Awesome

DBT Dynamic Binary Toolkit

A delivery system for self-updating, signed tools.

Imagine a set of tools that are always up-to-date, and always safe to use. Imagine anyone in your organization being able to easily contribute to this tool chest with minimal preparation. Imagine everything always just working, and getting out of your way so you can do your thing. What's more, your tools are unmodified, unchanged, unaltered. Sound like magic?

What kind of tools you say? Anything that can be compiled into a single file. Golang programs? Yup. Bash scripts? Yessir. Pyinstaller and pyoxidizer tools? You bet. As long as it's a single file, dbt can distribute it to your users painlessly, and securely, with best-in-class UX.

The Don'ts of Software Distribution

Delivering software to users is a common problem. At some level, every company, every software author has to do it.

Users of your software, it must be said, just want to use it. They're rarely concerned by the details of how they obtain your offering. They just want to get it, and move on with thier day.

While you certainly can distribute your software any old way, there are a great number of bad patterns in this space, such as:

You shouldn't need to be a professional developer with a tested, reliable, build system to use a tool. You also shouldn't have to be a mechanic to drive a car. Sometimes you just want to start the engine, and go down the road.
You shouldn't need to be a security expert to stay safe online.
You shouldn't run old or out ot date software - unless you have a strong reason to do so, in which case, you shouldn't be prevented from doing so.
Your company shouldn't need a large staff, or expensive, complicated, MDM software to distribute and maintain your apps, tools, or programs.

Software is really just bits. Distribution of software really comes down to finding the right bits, and getting them into place. Whether you assemble them onsite, or load them from an App Store, it's all the same. What are the right bits? Can I trust these bits? Do I have them? How do I get them? Ok, now I have them, how do I run them? That's all there is.

dbt distills these actions down to their core, and makes it all happen for you - securely, transparently, quickly - and lets you get on with your day.

How DBT Works

DBT is basically just a downloader and verifier for executable files. That's it. That's all it does.

The tools themselves are unaltered by dbt. The 'magic' works by leveraging the same low-level system calls used to load every other program on your computer. The same system calls that allow your machine to boot at all, let you run a mail client, and look at pictures of cute cats is available to your own internal tooling with very little setup. Once installed, dbt does it for you.

What's more, you're not adding any dependency - other than your people getting used to amazing UX. Your tools are unaltered. Running a tool via dbt is exactly the same as running it by itself. Indeed, the author is, to date, unaware of a means of differentiating a process running via dbt and one ran bare, on its own.

Always Up To Date

By default, the dbt tool keeps ensures your tools are always up-to-date. When run normally, dbt will automatically download and verify the latest version of a tool before running it. However, if you need and older version, simply specify it, and dbt will do the same for the version you want.

By preferring the latest version, the majority of users will automatically upgrade. It's only the ones who have a special limitation in mind, and go out of their way that will keep using an older version. When they're ready to upgrade, they simply stop working so hard and voila!

This 'stay up to date and upgrade in place' mechanism applies to dbt itself, too. Yes. You read that right. dbt upgrades itself, on the fly, in place, transparently and securely. Your users will see it happening - we're not hiding anything - but they don't need to care.

Use Case

Say you have a program that people use to do their jobs. How do you distribute it? How do people stay up to date? How do they get bug fixes and new versions?

There are a bazillion ways of solving this problem. At some level, dbt is just one more method. Why is this better than the others? User Experience.

DBT gets out of the way and helps the user do what they really should do, but usually don't have time to do - that is: stay up to date, while still verifying the integrity and authorship of the tools they use in their daily life.

Pull Model

You absolutely can maintain some sort of device and server management software like Jamf or Chef or Puppet, and update all your OS packages all the time. These solutions exist, and they're great - when they work well together. Often they do not- or they're so heavy-handed your small agile shop can't maintain them well enough to stay out of the user's way.

Most tools of this type work off a "push model". The central administrator pushes out updates, and you use whatever you get. This can be great - when it works. Be honest however, when's the last time you were required to update to the latest something and things stopped working? This month? This week? Today? Yeah. Me too.

DBT in contrast works on a pull model. The default is you get the latest version of whatever tool we're talking about. You can, however, request a previous version instead. So long as the old versions are available in your repository, the user can do whatever they need to do. They're the user. Tools exist to make user's lives easier/better - else what's the use?

