Overview 🔗︎

This quick start guide shows you how to install a self-hosted evaluation instance of the Banzai Cloud Pipeline platform on AWS for evaluation purposes. The procedure uses the Banzai CLI tool to deploy a Banzai Cloud Pipeline platform to AWS. The infrastructure will consist of an EC2 instance, which runs the components of Pipeline on a single-node PKE cluster.

After completing these steps, you will have an environment where you can:

  • launch clusters, and
  • evaluate the services of the Banzai Cloud Pipeline platform.


This installation is strictly for evaluation purposes. You cannot convert this installation into a production installation.


System requirements 🔗︎

The following procedure works on macOS or Linux (x86_64). If you do not have access to a computer running macOS or Linux, evaluate the Banzai Cloud Pipeline platform online.

Prerequisites 🔗︎

Install the following software on the machine that you will use to manage the deployment (usually your laptop).

  • AWS credentials — have an AWS access key ready for deploying the infrastructure
  • Banzai CLI tool — the installation process depends heavily on the Banzai CLI tool
  • Docker 18.09+ — the heavy lifting of the deployment is managed by a Docker container

AWS credentials 🔗︎

You will need an AWS account, the related access keys, and the aws-cli tool configured to use these credentials to complete the installation.

  1. Request an AWS account and access keys of it from your AWS administrator.

  2. The installation process uses the credentials configured on your machine for the aws-cli tool. If you don’t already have aws-cli set up install and configure aws-cli.

    The Banzai CLI tool can use your AWS configuration to authenticate to AWS. This works as follows (use at least version 0.14.1):

    • If the AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY (and optionally AWS_SESSION_TOKEN) values are available as environmental variables in the terminal you are using, the Banzai CLI tool passes these values to the installer container.
    • If the previous values are not available, but the AWS_PROFILE is, and the AWS configuration and credentials files contain valid values, the Banzai CLI tool uses the AWS profile. Note: If you do not want to make the AWS profile available as environment variable, you can set it in the values.yaml file, under the providerConfig.profile key.
    • To assume the role of a different account, set the account to assume in the values.yaml file, under the providerConfig.assume_role key. You can combine this method with the previous methods that use AWS_PROFILE or AWS_ACCESS_KEY_ID.

Banzai CLI tool 🔗︎

Banzai Cloud Pipeline is installed using the Banzai CLI tool, which you will use for everyday tasks in the Banzai Cloud world.

The quickest way to install the banzai-cli package for your environment is to run the following command:

curl https://getpipeline.sh | sh

on Linux You can also use our packages for the most popular Linux distributions. For more options, check our detailed Installation guide for Banzai CLI.

You will also need kubectl`, the command line tool for Kubernetes. Since most Linux distributions have outdated packages for kubectl, we recommend using the following one-liner, or other options from the Kubernetes documentation:
curl https://getpipeline.sh | sh -s -- kubectl.

on macOS: You can install Banzai CLI on macOS directly with Homebrew: brew install banzaicloud/tap/banzai-cli. The Homebrew formula for Banzai CLI also installs kubectl automatically.

Make sure that your Banzai CLI version is up-to-date.

Docker 🔗︎

The installer needs a recent version of the Docker container engine, at least version 18.09. If you don’t already have it installed, follow the Docker docs for your platform.

Please note that the Docker daemon should be running, the docker command should be in the PATH, and the account used for the installation process should have the privileges needed to run containers (for Linux, check the post-installation steps).

For Docker for Mac, ensure that at least 3 CPU and 3 GiB of memory is allocated. You can check this on the Preferences > Advanced tab of Docker for Mac.

Install Banzai Cloud Pipeline 🔗︎

The installer creates an EC2 c5.large instance in your default AWS region, in the default Virtual Private Cloud (VPC). If this is not what you want, check how to customize the provider configuration.

Note: This guide expects you to run every command in the same terminal session, because some steps depend on the output of earlier steps. (You can supply those outputs manually in a new terminal, just keep that in mind.)

  1. To start the installer, simply execute the following command, and answer the questions displayed.

    banzai pipeline up --provider=ec2

    Note: Creating every component can take several minutes.

  2. Before finishing, the command will display the URL and access credentials of the created Banzai Cloud Pipeline instance. Record this information, you will need it to login. For example:

    pipeline-address = https://ec2-xx-yyy-4-zzz.us-west-1.compute.amazonaws.com/
    pipeline-password = ishbdfwoeihefo
    pipeline-username = admin@example.com
  3. When your Banzai Cloud Pipeline instance is ready for use, the installer offers to login for you. Accept the displayed certificate, and use the displayed credentials to login using your browser.

  4. A browser window shows up. Log in with the username and password from the terminal output. After that, you can return to your console.

    Note: If you cannot login for some reason, you can try to login later using the banzai login command.

  5. Installing the Banzai Cloud Pipeline is complete. Let’s create the first cluster for your workloads. In the examples we will use Banzai Cloud’s Kubernetes distribution, PKE on AWS.

Next steps 🔗︎

To try the features of the Banzai Cloud Pipeline platform, you will need a Kubernetes cluster that is managed by Pipeline. Follow the Create your first cluster guide to either:

  • create a cluster with Pipeline, or
  • import an existing cluster into Pipeline.

We recommend launching a PKE cluster in Amazon EC2. For details, see the Create a PKE cluster on AWS guide.