We’ve been hearing the phrase “year of the Linux desktop” from times immemorial. The FOSS and Linux community tosses up this idea at the beginning of a new year and expects the Linux adoption to rise exponentially in the upcoming months. While a complete Linux dominance in the desktop scene looks like a far-fetched dream, Tux continues to make slow strides.
According to the latest data from NetMarketShare, Linux is running on 3.37% desktop computers and laptops. This Linux market share number is from August 2017.
I’ve been working with container networking a bunch this week. When learning about new unfamiliar stuff (like container networking / virtual ethernet devices / bridges / iptables), I often realize that I don’t fully understand something much more fundamental.
This week, that thing was: network interfaces!!
You know, when you run ifconfig and it lists devices like lo, eth0, br0, docker0, wlan0, or whatever. Those.
This is a thing I thought I understood but it turns out there are at least 2 things I didn’t know about them.
I’m not going to try to give you a crisp definition, instead we’re going to make some observations, do some experiments, ask some questions, and make some guesses.
Linux serves — of that there is no doubt — literally and figuratively. The open source platform serves up websites across the globe, it serves educational systems in numerous ways, and it also serves the medical and scientific communities and has done so for quite some time.
I remember, back in my early days of Linux usage (I first adopted Linux as my OS of choice in 1997), how every Linux distribution included so many tools I would personally never use. Tools used for plotting and calculating on levels I’d not even heard of before. I cannot remember the names of those tools, but I know they were opened once and never again. I didn’t understand their purpose. Why? Because I wasn’t knee-deep in studying such science.
Modern Linux is a far cry from those early days. Not only is it much more user-friendly, it doesn’t include that plethora of science-centric tools. There are, however, still Linux distributions for that very purpose — serving the scientific and medical communities.
Let’s take a look at a few of these distributions. Maybe one of them will suit your needs.
Scientific Linux
You can’t start a listing of science-specific Linux distributions without first mentioning Scientific Linux. This particular take on Linux was developed by Fermilab. Based on Red Hat Enterprise Linux, Scientific Linux aims to offer a common Linux distribution for various labs and universities around the world, in order to reduce duplication of effort. The goal of Scientific Linux is to have a distribution that is compatible with Red Hat Enterprise Linux, that:
Provides a stable, scalable, and extensible operating system for scientific computing.
Supports scientific research by providing the necessary methods and procedures to enable the integration of scientific applications with the operating environment.
Uses the free exchange of ideas, designs, and implementations in order to prepare a computing platform for the next generation of scientific computing.
Includes all the necessary tools to enable users to create their own Scientific Linux spins.
Because Scientific Linux is based on Red Hat Enterprise Linux, you can select a Security Policy for the platform during installation (Figure 1).
Figure 1: Selecting a security policy for Scientific Linux during installation.
Two famous experiments that work with Scientific Linux are:
Collider Detector at Fermilab — experimental collaboration that studies high energy particle collisions at the Tevatron (a circular particle accelerator)
DØ experiment — a worldwide collaboration of scientists that conducts research on the fundamental nature of matter.
What you might find interesting about Scientific Linux is that it doesn’t actually include all the science-y goodness you might expect. There is no Matlab equivalent pre-installed, or other such tools. The good news is that there are plenty of repositories available that allow you to install everything you need to create a distribution that perfectly suits your needs.
Scientific Linux is available to use for free and can be downloaded from the official download page.
Bio-Linux
Now we’re venturing into territory that should make at least one cross section of scientists very happy. Bio-Linux is a distribution aimed specifically at bioinformatics (the science of collecting and analyzing complex biological data such as genetic codes). This very green-looking take on Linux (Figure 2) was developed at the Environmental Omics Synthesis Centre and the Natural Environment for Ecology & Hydrology and includes hundreds of bioinformatics tools, including:
abyss — de novo, parallel, sequence assembler for short reads
Artemis — DNA sequence viewer and annotation tool
bamtools — toolkit for manipulating BAM (genome alignment) files
Big-blast — The big-blast script for annotation of long sequence
Galaxy — browser-based biomedical research platform
Fasta — tool for searching DNA and protein databases
Mesquite — used for evolutionary biology
njplot — tool for drawing phylogenetic trees
Rasmo — tool for visualizing macromolecules
Figure 2: The Bio-Linux desktop.