The pull model is a lot more respectful of your users. There's incentive to use the latest versions. That's what happens if they do nothing. However if they need to go out of their way to use an older version, they can.

Once you set up your tool repository, dbt downloads and verifies the tools, automatically looking for and using the latest version - unless the user goes out of their way to use a previous version.

That's it. That's the magic: Downloading and verifying in a fashion that gets out of the way of the user and lets them do their job.

Overview

To use dbt, you need the following

A repository your users can reach. This can be S3, Artifactory, the built in reposerver, or any WebDAV enabled HTTP server.
The dbt binary and its config file installed locally.
Crypto keys for code signing.

That's it!

When compiled, dbt creates installation shell scripts for any OS and chip architecture you specify. The installer will install itself locally into your path, and voila! Everything should just work.

What's more, via the included boilerplate tool your users can create new tools to do anything you need. Creation is quick and easy with working program stubs being generated automatically.

You can give users their own code signing keys, or choose to only trust keys used by your build system. It's all up to you. All dbt does is do what any conscientious, well-built system would do for you, but it does it automagically on any system where you can compile and run golang programs - which is most of them.

Installation

The easiest way to install dbt is via a tool called gomason. You can build via go build and move the files any which way you like, but gomason makes it easy. Gomason is actually the build system I wrote for dbt, and then broke out as its own project since it was quite useful in a general sense.

If you don't want to make any changes to the code or tools:

Clone the repo.
Change the metadata.json file in your clone to reflect your own repository setup and preferences. Specifically you need to change the repository and tool-repository lines.

N.B. S3 urls must be of the https form, e.g. https://your-dbt.s3.us-east-1.amazonaws.com and https://your-dbt-tools.s3.us-east-1.amazonaws.com. Only Virtual Host based S3 urls are supported. Why? Because AWS is deprecating the path-style access to buckets. Check out https://aws.amazon.com/blogs/aws/amazon-s3-path-deprecation-plan-the-rest-of-the-story/ for more information.
Install gomason via go get github.com/nikogura/gomason@latest. Then run gomason publish -sl. If you have it all set up correctly, it should build and install the binary as well as the installer script for your version of DBT together with the tools catalog, boilerplate, and reposerver. (The -s flag skips running the tests on dbt locally. I've already run them prior to publishing, but by all means, feel free to do so yourself again. The -l flag tells gomason to use the local copy, instead of downloading everything into a temporary GOPATH. )
Run the installer you built. It'll be found in <repo>/install_dbt.sh. With an HTTP reposerver like Artifactory or DBT's internal server, you can install this script via curl https://your.repo.host/path/to/install_dbt.sh | bash.

If you're using S3 as your backend, you will have to do it in 2 steps:
1. aws s3 cp s3://<your bucket>/install_dbt.sh install_dbt.sh
2. bash install_dbt.sh.
This 2 step is forced by the aws cli not being able to feed a downloaded object directly to bash. (Or at least, I haven't figured out how to make it do so - yet!)
Verify installation by running: dbt catalog list.

Usage

Generally speaking, you will run your tools with a command of the form:

dbt [flags] -- <tool>  <tool args and flags>

Take special note of the -- That double dash separates the flags for dbt itself from those of the tool. It can get confusing if you don't spot the double dash and grok it's meaning.

Without it, any flags you try to run on <tool> will be consumed by dbt itself, and the result will probably not be what you intend.

Of course, if your command has no flags itself, only positional arguments, you can run it straight without the double dash.

Components

DBT consists of a binary dbt a config file, and a cache located at ~/.dbt. The dbt binary checks a trusted repository for tools, which are themselves signed binaries.

Tools are automatically downloaded, and verified for checksum and signature, then if they pass, they're run.

The DBT binary, when run:

Fetches the latest truststore from the Repository, verifies its checksum.
Checks the repository to see what the latest version of dbt is.
Compares its own checksum against the latest version's checksum.
Auto-updates itself by downloading the latest version, and if the new version's checksum and signature verifies, it overwrites itself on the filesystem, then calls the new binary with the original arguments, letting the child overwrite the parent in the process table.
The new binary verifies itself in the same manner. Presumably at this point, it is the latest version and we can continue.
Then dbt checks the filesystem for the tool indicated, performing the same cycle.
Checks the Tool on disk, verify checksum against what's in the repository - replacing it if needed.
Verifies the signature of the Tool - replaces if needed.
Executes the Tool with the provided arguments, letting the Tool overwrite DBT in the process table, to continue on it's own merry way.

