How to Run Linux on Windows Without Dual Boot Using WSL

·1 views

Windows Subsystem for Linux (WSL) allows Windows users to run a full Linux distribution directly within Windows, eliminating the need for dual booting or a virtual machine. Installation is straightforward — opening PowerShell with administrator privileges and running 'wsl --install' sets up the required components and installs Ubuntu by default. Users can alternatively choose from other distributions such as Debian, Kali Linux, or openSUSE by specifying the distro name in the install command. Once installed, a Linux username and password are created, after which the environment can be verified using basic terminal commands like 'uname -a' and 'cat /etc/os-release'. WSL 2, the current version, uses a lightweight virtualized environment that offers significantly better Linux compatibility than its predecessor, making it a practical choice for developers who rely on Linux tools.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

RustDesk gains GitHub traction as open-source, self-hostable remote desktop tool

RustDesk, an open-source remote desktop application built with Rust, has gained 84 GitHub stars recently due to growing interest in self-hosted infrastructure. Unlike conventional remote desktop clients, RustDesk uses a two-server model — a rendezvous server for peer discovery and a relay server for connections when direct peer-to-peer links are unavailable. The architecture gives operators full control over traffic and metadata, making it appealing to teams wary of third-party connection paths. The project can be deployed quickly using Docker, though production use requires careful management of server keys, firewall rules, TLS configuration, and software updates. Developers are advised to test RustDesk in a private lab environment before rolling it out broadly, given the operational complexity of self-hosting.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How to Diagnose and Fix Full Disk Space on a Linux Server

Linux administrators facing full-disk alerts can use a structured set of command-line tools to identify and resolve the issue quickly. The process begins with 'df -h' and 'df -i' to pinpoint which filesystem or inode table is exhausted, followed by 'du' commands to drill down into the largest directories. The 'find' command helps surface oversized individual files such as core dumps, forgotten database exports, or misbehaving logs. A lesser-known cause is deleted files that remain open by active processes, which can be detected using 'lsof +L1' and resolved by restarting the holding process. Once the culprit is identified, targeted cleanup tools — including Docker pruning, journalctl vacuuming, and package manager cleanup — can reclaim disk space efficiently.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How a Preview-First Workflow Makes AI Noise Removal More Trustworthy

A preview-first design approach for background noise removal tools prioritizes user confidence by letting people hear a sample result before committing to a full export. The workflow follows a clear sequence: upload, compatibility check, preview, side-by-side comparison, and then an export decision. A key principle is that the before-and-after audio samples must cover the same time segment, eliminating ambiguity that could mislead users into misjudging the processing quality. Compatibility checks are positioned early in the flow to catch unsupported file types or account limitations before any processing work begins. Modeling each stage as a distinct system state, rather than a flag on the final job, prevents the preview from becoming fragile or misleading.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Why Benchmarking Only Success Cases Creates Hidden Performance Debt

A software developer highlights a common pitfall where performance benchmarks measure only successful code paths, ignoring the cost of cache misses and exception handling. In production environments, failed lookups and debug logging can silently degrade performance, yet most AI-generated code patches optimize for the clean, happy path. The author built a small Python harness to compare three lookup variants — try/except, silent dict.get, and logged dict.get — across a deliberate 20% miss rate. Results are measured in both milliseconds and peak memory to avoid misleading single-metric conclusions. The article, prepared as part of MonkeyCode's product outreach, encourages developers to test with realistic miss-rate mixes rather than relying on idealized benchmarks.

0 comments Read more at DEV Community