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@varbear shared a link, 7 months ago

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Build Your Own Database

LSM trees fix the mess naive key-value stores run into. They blendin-memory sorted indexeswithappend-only disk filesto keep things snappy. Writes get logged, not scattered. Reads stay fast. When files pile up,compaction and segmentingkick in to keep storage lean. This is a rewrite of the storage pla.. read more

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@varbear shared a link, 7 months ago

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100X Faster: How We Supercharged Netflix Maestro’s Workflow Engine

The Maestro engine has been revamped for jaw-dropping improvement: a speed boost of100Xwith overhead slashed from seconds to milliseconds. The groundbreaking redesign delivers massive performance gains, solving past workflow development hurdles and elevating user experiences sky-high!.. read more

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@varbear shared a link, 7 months ago

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How I Reversed Amazon's Kindle Web Obfuscation Because Their App Sucked

A developer cracked Kindle Cloud Reader’s font obfuscation, sidestepping randomized glyph swaps withSVG renderingandSSIM-powered perceptual hashingto rebuild actual EPUBs. Amazon rotates font mappings every five pages, using finicky micro-paths to jam scrapers and derail OCR. It wasn’t enough. Syste.. read more

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@varbear shared a link, 7 months ago

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Measuring Engineering Productivity

A former engineering leader lays out a no-nonsense framework for tracking team output without turning into Big Brother. Think:daily Slack updates,weekly GitHub changelogs,tight 1:1s,demo-fueled All-Hands, andauto-verified deploys. It leans onpublic artifacts, not peeking over shoulders - and puts th.. read more

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@varbear shared a link, 7 months ago

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Discussion of the Benefits and Drawbacks of the Git Pre-Commit Hook

Pre-commit hooks catch secrets and fix formatting before bad stuff hits your repo. But if they’re clunky or slow, devs bail. Tools likePre-Commit,Husky, anddevenvare trying to fix that.devenvstands out—hooks are baked right into your Nix env, no extra glue scripts... read more

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@varbear shared a link, 7 months ago

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State of AI Report 2025

The 2025 State of AI Report just landed—China’s catching up fast on reasoning and coding. Models like DeepSeek, Qwen, and Kimi are starting to nip at OpenAI’s heels. AI is thinking longer-term now. Reinforced reasoning and rubric-style feedback are pushing models into deeper, more deliberate plannin.. read more

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@kaptain shared a link, 7 months ago

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Debugging container image creation with a Dockerfile

Docker just made debugging Dockerfiles inVS Codefeel like real development. With the latest Docker extension and Docker Desktop update, you can now set breakpoints, step through builds with F10/F11, poke at variables, and mess with the container’s file system mid-build... read more

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@kaptain shared a link, 7 months ago

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Kubernetes Gateway API in action

The Kubernetes Gateway API leveled up - unifying North-South, East-West, and egress traffic with standard CRDs likeGRPCRoute,HTTPRoute, andReferenceGrant. In a Linkerd world, that means clean, declarative canary releases, granular egress control to outside APIs (say, Mistral AI), and clearer lines b.. read more

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@kaptain shared a link, 7 months ago

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Bootstrapping Rancher’s RKE2 Kubernetes Cluster on a Podman VM with Cilium CNI and MetalLB LoadBalancer

Running RKE2 with Cilium and MetalLB in a lightweight Podman VM on macOS enables experimentation with Kubernetes. Unique network challenges require SSH port forwarding for service exposure... read more

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@kaptain shared a link, 7 months ago

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Exposing Kubernetes Services Without Cloud LoadBalancers: A Practical Guide

Bare-metal Kubernetes just got a cloud-style glow-up. By wiring upMetalLBin layer2 mode with theNGINX ingress controller, the setup exposesLoadBalancer-typeservices—no cloud provider in sight. MetalLB dishes out static, LAN-routable IPs. NGINX funnels external traffic to internalClusterIPservices th.. read more

Levelop is an interview preparation platform designed specifically for working software engineers (typically with 2–6 years of experience) who want to land jobs at top-tier tech companies.

Instead of just handing you endless lists of problems or passive videos to watch, Levelop uses an active, AI-guided approach to help you build the right mental models for tough technical interviews.

Here is how it works:

Two Specialized AI Mentors: * Orion (Coding AI): Instead of just telling you that your code is wrong, Orion steps in when your code fails, maps out where your knowledge gap is, and guides you to fix it yourself.

Aurora (System Design AI): Rather than making you watch a 40-minute video, Aurora has a live conversation with you to explain foundational system design concepts before you even start drawing on the canvas.

Sprint-Based Practice: You practice in structured loops called "sprints," which combine both Data Structures & Algorithms (DSA) and system design problems.

Actionable Feedback Loop: At the end of every sprint, you receive a detailed report. It scores your technical skills, gives you a behavioral profile, and ranks the exact weaknesses you need to focus on during your next sprint.

In short, it is a smart, interactive practice arena that focuses on actively fixing your specific weaknesses rather than just tracking how many hours you spend studying.