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@kaptain shared a link, 5 months, 3 weeks ago
FAUN.dev()

You Want Microservices—But Do You Need Them?

Amazon Prime Video ditched its pricey microservices maze and rebuilt as asingle-process monolith, cutting ops costs by 90%. No big press release. Just results. Same move from Twilio Segment. And Shopify. Both pulled their tangled systems back intomodular monoliths- cleaner, faster, easier to test, a.. read more  

You Want Microservices—But Do You Need Them?
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@kaptain shared a link, 5 months, 3 weeks ago
FAUN.dev()

The Grafana trust problem

Grafana’s been busy clearing the shelves.Grafana Agent,Agent Flow, andOnCall? All deprecated. The replacement:Grafana Alloy- a one-stop observability agent that handles logs, metrics, traces, and OTEL without flinching. Meanwhile,Mimir 3.0ships with a Kafka-powered ingestion pipeline. More scalabili.. read more  

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@kaptain shared a link, 5 months, 3 weeks ago
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Kubernetes Configuration Good Practices

Stripped down and sharp, the blog lays out Kubernetes config best practices: keep YAML manifests in version control, use Deployments (not raw Pods), and label like you mean it - semantically, not just alphabet soup. It digs into sneaky pain points too, like how YAML mangles booleans (yes≠true), and .. read more  

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@kala shared a link, 5 months, 3 weeks ago
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How I Built a 100% Offline “Second Brain” for Engineering Docs using Docker & Llama 3 (No OpenAI)

Senior Automation Engineer built an offline RAG system for technical documents using Ollama, Llama 3, and ChromaDB in a Dockerized microservices architecture. The system enables efficient retrieval and generation of information from PDFs with a streamlined UI. The deployment package, including compl.. read more  

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@kala shared a link, 5 months, 3 weeks ago
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How to Evaluate LLMs Without Opening Your Wallet

A new mock-based framework lets QA and automation folks stress-test LLM outputs - no API calls, no surprise charges. It runs entirely local, usingpytest fixtures, structured test flows, and JSON schema checks to keep things tight. Test logic stays modular. Cross-validation’s baked in. And if you nee.. read more  

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@kala shared a link, 5 months, 3 weeks ago
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I tested ChatGPT’s backend API using RENTGEN, and found more issues than expected

A closer look at OpenAI’s API uncovers some shaky ground: misconfiguredCORS headers, missingX-Frame-Options, noinput validation, and borkedHTTP status handling. Large uploads? Boom..crash!CORS preflightrequests? Straight-up denied. So much for smooth browser support... read more  

I tested ChatGPT’s backend API using RENTGEN, and found more issues than expected
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@kala shared a link, 5 months, 3 weeks ago
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Writing a good CLAUDE.md

Anthropic’s Claude Code now deprioritizes parts of the root context file it sees as irrelevant. It still reads the file every session, but won’t waste cycles on side quests. The message to devs: stop stuffing it with catch-all instructions. Instead, use modular context that unfolds as needed - think.. read more  

Writing a good CLAUDE.md
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@kala shared a link, 5 months, 3 weeks ago
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1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent

Spotify just gave its internal Fleet Management tooling a serious brain upgrade. They've wired inAI coding agentsthat now handle source-to-source transformations across repos - automatically. So far? Over 1,500 AI-generated PRs pushed. Not just lint fixes - these include heavy-duty migrations. They'.. read more  

1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent
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@kala shared a link, 5 months, 3 weeks ago
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AI and QE: Patterns and Anti-Patterns

The author shared insights on how AI can be leveraged as a QE and highlighted potential dangers to watch out for, drawing parallels with misuse of positive behaviors or characteristics taken out of context. The post outlined anti-patterns related to automating tasks, stimulating thinking, and tailor.. read more  

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@kala shared a link, 5 months, 3 weeks ago
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Cato CTRL™ Threat Research: HashJack - Novel Indirect Prompt Injection Against AI Browser Assistants

A new attack method -HashJack- shows how AI browsers can be tricked with nothing more than a URL fragment. It works like this: drop malicious instructions after the#in a link, and AI copilots likeComet,Copilot for Edge, andGemini for Chromemight swallow them whole. No need to hack the site. The LLM .. 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.