It's rather mind-bending and recursive, but what you get is an always up to date tool with built in authorship and integrity checks.

Tools can be anything and do anything- the only limit is the imagination and skills of the author. DBT is writen in, and inspired by Golang, where everything compiles down to a single binary, and you can easily cross-compile for other OSes and Architectures, but you don't have to use golang to use dbt.

A Tool can be anything that is contained in a single file, and can have a 'detatched signature'. Since you can digitally 'sign' any digital file, anything completely self contained in a single file is good to go. Prefer Python? Build your stuff with PyInstaller or PyOxidizer and DBT will distribute it to your users.

You could even have a bash script, signed by a trusted source, in a repo that DBT is configured to trust, and it will work. Pretty cool huh?

This allows the author to make tools that do things that can be truly 'write once, run anywhere' - for any desired degree of 'anywhere'. Furthermore, the tools and dbt itself are self-updating, so every time you use it, you're using the latest version available.

For backwards compatibility and emergencies, you can also specify the version of a tool, and use any old version in your trusted repository. The default, however will be to get and use the latest.

If the trusted repo is offline, or unavailable, you can choose to degrade gracefully into 'offline mode' and use tools that are already downloaded to disk.

As an added bonus, the Tools are programs in and of themselves. There's no difference between a binary program running by itself and one run via dbt. All dbt does is download a program, verify it for integrity and authorship, and then exec it with the arguments you provide.

It's all up to you. DBT is a framework, and frameworks are all about enablement.

Diagram (requires mermaid extension)

sequenceDiagram
    participant DBT
    participant Tool
    participant Repository
    DBT-->>Repository: Get truststore from Repository (public keys of trusted tool authors).
    DBT-->>Repository: What's latest version of dbt, and what's it's sha256 checksum?
    loop DBT Integrity Check
        DBT->>DBT: Calculate my own checksum.
        DBT->>DBT: Compare calculated checksum against downloaded checksum.
        DBT->>DBT: Verify signature of DBT itself.
    end
    Note over DBT,Repository: If validation fails, download the latest version.<br>Validate that, and if it passes, execute it with the original arguments.<br> The original process exits.  The child takes over parent's pid.<br>Lather, rinse, and repeat.
    DBT-->>Repository: Is there a tool called <tool name>?
    DBT-->>Repository: What's the latest version of <tool name>, and what's it's sha256 checksum?
    loop Tool Integrity Check
        DBT->>Tool: Is <tool name> already on disk?
        Note over DBT,Repository: If not, download it, it's checksum, and it's signature.
        DBT->>Tool: Calculate sha256 checksum of Tool.
        DBT->>Tool: Compare calculated checksum against downloaded checksum.
        DBT->>Tool: Verify signature of Tool.
    end
    DBT-->>Tool: Run <tool name> with provided arguments.
    Note over DBT,Repository: DBT exits.  Tool takes DBT's pid in the process table.

So, from the command line, if you were to run:

dbt -V -- catalog list -v

You would run dbt in verbose mode, and catalog with flag -v and argument list

The -- tells the shell it's done parsing flags and options. Anything to the right of it are arguments, the first of which is the name of the tool to run, and anything after that gets passed into the tool as the tool's arguments. Slightly wonky, but very very useful.

Why?

I had an experience in a role where a great many people did not agree with or accept that part of being a conscientious computer user was keeping their systems and tools up to date. Expecting people to pay attention to upgrade announcements, or even run things like brew upgrade regularly was not only too much. It was viewed as offensive, and a failure on my part as a toolsmith. wow huh?

Necessity is, as they say, the mother of invention though, so I worked out a way to slice that particular Gordian Knot. What I came up with was a way I could make everyone happy. Users were happy because they didn't need to concern themselves with updates. I could also make myself happy, because I could make sure the system was secure, reliable, and had some fall back. What I came up with I now offer to you as 'DBT'.

Whether the particular folks that drove me to this extreme were right or wrong is not really important. It turns out there is actually a legitimate use case for self-updating tooling beyond simply appeasing user laziness.

Sometimes you want to be a user of a tool, and not it's author or maintainer. Those hardy souls that make wonderfully useful and reliable building blocks that the rest of us can use to construct our own towers of awesomeness are to be glorified and revered- it's true. Face it though, you don't have time to be that person for every library and tool in your bag of tricks.

