NAMAN SHARMA

Spending the last few days deep diving into the docs for my LFX contribution. Mapping out how urunc can use Firecracker’s socket design to start the VMM in the background and parallelize the setup. Handling the edge cases now to make the coding phase a lot smoother. #LFX

Not all virtualization is created equal. 🖥️ If you think KVM is just "software emulation," you’re living in the past. Here is the breakdown of how we went from 5% speed to nearly 100% bare-metal performance: #Virtualization #KVM #CloudComputing #DevOps #TechExplained #Linux

#DevOps #CloudNative #Kubernetes #Docker #OpenSource #PlatformEngineering #SRE #InfrastructureAsCode #OCI #AIOps #DevEx #GitOps #MLOps #DevSecOps #InternalDeveloperPlatform #Automation #CloudComputing #SoftwareEngineering

Emulation translates every instruction. KVM lets the guest speak the hardware's native language. Eliminate the middleman for raw speed. #AWS #Serverless #CloudComputing #Engineering #Docker #Kubernetes #DevOps #CloudNative #OCI

From a laptop in Patiala to a specific EPYC core in Mumbai. aws lambda invoke myfunction The journey: Request hits the fiber Lands on a specific rack in ap-south-1 Firecracker spawns a microVM out of thin air Code executes All that orchestration for a 10ms round trip. #AWS

Firecracker is a VM controller (Small Program written in Rust). KVM is a feature/Kernel Module inside the Linux kernel that turns your Linux system into a hypervisor (VM host). Interface → /dev/kvm : Lets user programs control it. #DevOps #DevOpsLife #DevOpsEngineering

Everything runs on EC2 is a Myth. EC2 is a house; Firecracker is a secure, temporary sandbox. That’s how AWS scales millions of tasks instantly without the overhead. 🚀 #AWS #CloudComputing #DevOps #Serverless

Do you remember when you joined X? I do! #MyXAnniversary

> be Linus Torvalds > 21 year old Finnish student > just wanted a free operating system > writes it from scratch in his bedroom > posts it online "hey this is just a hobby, nothing serious" > 33 years later > powers 96% of the world's servers > runs on every Android phone > NASA uses it > your bank runs on it > the internet runs on it > all free, all open source 🚨 Most importantly, he isn't bald yet. the kid who just wanted a free OS accidentally took over the world absolute legend 🐐

Had a really insightful meeting with the mentors behind urunc #urunc #CloudNative #Kubernetes #DevOps #OpenSource #DistributedSystems #PlatformEngineering #SRE #Infra #SystemsDesign #LowLevel #BackendEngineering #Containers #Virtualization #Unikernels #Web3Infra #Scalability

Most people think Skills and MCP are the same thing. They're not. And confusing them is costing you weeks of wasted architecture decisions. I just mapped the entire Agentic AI extension stack on a whiteboard — here's the breakdown: 𝗦𝗸𝗶𝗹𝗹𝘀 Reusable knowledge modules that agents load on-demand. The agent scans metadata first, then loads full instructions only when relevant. This is called Progressive Disclosure — it keeps your context window clean while giving agents deep domain expertise when they need it. Think of them as training manuals for AI. 𝗠𝗖𝗣 (𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹) The universal connection layer between agents and external tools. Standardized protocol — like USB-C for AI. 10,000+ MCP servers in the ecosystem today. Now governed by Linux Foundation's Agentic AI Foundation. If Skills teach you to cook, MCP gives you the kitchen. 𝗦𝘂𝗯𝗮𝗴𝗲𝗻𝘁𝘀 Independent agent instances running in isolated context. They can use a different model, different tools, different permissions than the parent agent. Like specialized team members with their own workspace. You delegate. They execute. They return summaries. 𝗛𝗼𝗼𝗸𝘀 Deterministic scripts that fire outside the agent loop entirely. Pre-tool, post-tool, on-edit, on-notification triggers. The LLM does NOT control these. Pure event-driven automation. Think of them as tripwires — when X happens, do Y. Always. 𝗖𝗟𝗔𝗨𝗗𝗘. 𝗺𝗱 Always-on project context loaded every single session. Your conventions. Your patterns. Your team preferences. The sticky note permanently on your monitor. 𝗣𝗹𝘂𝗴𝗶𝗻𝘀 The packaging layer that bundles everything above — Skills + Hooks + Subagents + MCP configs into one installable, shareable unit. Here's what most architects miss: These are not competing approaches. They are layers that stack: Skills = WHAT to know MCP = HOW to connect Subagents = WHO does the work Hooks = WHEN to automate CLAUDE. md = WHERE you ground it Plugins = HOW you ship it The real power is in the combination: CLAUDE. md loads project context → Skill provides domain expertise → MCP connects to external systems → Subagent executes in isolation → Hook automates the handoff → Plugin packages it all for the team If you want to excel at building agents in 2026, stop picking one layer over another. Learn to orchestrate all six together. That's what separates demo agents from production agents. Which layers are you actually using today?

