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@anjali shared a link, 6 months, 3 weeks ago
Customer Marketing Manager, Last9

7 Observability Solutions for Full-Fidelity Telemetry

A quick guide to how seven leading observability tools support full-fidelity telemetry and the architectural choices behind them.

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@varbear shared a link, 6 months, 3 weeks ago
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We are replacing OOP with something worse

Object-oriented programming didn’t die - it evolved. Now it lives in the guts of infrastructure. Services talk through strict interfaces, crossing process and network lines like pros. Classes and objects? They're nowOpenAPI schemas,Docker containers, andKubernetes clusters- same old encapsulation ga.. read more  

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@varbear shared a link, 6 months, 3 weeks ago
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Why is Zig so Cool?

Zig bringscross-compilationandC interoperabilityto the forefront - no extra setup, no toolchain fuss. It builds across architectures, links with C code like it was born to, and skips headers entirely. Its real flex?Compile-time execution, sharperror handling, and azero-fat runtime. All wrapped in a .. read more  

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@varbear shared a link, 6 months, 3 weeks ago
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How the classic anime 'Ghost in the Shell' predicted the future of cybersecurity 30 years ago

“Ghost in the Shell” turned 30 this week. Still hits hard. Back in 1989, it dropped cyberpunk bombs that would take the real world decades to catch up with: government-grade AI hackers, behavior-based intrusion detection, malware tailored for humans, and remote code attribution that vanishes into th.. read more  

How the classic anime 'Ghost in the Shell' predicted the future of cybersecurity 30 years ago
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@varbear shared a link, 6 months, 3 weeks ago
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Programming Languages in the Age of AI Agents

GitHub Copilot and friends tend to shine in languages with rich static types - think Rust or Scala. Why? The compiler does the heavy lifting. It flags mistakes fast, keeps structure tight, and gives the AI sharper signals to riff on. But drop that agent into a sprawling legacy repo, and cracks show... read more  

Programming Languages in the Age of AI Agents
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@varbear shared a link, 6 months, 3 weeks ago
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The (lazy) Git UI You Didn't Know You Need

Lazygit is a snappy terminal Git UI that’s picking up steam - and for good reason. It streamlines common tasks like staging, rebasing, and patching without dragging you through clunky menus. The interface sticks close to native Git commands but adds just enough structure to reduce context switches a.. read more  

The (lazy) Git UI You Didn't Know You Need
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@varbear shared a link, 6 months, 3 weeks ago
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Your URL Is Your State

Modern frontend apps love to complicate state. But they keep forgetting the URL - shareable, dependency-free, and built for the job. This piece breaks down how a well-structured URL can capture UI state, track history, and make bookmarking effortless. NolocalStorage. No cookies. No bloated global st.. read more  

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@varbear shared a link, 6 months, 3 weeks ago
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ChatGPT as My Coding Mentor: How I Learned React and Next.js as a Junior Developer

A junior dev leveled up their React and Next.js chops just by writing better prompts. Big wins came from getting specific - like stating their skill level, asking for analogies, and stacking questions to unpack how Next.js splits client and server. Trend to watch:Prompting is a core dev skill for an.. read more  

ChatGPT as My Coding Mentor: How I Learned React and Next.js as a Junior Developer
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@varbear shared a link, 6 months, 3 weeks ago
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How to Benchmark Python Code?

pytest-benchmarknow plugs straight intoCodSpeedfor automatic performance runs in CI - flamegraphs, metrics, and history included. Just toss a decorator on your test and it turns into a benchmark. Want to measure a slice of code more precisely? Use fixtures to zoom in... read more  

How to Benchmark Python Code?
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@kaptain shared a link, 6 months, 3 weeks ago
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How Kubernetes Became the New Linux

AWS just handed overKarpenterandKubernetes Resource Orchestrator (Kro)to Kubernetes SIGs. Big move. It's less about AWS-first, more about playing nice across the ecosystem. Kroauto-spins CRDs and microcontrollers for resource orchestration.Karpenterhandles just-in-time node provisioning - leaner, fa.. read more  

How Kubernetes Became the New Linux
AWX is the open source, community supported upstream project for Red Hat Ansible Automation Platform, formerly known as Ansible Tower. It gives teams a web based interface, a full REST API, and a distributed task engine on top of Ansible, turning command line playbook runs into a managed, auditable automation service.

The project began at AnsibleWorks as the commercial Ansible Tower product, and after Red Hat acquired Ansible, it open sourced the codebase as AWX in September 2017, positioning it as the development ground where new features land before they are hardened into the supported Automation Platform controller. With AWX, you organize automation around projects (synced from Git or other source control), inventories (static or dynamically pulled from cloud providers), credentials (stored encrypted and injected at runtime), and job templates that tie a playbook to its inventory and credentials. On top of that, it adds role based access control, a visual dashboard, job scheduling, workflow chaining, webhooks, and real time job output, so multiple teams can run, track, and delegate automation without sharing SSH keys or sitting at a terminal.

Modern AWX runs on Kubernetes or OpenShift through the AWX Operator, which manages installation, upgrades, and scaling declaratively, reflecting its shift from a single host application to a cloud native, container based platform. Because it is the upstream of a paid product, AWX moves fast and ships frequently, which makes it ideal for labs, learning, and self managed deployments, though teams needing formal support and long term stability typically run the downstream Automation Platform instead.