# Getting Started¶

This Getting Started guide will conver installing the Deployer CLI as well as some initial basic concepts needed before moving to the User Guide.

## Installation¶

To install the Deployer CLI, the only dependency is Docker. If you do not have Docker installed, see the Official Docs for installation instructions for your platform.

Once Docker is installed, change into a temporary directory and run:

$docker run -v$(pwd):/conf tacc/deployer --setup && mv deployer /usr/local/bin/deployer


The first step pulls down the latest stable version of the Deployer Docker image and installs a small alias script, deployer, in the current working directory. The second stop is optional but recommended so that the deployer script is on $PATH and not left in the temporary directory. Note Different versions of Deployer can be installed by specifying a TAG on the tacc/deployer image. With the alias installed, simply issue commands directly to the script. For example, validate your installation by executing: $ deployer --help


which should display the help.

## Basic Usage¶

The general format for executing commands via the the Deployer CLI is:

$deployer <command> -p <project> -i <instance> -t <tenant> -a <action> -d <deployment_file>  For any kind of deployment activity, one will use the execute command to the Deployer CLI, which is its default value and can be omitted. However, the Deployer CLI recognizes a few other informational commands. For example, we can get the version of the installed Deployer using the version command which requires no other arguments: $ deployer version
TACC Deployer
Version: 0.1-rc1


The arguments project, instance, etc, are defined in the following table and are covered in more detail in the Basic Concepts section below.

CLI Arguments:

 -h, –help show help message and exit -p PROJECT, –project PROJECT Software project to deploy such as JupyterHub or Abaco. Overrides that specified in the deployment file. -i INSTANCE, –instance INSTANCE Instance to deploy, such as ‘prod’ or ‘dev’. Overrides that specified in the deployment file. -t TENANT, –tenant TENANT Tenant to deploy, such as ‘SD2E’ or ‘designsafe’. Overrides that specified in the deployment file. -a ACTION, –action ACTION Action to take, such as ‘deploy’ or ‘update’ Must be a valid action for the project specified. -s SERVERS, –servers SERVERS Relative path to servers file, in the YAML format, of servers to target. This file should be in the current working directory or a sub directory therein. -c CONFIGS, –configs CONFIGS Relative path to config file, in the YAML format, of config to use. This file should be in the current working directory or a sub directory therein. -z PASSWORDS, –passwords PASSWORDS Relative path to passwords file, in the YAML format, of passwords to use. This file should be in the current working directory or a sub directory therein. -e EXTRAS, –extras EXTRAS Relative path to a directory of extra files needed for the action. This path should be in the current working directory or a sub directory therein. -o OVERRIDES, –overrides OVERRIDES String of config overrides; should have the form key1=value1&key2=value2.. These values will override values supplied in the config file at the project/instance/tenant level specified through those corresponding command line arguments or the deployment file -v, –verbose The value of the actor’s state at the start of the execution. -k, –keep_tempfiles Whether to keep the temporary Ansible files generated to execute playbooks -vv, –very_verbose Display very verbose output.

## Basic Concepts¶

The following concepts are important to understand before using Deployer.

### Projects, Instances and Tenants¶

The notions of project, instance and tenant are fundamental to Deployer’s approach to managing deployments. A project is one of a set of systems Deployer knows how to manage, and will eventually include the TACC JupyterHub, Abaco and Agave projects. When working with Deployer CLI, projects are referenced by a project id. To see information about what projects are supported in an existing Deployer installation, including their id’s, use the list_projects command:

$deployer list_projects Available Projects: TACC Integrated JupyterHub ************************** id: jupyterhub Description: Customized JupyterHub enabling deeper integration and ease of use of TACC resources from within running notebooks. Docs: http://cic-deployer.readthedocs.io/en/latest/users/projects.html#jupyterhub  The values for instance and tenant can be chosen by the operations team to best organize their infrastructure and configuration. One approach is to use instance values to distinguish physically isolated systems such as “development” and “production” and to use tenant values to distinguish logically separated aspects of systems (such as the DesignSafe tenant for JupyterHub or Abaco). ### Actions¶ Actions define what procedure should be taken on the deployment. Actions are defined on a project by project basis, though some standard actions such as deploy are available for all projects. To see which actions are available for a given project, use the list_actions command, specifying a project; e.g.: $ deployer -p jupyterhub list_actions
Available actions: ['deploy']


Note that the value to the project argument must be a project id, as output by the list_projects command.

### Deployment Files¶

In order to use Deployer, the operator will need to supply some deployment files describing the infrastructure to deploy onto and the configuration for the projects to deploy. At a minimum, this includes configuration file(s) and server file(s). Details on how to write these files are provided in the User Guide. We encourage teams to keep these files in a version control system and check them out on each machine that will run Deployer. For example, the CIC team stores its own deployment files in a bitbucket repository.

### Hierarchical Organization of Properties¶

The goal of the Deployer design is to minimize the time needed to write deployment files by eliminating the need to ever duplicate a property definition for a server or a project configuration. To achieve this goal, Deployer uses a hierarchical organization of properties for both servers and configuration, organized by project, instance and tenant.

In general, each instance belongs to exactly one project, and each tenant belongs to exactly one instance. Properties can be defined at a project, instance or tenant level, and property values defined at a more “local” level override those defined at a more “global” level. For example. if the jupyter_user_image property is defined for the “prod” instance but also for the “DesignSafe” tenant within the “prod” instance, then the value defined for DesignSafe would be used for all deployment actions taken against that tenant.

More details are given in the User Guide.

### Ansible¶

The Deployer contains scripts that can be launched from the command line to manage deployments on remote servers. It does so by first reading configuration files, server files, (optionally) extra files and command line arguments provided by the operator to generate temporary Ansible playbooks and then execute these playbooks on the remote servers specified. In general, the operator should not need to know anything about the generated Ansible scripts, and by default, Deployer removes these files after each command. For debugging purposes, Deployer can be instructed to keep these files using the -k flag.