These are the prerequisites to setting up a full private LTE Magma deployment. Additional prerequisites for developers can be found in the contributor guide on Github.
Currently, the main development operating system (OS) is macOS. Documentation is mainly focused on that operating system.
To develop on a Linux OS, the package manager (brew for macOS) will need to be replaced by the appropriate package manager for the respective Linux distribution (e.g. apt, yum, etc.).
Windows OS is currently not supported as developing environment, due to some dependencies on Linux-only tools during setup, such as Ansible or
fcntl. You can try to use a DevContainer setup though.
Development can occur from multiple OS's, where macOS and Ubuntu are explicitly supported, with additional polish for macOS.
Note: If you still want to contribute from a different OS, you will need to figure out some workarounds to install the tooling. You might want to follow one of the guides, either macOS or Ubuntu, and replicate the steps in your preferred OS.
Install the following tools
- Docker and Docker Compose
brew install firstname.lastname@example.org pyenv # NOTE: this assumes you're using zsh. # See the above pyenv install instructions if using alternative shells. echo 'export PATH="/email@example.com/bin:$PATH"' >> ~/.zshrc echo 'eval "$(pyenv init --path)"' >> ~/.zprofile echo 'eval "$(pyenv init -)"' >> ~/.zshrc exec $SHELL # IMPORTANT: close your terminal tab and open a new one before continuing pyenv install 3.8.10 pyenv global 3.8.10 pip3 install ansible fabric3 jsonpickle requests PyYAML vagrant plugin install vagrant-vbguest vagrant-disksize vagrant-reload
Note: In the case where installation of
fabric3through pip was unsuccessful, try switching to other package installers. Try running
brew install fabric.
You should start Docker Desktop and increase the memory allocation for the Docker engine to at least 4GB (Preferences -> Resources -> Advanced). If you are running into build/test failures with Go that report "signal killed", you likely need to increase Docker's allocated resources.
Install the following tools
- Docker and Docker Compose
- Vagrant (Install by downloading the
.debfile. Installing via the command line using
apt-getcan currently cause an issue with OpenSSL. See also this discussion.)
Install golang version 18.
Download the tar file.
Extract the archive you downloaded into
/usr/local, creating a Go tree in
sudo rm -rf /usr/local/go && sudo tar -C /usr/local -xzf go1.18.3.linux-amd64.tar.gz
/usr/local/go/binto the PATH environment variable.
Verify that you've installed Go by opening a command prompt and typing the following command
You should expect something like this
go version go1.18.3 linux/amd64
Update system packages.
sudo apt update -y
Install some necessary dependencies. If you are using
apt install -y make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev libncursesw5-dev xz-utils tk-dev libffi-dev liblzma-dev python-openssl git
Note: For Ubuntu 22.04, use
git clone https://github.com/pyenv/pyenv.git ~/.pyenv
echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc echo -e 'if command -v pyenv 1>/dev/null 2>&1; then\n eval "$(pyenv init -) "\nfi' >> ~/.bashrc exec "$SHELL"
Create python virtual environment version 3.8.10.
pyenv install 3.8.10 pyenv global 3.8.10
pyenvinstallation might fail with a segmentation fault. Try using
CFLAGS="-O2" pyenv install 3.8.10in that case.
pip3and its dependencies.
sudo apt install python3-pip
Install the following dependencies
pip3 install ansible fabric3 jsonpickle requests PyYAML
vagrant plugin install vagrant-vbguest vagrant-disksize vagrant-reload
virtualboxis the default provider for
vagrantby adding the following line to your
.bashrc(or equivalent) and restart your shell:
You can find Magma code on Github.
To download Magma current version, or a specific release do the following
git clone https://github.com/magma/magma.git cd magma # in case you want to use a specific version of Magma (for example v1.8) git checkout v1.8 # to list all available releases git tag -l
First, follow the previous section on developer tools. Then, install some additional prerequisite tools.
Install necessary dependencies and configure the aws cli
brew install aws-iam-authenticator kubectl helm terraform python3 -m pip install awscli boto3 aws configure
Install the following
sudo apt install awscli
Orchestrator and NMS
Orchestrator deployment depends on the following components
- AWS account
- Registered domain for Orchestrator endpoints
We recommend deploying the Orchestrator cloud component of Magma into AWS. Our open-source Terraform scripts target an AWS deployment environment, but if you are familiar with devops and are willing to roll your own, Orchestrator can run on any public/private cloud with a Kubernetes cluster available to use. The deployment documentation will assume an AWS deployment environment - if this is your first time using or deploying Orchestrator, we recommend that you follow this guide before attempting to deploy it elsewhere.
Provide the access key ID and secret key for an administrator user in AWS
(don't use the root user) when prompted by
aws configure. Skip this step if
you will use something else for managing AWS credentials.
Access gateways (AGWs) can be deployed on to any AMD64 architecture machine which can support a Debian or Ubuntu 20.04 Linux installation. The basic system requirements for the AGW production hardware are
- 2+ physical Ethernet interfaces
- AMD64 dual-core processor around 2GHz clock speed or faster
- 4GB RAM
- 32GB or greater SSD storage
In addition, in order to build the AGW, you should have on hand
- A USB stick with 2GB+ capacity to load a Debian Stretch ISO
- Peripherals (keyboard, screen) for your production AGW box for use during provisioning
We currently have tested with the following EnodeB's
- Baicells Nova 233 TDD Outdoor
- Baicells Nova 243 TDD Outdoor
- Assorted Baicells indoor units (for lab deployments)
Support for other RAN hardware can be implemented inside the
on the AGW, but we recommend starting with one of these EnodeBs.