Let's be honest. You're a developer. You're great at writing code, solving complex logic problems, and building features. But lately, everyone—your tech lead, the DevOps team, that new senior engineer—keeps talking about "Dockerizing the app," "container pipelines," and "service orchestration." You've nodded along, maybe even run a docker pull command someone sent you, but you feel fundamentally lost. When you try to read about it, you're hit with a wall of jargon: cgroups, namespaces, storage drivers, and orchestration. It's overwhelming. You are not alone. Many developers find themselves in this exact position. The good news is that you don't need to be a kernel-hacking sysadmin to use Docker effectively. You just need a map to navigate the essentials. This Docker Survival Guide is that map. We'll skip the low-level kernel features and focus on the practical concepts and commands you need to survive, build, and ship yo...

In the world of DevOps and SRE, the Linux kernel is the foundation upon which all applications and services are built. When things go wrong—when latency spikes, throughput drops, or servers buckle under load—the blame game is useless. What's required is data. This is where Linux performance tuning becomes an indispensable skill. It’s the art and science of diagnosing bottlenecks at the system level and optimizing resource usage. While classic tools like top and iostat provide a high-level overview, modern, complex issues demand a more powerful lens. Enter perf , the most powerful profiling tool built directly into the Linux kernel. This comprehensive guide will take you on a deep dive into Linux performance tuning. We'll start with the "why," explore the core pillars of system performance, and then spend significant time mastering the perf command. We'll also cover other essential tools and look at the future of Linux observability with eBPF, providing y...

In less than a decade, containers and Kubernetes have fundamentally reshaped how we build, deploy, and scale software. From monolithic applications to sprawling microservice architectures, this cloud-native stack is the undisputed champion of modern infrastructure. But with great power comes a vastly expanded and dynamic attack surface. The security strategies that worked for static virtual machines are insufficient for the ephemeral, API-driven world of Kubernetes. As we look to the horizon, the evolution of Read more of Container and Kubernetes Security is not just about new tools; it's about a paradigm shift in how we approach defense, moving from reactive gatekeeping to proactive, intelligent, and deeply integrated security postures. The "secure the perimeter" model is dead. In a Kubernetes cluster, the "perimeter" is everywhere—at the API server, within the node, between pods, and all the way left in the CI/CD pipeline. The future of this domain ...

In the complex, distributed world of container orchestration, securing and governing workloads is a paramount challenge. As the central nervous system of your cluster, the Kubernetes API server is the gateway for all changes. This makes Kubernetes Admission Control one of the most critical components for enforcing security, compliance, and best practices. It's the ultimate gatekeeper, deciding what is and isn't allowed to run in your cluster. This deep dive will explore every facet of admission control, from the fundamental concepts and built-in controllers to the dynamic power of webhooks and modern policy engines. What is Kubernetes Admission Control? At its core, Kubernetes Admission Control is a process, enforced by a series of plugins in the kube-apiserver , that intercepts requests *after* they have been authenticated and authorized. Think of it this way: Authentication (AuthN): Asks "Who are you?" (e.g., "You are user 'dev-jane'")...

The landscape of artificial intelligence is moving at a breakneck pace. We've shifted from models that simply predict text to sophisticated systems that can understand and interact with the world. At the forefront of this evolution is the concept of "AI agents"—autonomous systems that can reason, plan, and execute tasks. Powering these agents requires a state-of-the-art "brain," and this is where Google Gemini enters the picture. As Google's most capable and natively multi-modal model, it offers unprecedented capabilities for reasoning across text, images, code, and more. But a great brain needs a body and tools to interact with its environment. This is where open-source frameworks like LangChain and LlamaIndex shine, providing the essential scaffolding to build robust, production-ready agents. This article provides a comprehensive guide for MLOps engineers, DevOps specialists, and AI developers on how to build powerful agents by combining the intelligence ...