Archives

A practical guide to building a cost-effective security platform on Azure Kubernetes Service using ACR and GitHub Actions CI/CD — covering Trivy, Falco, Checkov, Kubescape, Grafana, and Dependabot.

A practical guide to managing multiple Python versions—including the latest Python 3.15—on Linux, macOS, and Windows using pyenv and Python virtual environments (venv).

A practical guide to modern Playwright testing with the latest CLI workflows, GitHub Actions automation, Playwright MCP Server, and complex enterprise authentication scenarios such as Microsoft Entra ID and Okta.

A curated roundup of the biggest AI and SRE developments in 2026 — from autonomous on-call agents and evolved observability stacks to must-follow GitHub repos, Claude Code tips for ops teams, and the best courses to level up this year.

A comprehensive breakdown of the Kubernetes ecosystem — from container orchestration and GitOps to ML pipelines and LLM inference — covering 21 essential tool integrations every practitioner should know.

A forward-looking analysis of how Site Reliability Engineering has evolved since Google's 2016 book — from Kubernetes complexity and unified observability to AIOps, platform engineering, and the blurred line between SRE and autonomous systems.

A deep technical exploration of how Site Reliability Engineering was born at Google, grounded in the O'Reilly SRE book — covering SLIs/SLOs/SLAs, error budgets, toil, incident management, and why the discipline became an industry standard.

A comprehensive look at the modern authentication and authorization landscape in 2026: Passkeys (WebAuthn), optimized M2M auth, decoupled policy engines like OPA and Cerbos, identity-aware proxies, and AI-driven risk-based authentication.

A deep dive into what a DevOps agent in AWS is, how it works using services like Lambda, EventBridge, Bedrock, and Terraform, and why it represents the next evolution of autonomous cloud operations.

Enterprise guide to building a production AI stack with Python, TensorFlow, and PyTorch. Covers installation, GPU setup, distributed training, model serving, security best practices, and top GitHub projects.

A production-grade comparison of MLflow and Kubeflow for enterprise MLOps. Covers architecture, installation on Ubuntu, Kubernetes deployment patterns, security best practices, and top GitHub projects.

A production-grade guide to installing NVIDIA NemoClaw — the security reference stack for running OpenClaw agents inside OpenShell sandboxes. Covers architecture, prerequisites, secure installation, network policies, and best practices.

A security-first guide to installing OpenClaw on Ubuntu. Covers verified installation methods, sandboxed environments, firewall rules, API key management, and Docker isolation for running an always-on AI assistant safely.

JDK 26 ships a wave of language refinements and API upgrades. Explore every new feature with hands-on code examples, an enterprise impact analysis, and a step-by-step migration checklist.

A comprehensive look at where TensorFlow is used in 2026, which industries rely on it most, and which modern alternatives are challenging its dominance in the ML ecosystem.

A comprehensive guide to Kamal — the deployment tool from 37signals (Basecamp/HEY) that deploys containerized apps to bare-metal servers with zero downtime. Covers installation, adoption, examples, and cost analysis.

A complete guide to Dokku — the original open-source Heroku alternative powered by Docker. Covers installation, git-push deployment, plugin ecosystem, and cost analysis for startups.

An in-depth guide to CapRover — the battle-tested open-source PaaS for deploying apps on your own servers. Covers installation, adoption, use cases, and cost analysis for startups.

A detailed guide to Dokploy — the minimal, open-source self-hosted PaaS for deploying Docker applications. Covers installation, adoption, use cases, and cost analysis for startups.

A complete guide to Coolify — the self-hosted PaaS that lets you deploy apps, databases, and services on your own servers. Covers installation, adoption, real-world examples, and cost analysis.

A comprehensive guide to Qovery — the deployment platform that gives you Heroku-level simplicity on your own AWS, GCP, or Azure account. Covers setup, adoption, use cases, and cost analysis.

An in-depth guide to Northflank — the developer platform that combines the ease of Heroku with the power of Kubernetes. Covers setup, adoption level, use cases, and cost analysis for startups.

A deep dive into Fly.io — the platform that runs your apps on micro-VMs across 30+ regions worldwide. Covers installation, adoption trends, multi-region architectures, and cost analysis for startups.

A comprehensive guide to Render — the managed cloud platform built to replace Heroku. Covers setup, adoption trends, real-world architectures, and a startup-friendly cost analysis.

A complete guide to Railway — the managed platform that lets you deploy apps, databases, and cron jobs from a Git push. Covers installation, adoption, real-world examples, and cost analysis for startups.

A deep dive into Agent Skills for SRE and DevOps—what they are, how engineers are adopting them in 2026, and a complete hands-on example building a Terraform Azure best-practices skill that avoids Microsoft Defender for Cloud alerts.

A curated collection of the best technical publications, developer communities, and engineering blogs to follow in 2026—sites with InfoQ and DZone-level depth, strong editorial standards, and consistent output of high-quality content.

A curated guide to the most popular open-source GitHub repositories powering AI Agentic architectures, enterprise agentic AI frameworks, and document extraction in 2026, ranked by stars and forks, with analysis on why each matters.

Exploring the rise of pgvector, the power of relational context in RAG, and why Postgres is becoming the gold standard for AI-driven applications.

A deep-dive into the convergence of document extraction and chatbot agents—the defining enterprise AI pattern of 2026. Covers architecture, tooling, evaluation, and build-vs-buy guidance for engineering teams.

Agentic AI systems combine autonomous agents, orchestration logic, and guardrails to automate document-heavy workflows while keeping humans in control...

Prompt engineering is the art and science of crafting inputs that guide Large Language Models (LLMs) to produce accurate, useful, and reliable outputs...

Spring AI applications bring the power of large language models to enterprise Java development, but deploying these applications to production require...

Large Language Models (LLMs) are powerful, but they have a critical limitation: they only know what they were trained on. Ask them about your company'...

Legacy systems represent decades of business logic, institutional knowledge, and critical operations. While these systems may run on older technologie...

The intersection of enterprise Java development and artificial intelligence has reached an exciting milestone with Spring AI's integration of the Mode...

As organizations scale their cloud-native infrastructure, the complexity of managing deployments grows exponentially. What works for a single develope...

Observability is the cornerstone of running reliable production workloads on Kubernetes. If you can’t see what your pods are doing, you can’t fix them...

Welcome to **yisusvii Blog**! I'm excited to launch this space where I'll be sharing my thoughts, experiences, and learnings about Cloud Computing, De...