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The most severe Linux threat to surface in years catches the world flat-footed

Publicly released exploit code for a critical privilege escalation vulnerability in Linux, known as CopyFail (CVE-2026-31431), allows attackers to gain root access across all vulnerable distributions with a single piece of code. The researchers from Theori disclosed the vulnerability 5 weeks after n.. read more  

The most severe Linux threat to surface in years catches the world flat-footed
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The Software Development Lifecycle Is Dead

AI agents collapse the classicSDLC-requirements,design,implementation,testing,review,deployment- into an intent-driven loop. They generate code, tests, and pipelines together. They commit tomain. Automated verification runs. Deployment and release split withfeature flags... read more  

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The Human Infrastructure: How Netflix Built the Operations Layer Behind Live at Scale

Netflix has massively scaled its live content, now streaming over nine shows per day with up to 17.9M peak viewers per game, thanks to a complex Broadcast Operations Center, strict transmission quality standards, and a tiered human operations model, including specialized engineering teams and dedica.. read more  

The Human Infrastructure: How Netflix Built the Operations Layer Behind Live at Scale
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The Silent Failure of Reliability Metrics at Scale: Lessons Learned from a Decade of Broken Metrics

At scale, observability breaks whenSLIsand metrics mix different behaviors and lose clear meaning. Complexity grows: more event types, extra labels, and risingcardinality. That bloats queries, slows evaluation pipelines, and distortsPrometheus,PromQL, andElasticmetrics. Why this matters:Teams must t.. read more  

The Silent Failure of Reliability Metrics at Scale: Lessons Learned from a Decade of Broken Metrics
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@devopslinks shared an update, 1 month ago
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Ubuntu's Next Chapter: Local AI, Confined Agents, and a Bet Against the Cloud-First OS

Ubuntu Ollama Snap

Ubuntu is getting local AI as a native capability over the next year, with inference snaps that install models like any other package, AI-powered accessibility features, and confined agentic workflows for both desktops and server fleets. Canonical is betting on open weight models, local-by-default inference, and snap confinement, a deliberate counter to the cloud-first AI direction Microsoft, Apple, and Google are taking with their operating systems.

Ubuntu's Next Chapter: Local AI, Confined Agents, and a Bet Against the Cloud-First OS
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@sancharini shared a post, 1 month ago

Building Automated Regression Testing From Scratch: A Complete Walkthrough

Learn how to build automated regression testing from scratch in 4-6 weeks. Step-by-step walkthrough covering phases, implementation, tools, and avoiding mistakes.

regression testing services
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@elsie-rainee shared a post, 1 month ago
Full Stack Engineer, WPWeb Infotech

Android Architecture: Components, Patterns & Best Practices Guide

Learn Android architecture with components, patterns, and best practices to build mobile apps that are scalable, easy to maintain, and high-performing.

Android Architecture
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@viktoriiagolovtseva shared a post, 1 month ago

Online event planning template

Planning a webinar, workshop, or team-wide event in Jira? You’re not alone. When you’re managing internal demos, customer-facing webinars, or company-wide town halls, event coordination takes effort and often involves stakeholders across departments.

Missed deadlines, unclear responsibilities, or last-minute changes can turn even a small event into a major time sink. But there’s good news: you can streamline your event workflows using the tools your team already uses.

Instead of juggling spreadsheets, emails, and calendar invites, create a customizable event planning template in Jira. It brings everything into one place, supports collaboration, and helps you keep track of dependencies, deliverables, and last-minute requests in real time.

Zrzut ekranu 2026-05-01 150322
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.