There are plenty of command line and graphical tools to be found in this niche platform. For a complete list, check out the included software page here.
Bio-Linux is based on Ubuntu and is available for free download.
Poseidon Linux
This particular Ubuntu-based Linux distribution originally started as a desktop, based on open source software, aimed at the international scientific community. Back in 2010, the platform switched directions to focus solely on bathymetry (the measurement of depth of water in oceans, seas, or lakes), seafloor mapping, GIS, and 3D visualization.
Figure 3: Poseidon Linux with menus (Image: Wikipedia).
Poseidon Linux (Figure 3) is, effectively, Ubuntu 16.04 (complete with Ubuntu Unity, at the moment) with the addition of GMT (a collection of about 80 command-line tools for manipulating geographic and Cartesian data sets), PROJ (a standard UNIX filter function which converts geographic longitude and latitude coordinates into Cartesian coordinates), and MB System (seafloor mapping software).
Yes, Poseidon Linux is a very niche distribution, but if you need to measure the depth of water in oceans, seas, and lakes, you’ll be glad it’s available.
A group of British IT specialists took on the task to tailor Ubuntu Linux to be used as a desktop distribution by the UK National Health Service. NHSbuntu was first released, as an alpha, on April 27, 2017. The goal was to create a PC operating system that could deliver security, speed, and cost-effectiveness and to create a desktop distribution that would conform to the needs of the NHS — not insist the NHS conform to the needs of the software. NHSbuntu was set up for full disk encryption to safeguard the privacy of sensitive data.
NHSbuntu includes LibreOffice, NHSMail2 (a version of the Evolution groupware suite, capable of connecting to NHSmail2 and Trust email), and Chat (a messenger app able to work with NHSmail2). This spin on Ubuntu can:
Perform as a Clinical OS
Serve as an office desktop OS
Be used as in kiosk mode
Function as a real-time dashboard
Figure 4: NHSbuntu main screen.
The specific customizations of NHSbuntu are:
NHSbuntu wallpaper (Figure 4)
A look and feel similar to a well-known desktop
NHSmail2 compatibility
Email, calendar, address book
Messager, with file sharing
N3 VPN compatibility
RSA token supported
Removal of games
Inclusion of Remmina (Remote Desktop client for VDI)
NHSbuntu can be downloaded, for free, for either 32- or 64-bit hardware.
The tip of the scientific iceberg
Even if you cannot find a Linux distribution geared toward your specific branch of science or medicine, chances are you will find software perfectly capable of serving your needs. There are even organizations (such as the Open Science Project and Neurodebian) dedicated to writing and releasing open source software for the scientific community.
Learn more about Linux through the free “Introduction to Linux” course from The Linux Foundation and edX.
“The Compliance Industrial Complex” is a term that evokes dystopian imagery of organizations engaging in elaborate and highly expensive processes to comply with open source license terms. As life often imitates art, many organizations engage in this practice, sadly robbing them of the many benefits of the open source model. This article presents an economically efficient approach to open source software license compliance.
Open source licenses generally impose three requirements on a distributor of code licensed from a third party:
Provide a copy of the open source license(s)
Include copyright notices
For copyleft licenses (like GPL), make the corresponding source code available to the distributees
If you explore the Wiki pages of EdgeX Foundry, you will see several references to the project’s architectural “tenets”. These are the principles that guide how the project’s contributors and technical steering committee decide what changes are accepted into the project, what features will be pursued, and ultimately what technology the group will advance together.
The tenets of EdgeX did not get established overnight. They are not some sort of religious doctrine or commandments (although some of us would like to see them carved in stone someday). We didn’t blindly establish them because it fit within today’s software mantra.
