Backup of Image Store buckets#
Create a backup of buckets using the following command:
cp -r /var/lib/luna/image_store /var/lib/luna/BACKUP_image_store
Dump file with service settings#
Custom values of settings for LUNA PLATFORM services (all except the Configurator service) are automatically migrated using the Configurator service migration mechanism.
If the migration of the service for some reason has lost the user configuration or the user just wants to store the old service settings for different LP versions, then you can create a dump file.
To create a dump file, use the following command (may be executed from anywhere on your server):
wget -O /var/lib/luna/BACKUP_settings_dump.json 127.0.0.1:5070/1/dump
or
curl 127.0.0.1:5070/1/dump > /var/lib/luna/BACKUP_settings_dump.json
Important: This file will not be used during the normal installation of the LUNA PLATFORM. To apply the dumped settings use the db_create.py
script with the --dump-file
command line argument (followed with the created dump file name): base_scripts/db_create.py --dump-file settings_dump.json
. You can apply full settings dump on an empty database only. See the detailed information in the "Settings dump" section of the administrator manual.
Prepare to change the neural network version#
In some LUNA PLATFORM builds, neural network models for extracting face and body descriptors are removed, and the default model usage settings are changed. See the section "Key changes from previous versions" for more information about these changes.
If you are updating 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.
The current build of LUNA PLATFORM supports neural network models for extracting descriptors:
Object from which descriptor is extracted | Neural network models | Default model |
---|---|---|
Face | 59, 60, 62 | 62 |
Body | 107, 110 | 110 |
It is necessary to perform one of the additional actions depending on the following scenarios of the work:
Continuation of the use of missing neural networks
Request to VisionLabs an old neural network model and prepare it for transfer to the new Remote SDK container after its launch (see instructions in the section "Use non-delivery neural network model" of administrator manual).
Switching to new version of the neural network with continuation of the use of old descriptors
- Run the "Additional extraction" task before the update (see "Additional extraction task" in the administrator manual). This will convert old descriptors to a new version of the neural network.
- Specify the new version of the neural network in the settings "DEFAULT_FACE_DESCRIPTOR_VERSION" or "DEFAULT_HUMAN_DESCRIPTOR_VERSION" before launching the Remote SDK service in accordance with the section "Change neural network version using Configurator".
Switching to new version of the neural network with cessation of the use of old descriptors
Specify the new version of the neural network in the settings "DEFAULT_FACE_DESCRIPTOR_VERSION" or "DEFAULT_HUMAN_DESCRIPTOR_VERSION" before launching the Remote SDK service in accordance with the section "Change neural network version using Configurator".
If it is not necessary to extract body descriptors, then you can disable the use of the neural network using the command
--env=EXTEND_CMD="--enable-body-descriptor-estimator=0"
when launching Remote SDK container (see the detailed information in the section "Enable/disable several estimators and detectors" of the administrator manual).
Change neural network version using Configurator#
To change the version of the neural network, you must perform the following steps:
- Open the Configurator user interface
http://<configurator_server_ip>:5070
. - Enter the name of the setting "DEFAULT_FACE_DESCRIPTOR_VERSION" or "DEFAULT_HUMAN_DESCRIPTOR_VERSION" in the "Setting name" field and click "Apply Filters".
- Set the necessary neural network model in the "DEFAULT_FACE_DESCRIPTOR_VERSION" or "DEFAULT_HUMAN_DESCRIPTOR_VERSION" setting.
- Save the changes by clicking the "Save" button.
Delete old symbolic link#
Delete the symbolic link to the previous minor version directory using the following command:
rm -f /var/lib/luna/current
Distribution unpacking#
The distribution package is an archive luna_v.5.62.3, where v.5.62.3 is a numerical identifier, describing the current LUNA PLATFORM version.
The archive includes configuration files, required for installation and exploitation. It does not include Docker images for the services. They should be downloaded from the Internet.
Move the distribution package to the directory on your server before the installation. For example, move the files to /root/
directory. The directory should not contain any other distribution or license files except the target ones.
Move the distribution to the created directory.
mv /root/luna_v.5.62.3.zip /var/lib/luna
Install the unzip archiver if it is necessary.
yum install -y unzip
Go to the folder with distribution.
cd /var/lib/luna
Unzip files.
unzip luna_v.5.62.3.zip
Symbolic link creation#
Create a symbolic link.
The link indicates that the current version of the distribution file is used to run LUNA PLATFORM.
ln -s luna_v.5.62.3 current
Changing group and owner for directories#
LP services are launched inside the containers by the "luna" user. Therefore, it is required to set permissions for this user to use the mounted volumes.
Go to the LP "example-docker" directory.
cd /var/lib/luna/current/example-docker/
Create a directory to store settings.
mkdir luna_configurator/used_dumps
Set permissions for the user with UID 1001 and group 0 to use the mounted directories.
chown -R 1001:0 luna_configurator/used_dumps
Save user configurations of the Configurator#
Note: Skip this step if the Configurator settings have not been changed.