Are you on the latest version? What is the latest version? Do you need to upgrade? How? Will the version you have even work? How do you know when you need a new version? These are questions that sometimes you'd rather not have to ask. They're also questions that, odds are, the author of the tool is already tired of answering. Why not let the machine handle it for you?

DBT is doing exactly what you would do, if you had time, resources, and face it, interest in doing it all by hand in a secure fashion.

Be honest. How often do you verify the checksum or signature on something you download and run? Do you even know how to verify them? Don't feel bad, many people don't. While it's a good thing to know how to do, the syntax for the tools are generally wonky and esoteric. It's not the sort of thing you're going to remember how to do unless you do it a lot, and who wants that job? Blech.

DBT does your due diligence for you, and lets you get on with your day.

Another real-world example: Imagine this, you've got a system of dynamic VM's and Containers, all leveraging common tooling. You might even have a serious DAG or web of 'things' dynamically generating other 'things' in a busy and automated fashion. What is there's a problem, or an upgrade? With normal utility tools and scripts you have to re-bake your machine images and containers to pick up the changes. You might say that that's a good thing. But what if it's not?

With DBT, you have the best of both worlds. You can force your tools to use an explicit version (dbt -v 1.2.3 -- <tool>). You can also dispense with the '-v' and run the latest. Voila! You're automatically picking up the latest version of the tooling from your trusted repository.

Security

DBT is as secure as the repository you trust to hold the binaries, and the degree to which you protect the signing keys.

It will ensure, come hell or high water that every bit of the binary downloaded is what it aught to be, and that the signature is one you've decided to trust. If it can't do that, it'll stop- immediately and scream bloody murder.

You can make the repo wide open, let anybody PUT tools there, give everyone a copy of a non-encrypted signing key, and everything will just work. It's just not recommended - or safe.

Failing to secure your repository and signing keys is an excellent way to p0wn your entire organization and every user of dbt. If you do this, it's not my fault, nor is it the fault of dbt. You have been warned.

I just build the tools. You choose how to use them.

"If you aim the gun at your foot and pull the trigger, it's UNIX's job to ensure reliable delivery of the bullet to where you aimed the gun (in this case, Mr. Foot)." -- Terry Lambert, FreeBSD-Hackers mailing list.

Configuration

Dbt uses a config file typically located in ~/.dbt/conf/dbt.json. It's built by default by the shell installer when you build dbt. The following data is for reference.

An example dbt config file:

    {
      "dbt": {
        "repository": "http://localhost:8081/dbt",
        "truststore": "http://localhost:8081/dbt/truststore"
      },
      "tools": {
        "repository": "http://localhost:8081/dbt-tools"
      }
      "username": "",
      "password": "",
      "usernamefunc": "echo $USERNAME",
      "passwordfunc": "echo $PASSWORD"
    }

It contains sections for the dbt tool itself, as well as for the tools dbt will download and run.

The individual sections are detailed below.

dbt

This section applies to the dbt binary itself. The dbt binary doesn't do much in and of itself beyond download , verify, and run tools, but this is where you set the degree of paranoia on the system by setting the truststore.

It's also conceivable that dbt itself might need a higher level of paranoia than the tools. It's all up to you.

repository

Url of the trusted repository.

truststore

Url of the truststore. This file contains the public keys of the trusted authors of dbt binaries. This can be a single ascii armored public key such as:

The file can consist of multiple public keys such as:

There's nothing magical about this file. It's just the keys you've decided to trust, concatenated together. Comments after an -----END PGP PUBLIC KEY BLOCK----- or before an -----BEGIN PGP PUBLIC KEY BLOCK--- are ignored, and can be quite useful for humans trying to maintain this file.

tools

This section is for the tools dbt downloads, verifies, and runs for you.

repository

Url of the repo where the tools are stored. This is where tools are found, and where the tool catalog looks for tools.

username

Username if basic auth is used on repos. (Optional)

password

Password if basic auth is used on repos. (Optional)

usernamefunc

Shell function to retrieive username.

passwordfunc

Shell funciton to retrieve password.

Repository Support

The dbt reposerver tool is written entirely in golang. All the internal tests work off an instance of the dbt reposerver. See Reposerver for more details on how to run it.

Artifactory Open Source can be used as a dbt repo. It works well without auth, or with basic authentication. Paid Artifactory versions work well too.