#DevOps #DevOpsLife #DevOpsEngineer #DevOpsCulture #CloudComputing #CloudNative #AWS #Azure #GCP #Docker #Kubernetes #K8s #Containerization #CICD #Automation #GitOps #InfrastructureAsCode #Unikernal #SRE #PlatformEngineering #CloudInfrastructure #DistributedSystem

Docker explained in 2 minutes! Most developers use Docker daily without understanding what happens under the hood. Here's everything you need to know. Docker has 3 main components: 1) Docker Client: Where you type commands that talk to the Docker daemon via API. 2) Docker Host: The daemon runs here, handling all the heavy lifting (building images, running containers, and managing resources) 3) Docker Registry: Stores Docker images. Docker Hub is public, but companies run private registries. Here's what happens when you run "docker run": • Docker pulls the image from the registry (if not available locally) • Docker creates a new container from that image • Docker allocates a read-write filesystem to the container • Docker creates a network interface to connect the container • Docker starts the container That's it. The client, host, and registry can live on different machines. This is why Docker scales so well. Understanding this architecture makes debugging container issues much easier. You'll know exactly where to look when something breaks. ____ Find me → @_avichawla For more insights and tutorials on ML and AI Engineering!

Unpopular opinion: If you can't code, you can't vibe code.

Linux is free Docker is free Kubernetes is free Git is free GitHub is free GitHub Actions is free GitLab is free Python is free Node.js is free Go is free PostgreSQL is free MySQL is free MongoDB is free Redis is free Terraform is free Ansible is free Jenkins is free Prometheus is free Grafana is free NGINX is free Apache is free VS Code is free Postman is free Figma is free Vercel is free Netlify is free AWS is free tier GCP is free tier Azure is free tier ChatGPT is free Claude is free Gemini is free Perplexity is free Hugging Face is free Ollama is free Stable Diffusion is free TensorFlow is free PyTorch is free LangChain is free What’s stopping you from becoming the greatest engineer?

URUNC #DevOps #DevOpsLife #DevOpsEngineer #DevOpsCulture #CloudComputing #CloudNative #AWS #Azure #GCP #Docker #Kubernetes #K8s #Containerization #CICD #Automation #GitOps #InfrastructureAsCode #Unikernal #SRE #PlatformEngineering #CloudInfrastructure #DistributedSystem

Roadmap to learn Agentic AI 🚀 AI fundamentals Python + frameworks LLMs Agents architecture Memory + RAG Planning & decision-making RL & self-improvement Deployment Real-world automation Agentic AI = full-stack intelligence. Credit: Tiksly #AgenticAI #LLM #RAG #A

QEMU: the invisible machine builder ⚙️ Powering cloud, VMs & containers#QEMU #KVM #Cloud #DevOps #Kubernetes #Linux

Raw QEMU vs urunc #nanovms #DevOps #Docker #CloudNative #Unikernel #urunc #Kubernetes

@Palak3312 Mnc

As a fresher, which would you choose- startup MNC