Linux

Introduction

Steam’s monthly Hardware & Software Survey, published by Valve, offers a window into what operating systems, hardware, and software choices its user base is making. It has become a key barometer for understanding trends in PC gaming, especially for less dominant platforms like Linux. The newest data shows that Linux usage among Steam users has edged downward subtly. While the drop is small, it raises interesting questions about momentum, hardware preferences, and what might lie ahead for Linux gaming.

This article dives into the latest numbers, explores what may be pushing them to abandon Steam, and considers what it means for Linux users, developers, and Valve itself.

Recent Figures: What the Data Shows

• June 2025 Survey Outcome: In June, Linux’s slice of Steam’s user base stood at 2.57%, down from approximately 2.69% in May — a decrease of 0.12 percentage points.

• Year-Over-Year Comparison: Looking back to June 2024, the Linux share was around 2.08%, so even with this recent slip, there’s still an upward trend compared to a year ago.

• Distribution Among Linux Users: A significant portion of Linux gamers are using Valve’s own SteamOS Holo (currying sizable usage numbers via Steam Deck and similar devices). In June, roughly one-third of the Linux user group was on SteamOS Holo.

• Hardware Insights:

  • Among Linux users, AMD CPUs dominate: about 69% of Linux gamers use AMD in June.

  • Contrast that with the Windows-only survey, where Intel still has about 60% CPU share to AMD’s 39%.

Interpreting the Slip: What Might Be Behind the Dip

Though the drop is modest, a number of factors likely combine to produce it. Here are possible causes:

1. Statistical Noise & Normal Fluctuation Monthly survey results tend to vary a bit, especially for smaller share percentages. A 0.12% decrease could simply be part of the normal ebb and flow.

2. Sampling and Survey Methodology

   • Survey participation may shift by region, language, hardware type, or time of year. If fewer Linux users participated in a given month, the percentage would drop even if absolute numbers stayed flat.

   • Language shifts in Steam’s usage have shown up before; changes in how many users set certain settings or respond could affect results.

   • Latency or delays in uploading or processing survey data might also contribute to anomalies.

3. External Hardware & Platform Trends

In June 2025, the Qt team officially rolled out Qt Creator 17, marking a notable milestone for developers who rely on this IDE for cross-platform Qt, C++, QML, and Python work. While there are many changes under the hood, two of the spotlighted improvements are its updated default visual style and significant enhancements in how CMake is supported. Below, we’ll explore these in depth, assess their impact, and offer guidance on how to adopt the new features smoothly.

What's New in Qt Creator 17: A Snapshot

Before zooming into the theme and CMake changes, here are some of the broader enhancements in version 17 to set context:

• The “2024” theme set (light and dark variants) — which first appeared in earlier versions — becomes the foundational appearance for all new installs.

• General polish across the UI: icon refreshes, more consistent spacing, and better contrast.

• Projects now bind run configurations more tightly to the build configurations. That means selecting a build (e.g. Debug vs Release) also constrains which run configurations apply.

• Upgraded C++ tooling (with LLVM 20.1.3), improved QML formatting options, enhanced Python (pyproject.toml) support, and refinements in version control & analysis tools.

With that backdrop, let’s dive into the theme and CMake changes in more detail.

A Refreshed Visual Identity: Default “2024” Themes

Qt Creator 17 makes the “2024” light and dark themes the standard look & feel for new installations. These themes had been available previously (since Qt Creator 15) but in this version become the out-of-the-box configuration.

Other visual adjustments accompany the theme change:

• Icons throughout the IDE have been reviewed and updated so they align better with the new theme style.

• UI consistency is improved: spacing, contrast, and alignment between interface elements have been refined so that the environment feels more cohesive.

A theme isn't just aesthetics. The look and feel of an IDE affect user comfort, readability, efficiency, and even fatigue. Some benefits include:

• Improved clarity for long coding sessions: better contrast helps in low-ambient light or for users with visual sensitivity.

• Consistency across elements: less jarring visual transitions when switching between parts of the interface or when using external themes/plugins.

• Reduced setup friction: since the “2024” theme is now default, many users won’t need to hunt down or tweak theme settings just to get a modern, usable look.

Introduction

Windows Subsystem for Linux (WSL) has gradually become one of Microsoft’s key bridges for developers, data scientists, and power users who need Linux compatibility without leaving the Windows environment. Over recent versions, WSL2 brought major improvements: a real Linux kernel running in a lightweight virtualized environment, much better filesystem behavior, nearly full system-call compatibility, etc. However, until recently, certain high-performance workloads, GPU computing, video encoding/decoding, and very up-to-date kernel features, were either limited, inefficient, or unavailable.