You can additionally utilize Amazon S3 as a repo server. Authentication to S3 is assumed to be already in place and leverages the expected configs in ~/.aws. Credential managers work transparently through credential_process as detailed in the AWS docs.

N.B. For S3 usage, only Virtual Host based S3 urls are supported. Why? Because AWS is deprecating the path-style access to buckets. Check out https://aws.amazon.com/blogs/aws/amazon-s3-path-deprecation-plan-the-rest-of-the-story/ for more information.

Included Tools

The whole point of DBT is that you'll create your own tools to do things your way. DBT is itself just a framework, and does exactly nothing without the tools that it's designed to download and run. By itself, it can't even tell you what tools are available to you.

DBT is designed to be as open and generic as possible. I, the author, don't know what you're going to do with it, and I will make as few assumptions as I possibly can while still presenting you with a useful tool.

There are, however, some common tasks that any user of DBT might want at their fingertips. The following is a list of tools that will build automatically with dbt and be available for your pleasure:

If for some reason you don't want to use the included tools, just remove them from your metadata.json and they won't publish.

Catalog

A tool for showing what tools are in your repository.

Command: dbt catalog list

Output:

Fetching information from the repository...
Commands:

	Command Name		Latest Version		Description



	    boilerplate    		3.0.4			A tool boilerplate generating tool for DBT.
	        catalog    		3.0.4			Tool for showing available DBT tools.
	     certinator    		1.0.0			Instrument Hashicorp Vault to create CA's and Certificates for Clients and Services
	      genkeyset    		0.1.2			Generate a JWK KeySet for use with Orionlabs PTT
	     reposerver    		3.0.4			A tool repository server for DBT.

Further information on any tool can be shown by running 'dbt <command> help'.

Catalog Help

Command: dbt catalog help

Output:

Tool for showing available DBT tools.

DBT tools are made available in a trusted repository.  This tool show's what's available there.

Usage:
  catalog [command]

Available Commands:
  help        Help about any command
  list        ListCatalog available tools.

Flags:
  -h, --help       help for catalog
  -V, --verbose    Verbose output
  -v, --versions   Show all version information for tools.

Use "catalog [command] --help" for more information about a command.

Reposerver

An HTTP repository server. It serves up the various dbt tools and components from a file location on disk.

Available Reposerver Auth Methods:

basic-htpasswd Your basic htpasswd file. Supports using different files for GET requests (dbt users) and PUT requests (dbt tool authors).
ssh-agent-file Authentication via JWT signed by an SSH key stored in the ssh-agent. Users are mapped to public keys by a server-side file. IDP files for the ssh-agent-file auth method can contain both GET and PUT users in a single file.
ssh-agent-func Authentication via JWT signed by an SSH key stored in the ssh-agent. Users are mapped to public keys by a server-side shell function. This method can, for instance, retrieve the SSH public key for a user from an LDAP directory.

You can even have different auth methods for GET and PUT requests. Why did I make it possible to have split auth methods? Flexibility. Passwordless ssh-key auth for a user is good UX for users. It's secure, and easy for the users. It's kind of a pain for CI systems and other automated uses. Sometimes just sticking a password in the environment is the best way for these use cases. Hey, do what you want. I'm just trying to help.

The PublicKey Auth IDP file contains sections for both GET and PUT, so a single file can be used for both. Obviously if you do use separate files, only the appropriate portion of each file will be read.

You can choose to require authentication on GET requests or not. Unauthenticated gets are appropriate for running a reposerver inside of a VPN. If you're exposing your reposerver to the internet, authenticating all requests is highly recommended.

Reposerver Config

Some examples of reposerver config files:

Basic Htpasswd Auth

Create your reposerver config file should be of the form:

{
    "address": "my-hostname.com",
    "port": 443,
    "serverRoot": "/path/to/where/you/store/tools",
    "authTypeGet": "basic-htpasswd",
    "authTypePut": "basic-htpasswd",
    "authGets": false,
    "authOptsGet": {
        "idpFile": "/path/to/htpasswd/file/for/gets"
    },
    "authOptsPut": {
        "idpFile": "/path/to/htpasswd/file/for/puts"
    },
}

JWT Auth with Public Keys

See https://github.com/orion-labs/jwt-ssh-agent-go#background for details.

