Complete MLOps guide for 2026: model versioning with MLflow, FastAPI serving, Docker containerization, GitHub Actions CI/CD pipelines, data drift detection, and production monitoring patterns.
AI tools accelerate DevOps work by generating Dockerfiles, GitHub Actions workflows, Kubernetes manifests, and Terraform configs from natural language descriptions. This guide covers practical DevOps AI workflows with real configuration examples.
Learn Kubernetes in 2026 with real-world Deployments, Services, Ingress, ConfigMaps, autoscaling, and Helm charts. Designed for developers moving from Docker to production-grade container orchestration.
Design production CI/CD pipelines in 2026 with GitHub Actions: parallel quality checks, Docker builds, staging deploys, E2E tests, blue-green and canary releases, rollback strategies, and DORA metrics.
A structured 12-month DevOps roadmap covering containers, Kubernetes, CI/CD, cloud platforms, and observability. Ideal for developers transitioning into DevOps or engineers leveling up their infrastructure skills.
Master Docker from installation to production-ready containers. This hands-on guide covers images, containers, volumes, networking, and Docker Compose for developers and DevOps engineers.
Learn Docker Compose v2 from scratch: defining multi-service applications, managing dependencies, networking, volumes, and environment configuration. Essential for every developer running local stacks.
A production-grade Docker checklist covering image size, security hardening, layer caching, health checks, and runtime best practices. Essential reading before deploying containers to any cloud environment.
Deep-dive into Dockerfile optimization techniques: multi-stage builds, layer caching strategies, base image selection, and BuildKit features that cut image sizes by 70-90% and speed up CI pipelines.
Master Docker networking modes: bridge, host, overlay, and macvlan. Learn how container DNS works, how to create isolated networks, and how to configure multi-host networking for production deployments.
Master Docker volume types — named volumes, bind mounts, and tmpfs — with real-world patterns for database persistence, file sharing between containers, backup strategies, and production storage management.
A comprehensive Docker security guide covering non-root containers, image scanning, secrets management, read-only filesystems, capabilities, and seccomp profiles. Essential for teams shipping containers to production.
Master Docker multi-stage builds to create lean production images. Includes real examples for Node.js, Go, Python, and Java with size comparisons, caching strategies, and BuildKit optimizations.
A detailed comparison of Docker and Podman in 2025: daemonless architecture, rootless containers, Docker compatibility, Kubernetes integration, and which tool fits different team workflows. With real migration examples.
A complete guide to automating Docker image builds and registry pushes with GitHub Actions, covering Docker Hub, GitHub Container Registry, multi-platform builds, layer caching, and semantic versioning. Ideal for teams shipping containerized applications.
A production deployment guide for Next.js 15 covering Vercel, Docker, self-hosted Node.js, edge functions, environment variables, cron jobs, and a pre-launch checklist. For developers taking Next.js applications from local development to production.
Docker best practices have matured in 2026: multi-stage builds, rootless containers, layer caching strategies, and security scanning are now table stakes. Learn what production-grade Dockerfiles look like and where teams still get it wrong.
Practical Docker guide for 2026 covering multi-stage builds, Docker Compose for local development, health checks, and production deployment patterns for Node.js and Next.js apps.
Practical microservices guide for 2026 covering service decomposition, synchronous and async communication, event-driven patterns, and Kubernetes deployment. For architects and senior developers.
Use TestContainers to run real PostgreSQL, Redis, and Kafka in tests. Isolate data per test, parallelize safely, and catch integration bugs before production.
Docker eliminates the "it works on my machine" problem forever. In this guide, we'll learn Docker from scratch — containers, images, Dockerfiles, Docker Compose, and production best practices — with real-world examples for Node.js and Python apps.