In Windows 11, Microsoft has taken bold strides to remove many of these bottlenecks. Two of the most significant enhancements are:

1. The ability for WSL to tap into the GPU for acceleration (compute, video hardware offload, etc.), reducing reliance on CPU where the GPU is much more suited.

2. More seamless Linux kernel upgrades, allowing users to run newer kernel versions inside WSL2, bringing performance, driver, and feature improvements faster.

This article walks through each thing in detail: what has changed, why it matters, how to use it, what limitations still exist, and how these developments shift what’s possible with WSL on Windows 11.

What WSL Was, and Where It Needed Improvement

Before diving into recent changes, it helps to understand what WSL (especially WSL2) already provided, and where it lagged.

• WSL1: Early versions translated Linux system calls to Windows equivalents. Good for basic command-line tools, scripts, but limited in compatibility with certain networking, kernel module, filesystem, and performance-sensitive tasks.

• WSL2: Introduced a real Linux kernel inside a lightweight VM (Hyper-V or a similar backend), better system-call compatibility, better performance especially for Linux tools, and much improved behavior for things like Docker, compiling, etc. Still, heavy workloads (e.g. ML training, video encoding, hardware-accelerated graphics) were constrained by CPU support, lack of passthrough of GPU features, older kernels, etc.

So developers were pushing Microsoft to allow more direct access to GPU functionality (CUDA, DirectML, video decoding), and to speed up how kernel updates reach users.

GPU Acceleration in WSL on Windows 11: What It Means

GPU acceleration here refers to WSL’s ability to offload certain computation or video tasks from the CPU to the GPU, enabling faster, more efficient execution. This includes:

• Compute workloads - frameworks like CUDA (for NVIDIA), DirectML, etc., so that things like deep learning, scientific computing, data-parallel tasks run much faster. Microsoft now supports running NVIDIA CUDA inside WSL to accelerate ML libraries like PyTorch, TensorFlow.

Introduction

Imagine a world where every server, application, and network configuration is meticulously orchestrated via Git, where updates, audits, and recoveries happen with a single commit. This is the realm GitOps unlocks, especially potent when paired with the versatility of Linux environments. In this article, we'll dive deep into how Git-driven workflows can transform the way you manage Linux infrastructure, offering clarity, control, and confidence in every change.

GitOps Demystified: A New Infrastructure Paradigm

GitOps isn't just a catchy buzzword, it's a methodical rethink of how infrastructure should be managed.

• It treats Git as the definitive blueprint for your live systems, everything from server settings to application deployments is declared, versioned, and stored in repositories.

• With Git as the single source of truth, every adjustment is tracked, reversible, and auditable, turning ops into a transparent, code-centric process.

• Beyond simple CI/CD, GitOps introduces a continuous reconciliation model: specialized agents continuously compare the actual state of systems against the desired state in Git and correct any discrepancies automatically.

Why Linux and GitOps Are a Natural Pair

Linux stands at the heart of infrastructure, servers, containers, edge systems, you name it. When GitOps is layered onto that:

• You'll leverage Linux’s scripting capabilities (like bash) to craft powerful, domain-specific automation that dovetails perfectly with GitOps agents.

• The transparency of Git coupled with Linux’s flexible architecture simplifies debugging, auditing, and recovery.

• The combination gives infrastructure teams the agility to iterate faster while keeping control rigorous and secure.

Architecting GitOps Pipelines for Linux Environments

A well-organized Git setup is crucial:

• Use separate repositories or disciplined directory structures for:

  • Infrastructure modules (e.g., Terraform, networking, VMs),

  • Platform components (monitoring, ingress controllers, certificates),

  • Application-level configurations (Helm overrides, container versions).

• This separation helps ensure access controls align with responsibilities and limits risks from misconfiguration or accidental cross-impact.

This article explores how modern DevOps teams are redefining stability and reproducibility in production environments by embracing truly unchangeable operating systems. It delves into how NixOS’s declarative configuration model and OSTree’s atomic update mechanisms open the door to systems that are both resilient and transparent. We'll explain the advantages, technologies, comparisons, and real-world use cases fueling this shift.

