Blog — Page 23 of 53
Browsing page 23 of 53 — 634 articles and counting.
The Raft Consensus Protocol: Leader Election, Log Replication, and Safety Guarantees in Distributed Systems
A deep-dive into how Raft achieves distributed consensus through term-based leader election, log replication with majority quorums, and strict safety properties. Covers Raft vs Paxos, split-brain prevention, and how etcd, CockroachDB, and Consul use it in production.
Building Interactive Data Visualizations with D3 and React: Charts, Responsive Layouts, and Real-Time Updates
A practical guide to combining D3.js with React for production data visualizations. Covers DOM ownership, reusable chart components, responsive SVG layouts with ResizeObserver, real-time transitions, accessibility, and performance patterns for large datasets.
Building Production Mobile Apps with React Native and Expo: Architecture, Navigation, and OTA Updates
A practical guide to React Native and Expo architecture decisions for production in 2026: project structure, navigation patterns, state management, native modules, OTA updates with EAS Update, and CI/CD with EAS Build.
Streaming HTML and Progressive Rendering: Chunked Transfer, React Suspense Boundaries, and Out-of-Order Streaming
How modern web frameworks stream HTML to browsers for faster perceived performance. Covers chunked transfer encoding, React 18+ Suspense streaming SSR, out-of-order streaming with placeholder slots, progressive hydration, RSC streaming vs traditional SSR, and practical implementation with Next.js and Hono.
Building a Multimodal AI Pipeline: Processing Images, Audio, and Text with LLMs in Production
A practical guide to building production multimodal AI systems that process images, audio, and text. Covers input preprocessing, modality routing, model orchestration, fusion strategies, latency management, cost control, and partial-failure handling.
LLM Fine-Tuning Infrastructure: Training Pipelines, Dataset Management, and Deployment Strategies for Custom Models
A practical guide to fine-tuning LLMs in production. Covers when fine-tuning actually beats RAG or prompt engineering, dataset preparation and versioning, LoRA/QLoRA training pipelines, multi-GPU compute provisioning, evaluation frameworks, model registry, A/B deployment, and rollback strategies.
LLM Structured Output in Production: JSON Mode, Function Calling, and Schema-Validated Response Patterns
Unstructured LLM output breaks downstream systems. This guide covers JSON mode across providers, function calling patterns, Zod/TypeBox schema validation, retry strategies for malformed output, streaming structured responses, and the real tradeoffs between constrained generation and post-processing validation.
Contract Testing for Microservices: Consumer-Driven Contracts, Pact, and Breaking Change Detection in CI/CD
How consumer-driven contract testing with Pact reduces integration test fragility in microservice architectures, with TypeScript examples and a CI/CD deployment gate pattern.
GitOps in Practice: Declarative Infrastructure, Drift Detection, and Reconciliation Loops
A deep dive into GitOps as a production infrastructure pattern: reconciliation loops, pull vs push deployment models, secrets management, multi-environment promotion, and the operational reality of running GitOps at scale.
OpenTelemetry Collector Architecture: Pipeline Design, Processors, and Scaling Telemetry Ingestion in Production
A production-focused guide to the OpenTelemetry Collector covering receiver and processor configuration, pipeline design, deployment patterns, cost reduction strategies, and horizontal scaling.
Engineering Roadmap Planning: Balancing Feature Delivery, Tech Debt, and Platform Investment
A practical guide for engineering leaders on building roadmaps that balance feature work, tech debt, and platform investment across company stages, with concrete allocation frameworks, quarterly planning mechanics, and stakeholder communication strategies.
Open Source Strategy for Startups: When to Release, License Selection, and Building Developer Community
A practical guide for startup CTOs and engineering leads on when open sourcing makes sense, which license to pick, what to keep proprietary, and how to build a contributor community that does not burn your team out.