No, the EdgeX tenets have evolved from industry-wide collaboration that addresses the use cases and challenges of edge computing. More specifically, they evolved through trial and practice in Project Fuse, which Dell started more than two years ago and donated to The Linux Foundation earlier this year to seed EdgeX Foundry. These tenets represent the imbued lessons learned while building EdgeX Foundry, and they are the bedrock that will allow the EdgeX community and the commercial ecosystem around the project to continue to grow and thrive.
Understanding the impact and expanding influence of DevOps culture, and how to apply DevOps principles to make your digital operations more performant and productive.
A few years ago, I wrote that DevOps is the movement that doesn’t want to be defined. That’s still true, though being cryptic doesn’t help executives who need to understand what’s going on in their industries, or who want to make their digital operations more productive. You may already have people in your company who are “doing DevOps,” or who want to. What are they doing? What do they want?
Let’s start with origins. Back in 2007, a Belgian engineer named Patrick Debois became frustrated by the friction between developer and operations teams. As a developer and a member of the Agile community, Debois saw an opportunity to use Agile methodologies to manage infrastructure management process, much like developers manage development process. He initially described this concept as Agile Infrastructure but later coined the phrase DevOps, a portmanteau of development and operations.
We have solved some of the scaling problems with the release management and documentation teams, and are planning a solution for an issue now facing the dependency management team. In the course of working with those teams, I have developed a six-step process that I use to find more sustainable approaches to scaling open source community practices.
1. Understand history — Why are things they way they are today? What requirements were we trying to meet? Before making a major change to a process, we need to establish the original requirements and identify their sources. We also need to understand any constraints that influenced early decisions, and how long-standing processes have evolved since being created. This stage involves asking questions, examining mailing list archives, and studying existing tools.
The following is a contributed article from Node.js core technical committee member Matteo Collina, summarizing the talk he will give at the Node.js Interactive conference, to be held Oct. 4 – 6 in Vancouver.
Why have we written yet another web framework for Node.js? I am committed to making the Node.jsplatform faster, more stable and more scalable. In 2016, myself and David Mark Clements started Pino, which was designed to be the fastest logger for Node.js, and it now has four active maintainers and an ecosystem of hundreds of modules.
Fastify is a new web framework inspired by Hapi, Restify and Express. Fastify is built as a general-purpose web framework, but it shines when building extremely fast HTTP APIs that use JSON as the data format. These are extremely common in both web and mobile software architectures, so Fastify could improve the throughput of the majority of applications.
Google has outlined four key kernel hardening features its engineers have backported from upstream Linux to Android kernels on devices that ship with Android 8.0 Oreo. They will benefit “all Android kernels supported in devices that first ship with this release”, according to Sami Tolvanen, a senior software engineer on the Android Security team.
The new kernel protections should also help developers who are responsible for building Android hardware drivers detect kernel security bugs before shipping them to users. According to Google, 85 percent of the kernel vulnerabilities in Android were due to bugs in vendor drivers.
DevOps is a way of thinking; it’s an approach, not a specific set of tools. And that’s all well and good – but it only gives you half the picture. If we overstate DevOps as a philosophy or a methodology, then it becomes too easy to forget that the toolchain is everything when it comes to DevOps. In fact, DevOps thinking forces you to think about your toolchain more than ever – when infrastructure becomes code, the way in which you manage it, change it is constantly.
Skills Up survey: Python is the primary language used by those working in DevOps
Because DevOps is an approach built for agility and for handling change, engineers need to embrace polyglotism. But there’s one language that’s coming out as a crucial component of the DevOps toolchain — Python. In this year’s Skill Up survey, publisher Packt found that Python was the primary language used by those working in DevOps. Indeed, it was a language that dominated across job roles – from web development to security to data science – a fact which underscores Python’s flexibility and adaptability. But it’s in DevOps that we can see Python’s true strengths. If DevOps is a modern, novel phenomenon in the software world, it’s significant that Python is the tool that DevOps practitioners share as a common language.