The Paradigm Shift: From Mutable Chaos to Immutable Assurance

• Why the change happened: The traditional model, logging into servers, tweaking packages, and patching in place, has led to unpredictable environments, elusive bugs, “snowflake” systems, and configuration drift as environments diverged over time. Immutable infrastructure treats machines like fungible artifacts: if you need change, you don’t fix the running system, you replace it.

• Key benefits:

  • Reliability at scale: Automated, reproducible deployments, no divergence across servers.

  • Simplified rolling back: If something breaks, spin up the previous, working version.

  • Security by design: Core systems are read-only, reducing the attack surface.

Immutable Foundations in Action

• How it works: System configuration, including packages, services, kernels, is expressed in the Nix language in a config file. Rebuilding produces a new system “generation,” which can be booted or rolled back.

• Why DevOps teams love it:

  • Reproducibility: Exact environments can be rebuilt from config files, promoting parity across development, CI, and production.

  • Speed and consistency gains: In one fintech case, switching to NixOS reduced deployment times by over 50 percent, erased environment-related incidents, shrank container sizes by 70%, and cut onboarding time dramatically.

  • Edge readiness: Ideal for remote systems or stateless servers rebuilt nightly to ensure fleet consistency with easy rollback.

  • Personalization meets immutability: With tools like Home Manager, even user-specific configurations (like dotfiles or shell preferences) can be managed declaratively, and consistently reproduced across machines.

Introduction: Why Lightweight Matters for Kubernetes Devs

When running Kubernetes clusters for development, the operating system’s footprint can make or break performance and agility. Heavy, general-purpose Linux distributions waste memory and CPU cycles on components you’ll never use, while lightweight, container-focused distros keep your nodes lean and optimized. For developers experimenting with k3s, MicroK8s, or full-blown Kubernetes clusters, lightweight Linux offers faster spin-ups, lower overhead, and environments that better simulate production-grade setups.

In this guide, we’ll take a look at the best lightweight Linux options for Kubernetes developers, compare their strengths, and walk through code examples for quick setup. Whether you’re spinning up a local test cluster or building a scalable dev lab, this breakdown will help you pick the right base OS and make the most of your Kubernetes workflow.

Key Considerations for Dev-Focused Kubernetes Nodes

Before diving into individual distros, it’s important to understand what really matters when pairing Linux with Kubernetes:

• Minimal Resource Usage: A slim OS footprint leaves more CPU and RAM for pods and workloads.

• Container Runtime Compatibility: Built-in or easy-to-install support for containerd, CRI-O, or Docker ensures smooth cluster bootstrapping.

• Init System Support: Compatibility with systemd or OpenRC impacts how Kubernetes services are managed.

• Immutable vs. Mutable: Immutable systems like Fedora CoreOS or Talos enhance reliability but restrict tinkering, while Alpine and Ubuntu Core offer more flexibility for on-the-fly customization.

• Developer Friendliness: A distro should integrate seamlessly with kubectl, Helm, CI/CD agents, and debugging workflows.

Introduction

Container technology has matured rapidly, but in 2025, two tools still dominate conversations in developer communities: Docker and Podman. Both tools are built on OCI (Open Container Initiative) standards, meaning they can build, run, and manage the same types of images. However, the way they handle processes, security, and orchestration differs dramatically. This article breaks down everything developers need to know, from architectural design to CLI compatibility, performance, and security, with a focus on the latest changes in both ecosystems.

Architecture: Daemon vs. Daemonless

Docker uses a persistent background service, dockerd, to manage container lifecycles. The CLI communicates with this daemon, which supervises container creation, networking, and resource allocation. While this centralized approach is convenient, it introduces a single point of failure: if the daemon crashes, every running container goes down with it.

Podman flips the script. Instead of a single daemon, every container runs as a child process of the CLI command that started it. This design eliminates the need for a root-level service, which is appealing for environments concerned about attack surfaces. Containers continue to run independently even if the CLI session ends, and they can be supervised with systemd for long-term stability.

Developer Workflow and CLI

Podman was designed as a near drop-in replacement for Docker. Commands like podman run, podman ps, and podman build mirror their Docker equivalents, reducing the learning curve. Developers can often alias docker to podman and keep using their existing scripts.

Run an NGINX container

Docker

docker run -d --name web -p 8080:80 nginx:latest

Podman

podman run -d --name web -p 8080:80 nginx:latest

For desktop users, Docker Desktop remains polished and feature-rich. However, Podman Desktop has matured significantly. It now supports Windows and macOS with better integration, faster file sharing, and no licensing restrictions, making it appealing for enterprise environments.

