Faster Docker Builds: Practical Guide to BuildKit cache, buildx, and image optimization
Slow Docker builds in CI waste developer time and CI minutes. BuildKit (via docker buildx) gives you powerful ways to persist and share build cache across runs and machines —...
Getting started with GitHub Actions for continuous integration: a practical Node.js pipeline
Continuous integration (CI) catches bugs earlier, gives teams fast feedback, and makes releases less stressful. GitHub Actions makes it easy to run CI inside your repository using YAML workflows that...
Intro to observability as code: managing dashboards with GitOps
Dashboards are the musical score of your observability system — they arrange metrics, logs and traces into something your team can “hear” and act on. But like any score, if...
Automating Carbon-Aware DevOps: Practical Patterns to Reduce Cloud Carbon Footprint
Cloud computing brought huge operational flexibility — but it also shifted a lot of energy use (and carbon) into providers’ data centers. Sustainable DevOps focuses on shrinking that footprint without...
Hybrid Executors, Datasets, and KEDA: a practical path from DevOps to MLOps with Airflow on Kubernetes
Moving ML from notebooks to production feels a bit like taking a garage band on tour. You need the right stage (Kubernetes), a reliable manager (Airflow), and a crew that...
Edge Containers, Closer Than You Think: Three Practical Paths to Deploy Apps Near Users
If serving users is like playing a live show, edge computing is bringing the speakers to the front row. You can keep your “amp” (the control plane) in a familiar...
Push, Sign, and Ship: GitOps for ML Models with OCI Images, Argo CD, and KServe
GitOps for ML has often stalled on one messy detail: how to version, transport, and roll out big model artifacts safely and repeatably. Two recent moves make this much easier:...
From DevOps to MLOps: Airflow’s Hybrid Executor and KServe on Kubernetes
Modern MLOps looks a lot like DevOps—pipelines, containers, CI/CD—but with new wrinkles: GPUs, data freshness, and model serving. If you already run Airflow on Kubernetes for data engineering, there’s a...