Perkian - Implementation
Written by Rich Morin.
Precis: notes on Perkian's implementation
This page sketches out my current implementation notions for creating and distributing Perkian packages.
Creating a turnkey collection of several dozen software packages is a lot of work. Creating collections for multiple operating systems and processor types increases the difficulty, for a variety of reasons. For example, each OS (e.g., Linux, macOS, Windows) will have its own default packages, package management tools, and overall system environment. Differences in the processor family (e.g., AMD, Intel) and other characteristics (e.g., word size) also complicate turnkey distribution of software packages.
Each operating system has its own collection of default libraries and utilities. The available compilers and libraries may vary, along with the file tree layout, configuration files, I/O devices, processor architecture, etc. This affects the runtime environment for both deployment and development.
Supporting a large number of packages on arbitrary operating systems, processor families, and word sizes could yield dozens of combinations, producing a combinatorial explosion of complexity. Fortunately, we can work around this problem by abstracting away the operating system issues and limiting the number of supported architectures.
Docker containers based on Linux can be run on any Linux system that has the same processor architecture (e.g., 64-bit Intel). With a bit of work, these containers can also be run on Apple’s macOS or Microsoft Windows. Appropriate containers can also be built for 32-bit ARM processors, etc. See Perkify - Docker for details.
That said, we are currently concentrating on using Vagrant and Virtual Box, rather than Docker. This combination works on Linux (albeit with some inefficiency), macOS, and Windows. If and when we have this approach in production, we’ll look into alternatives for Linux variants, including Android OS and Raspbian.
At a high level, here are the tasks involved:
Collect package information on Pete’s Alley.
Use TOML to encode package “wish lists”.
Create and augment Ubuntu-based “boxes”.
Distribute the boxes via Vagrant Cloud.
There are a variety of package management archives, commands, etc.
Some are tied to operating systems, others to programming languages.
For example, Alacritty’s
GitHub page lists about a dozen commands
for retrieving and/or building software packages,
Debian’s Advanced Package Toolkit (APT) is well known as a reliable way to install software packages. Given that there are tens of thousands of packages in the archive, installation for most packages we want will “Just Work”. Finally, numerous versions of Linux (e.g., Raspbian, Ubuntu) are derived from Debian, so they inherit APT and many other design details.
Chef is a Ruby-based configuration management tool which can abstract away the specifics of tasks such as building, configuring, downloading, and installing packages. So, any task which is done for multiple packages or targets only needs to be described once. However, if the target OS doesn’t have a current and correct set of installation and configuration code for a package, we’ll need to resolve this deficiency. Each package management system has its own notion of how to specify installation and configuration details, so we’ll need a spanning set of cookbooks and recipes. See Perkian - Chef for details.
Docker is an OS-level virtualisation ecosystem which addresses a number of deployment issues. Lightweight “containers” can be created for a single OS (e.g., Debian) and deployed on systems ranging from personal computers through embedded systems to cloud-based servers. Android OS, sadly, is a conspicuous exception to this coverage, though it still can benefit from APT and Chef.
All Linux distributions have basically the same kernel, default libraries, and utilities. However, that doesn’t mean that they have the same runtime environment, whether for deployment or development. The available compilers and libraries may vary, along with the file tree layout, configuration files, I/O devices, processor architecture, etc.
To minimize the number of packages we need to add (and the amount of support we need to provide), we’ve opted to base Perkify on Ubuntu, a popular, “batteries-included” Linux distribution.
Our use case presents a potentially unmanageable amount of development, testing, and support. Fortunately, there are ways to manage this, using readily available software and other resources. Stitching these resources together will be a job for custom code (e.g., Elixir, Ruby) and data files (e.g., TOML).
To be continued…