When Red Hat announced the abrupt end of traditional CentOS in late 2020, the Linux ecosystem was shaken to its core. Developers, sysadmins, and enterprises that relied on CentOS for years suddenly found themselves scrambling for answers. Out of that disruption, two projects, AlmaLinux and Rocky Linux, emerged to carry forward the legacy of CentOS while forging their own identities. This article dives into how these two distributions established themselves as reliable, enterprise-grade options for developers and organizations alike.

The Fall of CentOS: An Industry Shockwave

For over a decade, CentOS was the backbone of countless servers, from small web hosts to enterprise data centers. It provided a stable, free, and RHEL-compatible platform, perfect for developers and administrators building and maintaining critical infrastructure.

That stability came to an end when Red Hat pivoted CentOS to a rolling-release model, CentOS Stream. Instead of offering a downstream, binary-compatible version of RHEL, Stream became a preview of future RHEL updates. This move caused widespread frustration:

• Organizations that built production environments around CentOS suddenly faced shortened support lifecycles.

• Developers who depended on a “set-and-forget” environment now had to deal with the unpredictability of a rolling release.

• Compliance-driven industries were left in limbo, as running on an unsupported OS could trigger security and regulatory risks.

This disruption created a vacuum, and the Linux community quickly stepped up to fill it.

The Birth of AlmaLinux and Rocky Linux

Shortly after the CentOS announcement, CloudLinux, a company with deep experience in server environments, launched AlmaLinux. The first stable release landed in March 2021. True to its name, “alma” meaning “soul”, the project’s mission was clear: to embody the spirit of CentOS while maintaining community governance. The non-profit AlmaLinux OS Foundation now oversees the project, ensuring it remains free and open for everyone.

At almost the same time, Gregory Kurtzer, one of the original CentOS founders, unveiled Rocky Linux, named in honor of CentOS co-founder Rocky McGaugh. From the beginning, Rocky positioned itself as a 1:1 binary-compatible rebuild of RHEL, mirroring CentOS’s original mission. Its governance structure, managed by the Rocky Enterprise Software Foundation (RESF), ensures that the project remains rooted in community oversight rather than corporate ownership.

A Shift in GNOME’s Core Applications

For over two decades, Eye of GNOME (often shortened to EOG) was the silent workhorse of the GNOME desktop environment. It wasn’t flashy, but it did exactly what most people expected: double-click a picture, and it opened instantly. Yet, with the arrival of GNOME 45 in late 2023, a new name appeared in the lineup of “core” apps: Loupe. From that moment forward, Loupe became the official default image viewer on GNOME desktops, displacing EOG.

This decision wasn’t made lightly. GNOME has been steadily refreshing its default applications in recent years, Gedit was replaced by GNOME Text Editor, and Cheese gave way to Snapshot. Loupe is the continuation of this modernization trend. Eye of GNOME is still available in repositories for those who want it, but the GNOME team has shifted its endorsement to Loupe as the better long-term solution.

What Loupe Brings to the Table

Loupe isn’t just a reskin of EOG. It was built from scratch with today’s hardware, design standards, and security expectations in mind. At first glance, the interface looks minimal, but there’s more happening beneath the hood than many realize.

• Rust-Powered Foundation – Unlike Eye of GNOME’s decades-old C codebase, Loupe is written in Rust. This choice immediately grants it memory safety, helping avoid whole categories of crashes and vulnerabilities. For an app that regularly opens untrusted files, this is an important safeguard.

• GPU-Accelerated Image Handling – Instead of pushing all rendering to the CPU, Loupe leverages the GPU. Panning across a large image or zooming into a 50-megapixel photo feels fluid, even on high-resolution displays.

• Touch-Friendly Navigation – GNOME has been preparing for a future that includes more touch devices. Loupe fits right in, supporting pinch-to-zoom, two-finger swipes to move between images, and smooth transitions that feel natural on both touchscreens and trackpads.

• Streamlined Metadata View – Instead of burying photo information behind a separate dialog, Loupe integrates an optional sidebar. With a click, you can see dimensions, file size, EXIF data, and even location details without leaving the main view.

• Security Through Sandboxing – Image decoding is handled in isolated processes using a new backend called Glycin. If a corrupt or malicious image tries to crash the decoder, it won’t take the entire viewer down with it.