Public Keys Mapped to Users in a File

Your reposerver config should look something like:

{
    "address": "my-hostname.com",
    "port": 443,
    "serverRoot": "/path/to/where/you/store/tools",
    "authTypeGet": "ssh-agent-file",
    "authTypePut": "ssh-agent-file",
    "authGets": true,
    "authOptsGet": {
        "idpFile": "/path/to/idp/file"
    },
    "authOptsPut": {
        "idpFile": "/path/to/idp/file"
    },
}

Public Keys Mapped to Users via Function

{
    "address": "my-hostname.com",
    "port": 443,
    "serverRoot": "/path/to/where/you/store/tools",
    "authTypeGet": "ssh-agent-file",
    "authTypePut": "ssh-agent-file",
    "authGets": true,
    "authOptsGet": {
        "idpFunc": "ldapsearch '(&(objectClass=posixAccount)(uid='"$1"'))' 'sshPublicKey' | sed -n '/^ /{H;d};/sshPublicKey:/x;$g;s/\n *//g;s/sshPublicKey: //gp'"
    },
    "authOptsPut": {
        "idpFunc": "ldapsearch '(&(objectClass=posixAccount)(uid='"$1"'))' 'sshPublicKey' | sed -n '/^ /{H;d};/sshPublicKey:/x;$g;s/\n *//g;s/sshPublicKey: //gp'"
    },
}

Reposerver IDP File

The reposerver takes an IDP (Identity Provider) file. In the case of http basic auth, this is a standard htpasswd file.

In the case of Public Key JWT Auth, it looks like so:

  {
     "getUsers": [
        {
           "username": "foo",
           "publickey": "ssh-rsa ...... foo@example.com"
        }
     ],
     "putUsers": [
        {
           "username": "bar",
           "publickey": "ssh-rsa ...... bar@example.com"
        }
     ]
  }

Running the Reposerver

Command: dbt reposerver -f /path/to/config

Output:

{"level":"info","msg":"Running dbt artifact server on my-hostname.com port 443.  Serving tree at: /var/dbt","time":"2020-11-11T11:18:43-08:00"}

Running the Reposerver in Kubernetes

Checkout the kubernetes directory for example manifests for running the reposerver in Kubernetes.

These examples use the HTTPPRoxy ingress from projectcontour. Any old ingress will do though.

Reposerver Config Reference

address The IP or hostname on which your reposerver is running.
port The port on which your reposerver is running
serverRoot The directory who's contents get served up to dbt clients
authTypeGet Auth type to use for GET requests.
authTypePut Auth type to use for PUT requests.
authGets Whether to require authentication of GET requests at all. Obviously if this is false, your authTypeGet doesn't amount to much.
authOptsGet Auth Options for GET Requests. Can contain:
- idpFile File path to IDP file.
- idpFunc Shell function that receives the username as $1 and is expected to return a ssh public key for that username.
authOptsPut Auth Options for PUT Requests. Can contain:
- idpFile File path to IDP file.
- idpFunc Shell function that receives the username as $1 and is expected to return a ssh public key for that username.

Boilerplate

This tool uses a templated file system to help generate templated projects. Each of the folders in this directory contain a layout for a specific type of project to generate. Each folder name starts with an underscore (_) to prevent go tools from treating them as actual golang project files.

Within a given project, all items are templatized; folders and files.

Project Types

Cobra

This project is used to generate tools using the cobra command line framework.

Adding a new Project

Make a project folder

First step is to creat a new "projects" folder in the project_templates directory. Under this created directory you can create any number of templated file structures that will become the basic of your new destination project.

For example, under a project you might create both a templated service and web GUI application which require separate templating schemes.

NB: Your directory name needs to start with an underscore ("_"). This will ensure the golang tools ignore it. If you don't follow this rule, things like go mod will throw errors on the template syntax.

NB: Only single folder projects have been attempted at the time of this writing.

Add project to projects.go

Create a go:embed FS to hold your project structure

go:embed project_templates/_cobraProject/*
var myNewProject embed.FS

Add the project to each function in this file.

Add new prompt types

If adding new template variables, they should be added to the prompt.go file. This includes the prompt questions as well as any validations to perform on a given answer.

Make params structure

Create a struct that holds all of the variables your application requires to run

type DockerParams struct {
   	DockerRegistry    string
   	DockerProject     string
   	ProjectName       string
    ...

Done

After this your new project will be available for generation at the top level of the application