The configurations of the Configurator service are not automatically migrated, unlike the configurations of all other services.
If your previous LP version was used with non-default Configurator service configurations, back up your "luna_configurator_postgres.conf" config file in the separate directory on your server.
cp /var/lib/luna/<your_previous_lp_version>/example-docker/luna_configurator/configs/luna_configurator_postgres.conf /var/lib/luna/BACKUP_luna_configurator_postgres.conf
This backup must be mounted to the Configurator service container that is being run.
If you are not sure if the Configurator service configurations have changed, you can compare the created backup with the Configurator configurations from the current distribution using the following command:
diff /var/lib/luna/current/example-docker/luna_configurator/configs/luna_configurator_postgres.conf /var/lib/luna/BACKUP_luna_configurator_postgres.conf
Create log directory for new services#
Skip this section if no logs were previously stored on the server.
In the new version of LUNA PLATFORM, new services could appear, for which you need to create directories with logs. It depends on the version from which you are upgrading. For example, version 5.30.0 introduced the Accounts service.
See "Logging to server" section if you have not previously used logging to a file, but want to enable it.
Following are the commands to create directories for all existing services. These commands will create and assign permissions only to missing directories.
mkdir -p /tmp/logs/configurator /tmp/logs/image-store /tmp/logs/accounts /tmp/logs/faces /tmp/logs/licenses /tmp/logs/events /tmp/logs/python-matcher /tmp/logs/handlers /tmp/logs/remote-sdk /tmp/logs/tasks /tmp/logs/tasks-worker /tmp/logs/sender /tmp/logs/api /tmp/logs/admin /tmp/logs/backport3 /tmp/logs/backport4
chown -R 1001:0 /tmp/logs/configurator /tmp/logs/image-store /tmp/logs/accounts /tmp/logs/faces /tmp/logs/licenses /tmp/logs/events /tmp/logs/python-matcher /tmp/logs/handlers /tmp/logs/remote-sdk /tmp/logs/tasks /tmp/logs/tasks-worker /tmp/logs/sender /tmp/logs/api /tmp/logs/admin /tmp/logs/backport3 /tmp/logs/backport4
If you need to use the Python Matcher Proxy service, then you need to additionally create the /tmp/logs/python-matcher-proxy
directory and set its permissions.
License update#
To update the license, follow these steps:
- Follow the steps from license activation manual.
- Set settings for HASP license or Guardant license before starting Licenses container.
Actions from License activation manual#
Open the license activation manual and follow the necessary steps.
Note: This action is mandatory. The license will not work without following the steps to activate the license from the corresponding manual.
Note. When updating Guardant Control Center, you must re-issue the license key.
Calculations using GPU#
You can use GPU for the general calculations performed by Remote SDK.
Skip this section if you are not going to utilize GPU for your calculations.
You need to install NVIDIA Container Toolkit to use GPU with Docker containers. The example of the installation is given below.
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | tee /etc/yum.repos.d/nvidia-docker.repo
yum install -y nvidia-container-toolkit
systemctl restart docker
Check the NVIDIA Container toolkit operating by running a base CUDA container (this container is not provided in the LP distribution and should be downloaded from the Internet):
docker run --rm --gpus all nvidia/cuda:11.4.3-base-centos7 nvidia-smi
See the NVIDIA documentation for additional information.
Attributes extraction on the GPU is engineered for maximum throughput. The input images are processed in batches. This reduces computation cost per image but does not provide the shortest latency per image.
GPU acceleration is designed for high load applications where request counts per second consistently reach thousands. It won’t be beneficial to use GPU acceleration in non-extensively loaded scenarios where latency matters.
Remove old containers (optional)#
Note: Removing old containers is not necessary when preparing your environment using the Storages utility. It is enough to simply limit the number of queries to the database, but in this case it is necessary to understand certain consequences. See the "Recommendations services behavior during environment preparation" section in the Storages utility manual.
Before launching the containers of the current minor version, stop all LUNA PLATFORM related containers of the previous minor version. It is not necessary to delete third-party services containers.
For example, to remove LP containers only use the following command:
docker container rm -f luna-configurator luna-backport3 luna-backport4 luna-sender luna-tasks luna-handlers luna-remote-sdk luna-python-matcher luna-events luna-licenses luna-faces luna-image-store luna-ui-3 luna-ui-4 luna-admin luna-api luna-tasks-worker luna-accounts luna-lambda
To see the containers names or IDs, use the following command:
docker ps -a
It is also recommended to delete old images of the containers to free space. You can use the following command to delete all unused images.
If there is enough space on the server it is recommended to perform this action only after new version of LP is successfully launched.
The command deletes all the unused images, not only the images related to LP.
docker image prune -a -f