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The latest articles, tutorials, and insights from our DevOps experts.
How to Write a Dockerfile for Node.js Apps (Step-by-Step to Production-Ready)
Master Dockerfiles from first principles with a Node.js + SQLite Recipe App. Learn each instruction, caching strategies, security best practices, and multi-stage builds for efficient, secure containers.
Mapping Kubernetes Components to Linux Primitives
A deep technical exploration of how Kubernetes relies on core Linux primitives—namespaces, cgroups, virtual networking, and filesystem mounts—to orchestrate containers at scale. This article explains how Pods become Linux process groups, how kubelet and container runtimes build isolation boundaries, and how networking and storage map directly to kernel mechanisms.
Understanding ENI Trunking in AWS: Scaling ECS and EKS Without Wasting Nodes
This article explains why Elastic Network Interface (ENI) limits become a hidden bottleneck in ECS and EKS, how ENI trunking works under the hood, and why it enables higher workload density without changing fundamental performance limits.
Running Highly Available Databases in Kubernetes — Part 1
This article explores the realities, trade-offs, and first principles of running highly available databases in Kubernetes. It explains why Kubernetes is optimized for stateless, ephemeral workloads, the challenges databases face under these assumptions, and what operational responsibilities teams inherit when they attempt to run production-critical stateful systems on Kubernetes.
Running Highly Available Databases in Kubernetes — Part 2
This article continues the discussion on running highly available databases in Kubernetes, focusing on practical architecture patterns, operational realities, and responsible design. It covers consensus-based clusters, operator-managed databases, Kubernetes primitives that matter, backup and restore strategies, and how to make informed decisions about running databases in production.
Choosing AWS Services: A Workload-First Framework for Lambda vs ECS
This article presents a workload-first framework for choosing between AWS Lambda and Amazon ECS. It explains why both services can dramatically reduce costs in different scenarios, and shows how execution patterns, operational realities, and long-term economics—not service preference—should drive architectural decisions.