REQUIREMENTS
In order to install Learning Locker you will require a machine that has these minimum requirements:
Node (v14)
Connectivity to a Mongo instance (v4+ as of LL v7.0.0)
Connectivity to a Redis instance (v2.8.18+)
Process management system e.g. PM2 or Supervisor
GCC AND GIT
A good minimum set of requirements for Git and the GCC toolchain can be installed with the following commands:
FEDORA BASED SYSTEMS
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yum update yum -y install curl git python make automake gcc gcc-c++ kernel-devel xorg-x11-server-Xvfb git-core |
UBUNTU/DEBIAN BASED SYSTEMS
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apt-get update && apt-get upgrade apt-get -y install curl git python build-essential xvfb apt-transport-https |
NODE AND YARN INSTALLATION
There are multiple ways to install Node and Yarn (a package management system for Node). We would recommend the excellent NVM (Node Version Manager) which can be installed by following instructions here: https://github.com/creationix/nvm
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npm install -g yarn |
PROCESS MANAGEMENT
PM2 is an excellent tool that can be used to manage the Node processes. It also handles log management/rotation and can automatically restart failed services. Learning Locker comes pre-packaged with some pm2 configuration scripts.
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pm2 install pm2-logrotate pm2 set pm2-logrotate:compress true |
USER BEST PRACTICE
It is always preferable that you do not run your Node processes as the root user. For this reason we would always suggest creating a new system user under which installation, builds and services can be run.
SETUP
The Learning Locker application is divided into two logically separate codebases, each of which can be configured to talk to the same Mongo and Redis instances.
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More distribution specific information can be found inside the install script source code.
INSTALLING AND BUILDING THE LEARNING LOCKER UI, API AND WORKER
CLONE AND INSTALL
Clone the Learning Locker application into a new working directory on your server.
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npm_config_build_from_source=true yarn install --ignore-engines |
BUILD
You are now ready to build the code. You have different option here depending on how you wish to deploy the services. The codebase has 5 distinct services that can be built:
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If you wish to run the UI, API and Worker on the same machine and run CLI commands, you will probably want to build all the services in one simple command:
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yarn build-all |
CONFIGURATION
Copy the .env.example into a new .env file and edit as required.
MIGRATIONS
The database requires some indexes adding and also when upgrading you will find migrations that take care of mutating your data where required.
Once your instance is configured, run required migrations using the below command.
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yarn migrate |
INSTALLING THE XAPI SERVICE
CLONE AND INSTALL
Clone the xAPI Service into a new working directory on your server.
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yarn install --ignore-engines |
BUILD
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yarn build |
CONFIGURATION
Copy the .env.example into a new .env file and edit as required.
RUNNING THE SERVICES VIA PM2
If PM2 has been installed, you will be able to run the services using the preconfigured pm2 files in each codebase:
LEARNING LOCKER UI, API, WORKER
To start all 3 services, navigate to the LL working directory and run:
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pm2 start pm2/all.json |
XAPI SERVICE
To start the xAPI service, navigate to the xAPI Service working directory and run:
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pm2 start pm2/xapi.json |
CONFIG, STATUS AND LOGS
Note you may wish to copy and modify these pm2 config files based on your setup. Documentation can be found here.
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pm2 restart all |
RUNNING THE SERVICES MANUALLY
If you wish to use a different process management tool (e.g. Supervisor) or simply wish to run them manually for testing, you can start the services with these commands.
RUNNING THE UI
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node ui/dist/server |
RUNNING THE API
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node api/dist/server |
RUNNING THE WORKER
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node worker/dist/server |
RUNNING THE XAPI SERVICE
In your xAPI service directory
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node dist/server.js |
SERVER CONFIGURATION
The application is accessed through 3 web interfaces, the UI, API and xAPI. Each of these is configured to run on independent ports but it is recommended you setup a server to sit infront of all traffic and route accordingly. An example nginx config can be seen here: nginx.conf.example