Blog — Page 33 of 53
Browsing page 33 of 53 — 634 articles and counting.
Designing an A/B Testing Platform: Experiment Assignment, Statistical Analysis, and Feature Flag Integration at Scale
A deep-dive into architecting an A/B testing platform from scratch: consistent user assignment via hashing, mutual exclusion layers, frequentist and Bayesian statistical engines, feature flag integration, and production pitfalls like sample ratio mismatch.
Building a Server-Driven UI System: Backend-Controlled Layouts, Dynamic Components, and Over-the-Air Updates in React
Server-driven UI flips the rendering model so the backend decides what components render and how they are arranged. This article covers the component registry pattern, JSON schema design, dynamic resolution in React, versioning, and when the complexity is actually worth it.
Building Real-Time Multiplayer Backends: State Synchronization, Conflict Resolution, and Latency Compensation in TypeScript
Most multiplayer backend guides stop at getting two clients connected. This covers what actually matters in production: networking model tradeoffs, delta-compressed state sync, conflict resolution under concurrent mutations, client-side prediction with server reconciliation, and how to scale from 10 to 10,000 concurrent players using WebSockets and Cloudflare Durable Objects.
View Transitions API in Production: Smooth Page Navigation, Persistent Elements, and Animation Patterns for Modern Web Apps
The View Transitions API lets you animate between UI states without a JavaScript animation library. Here is how it actually works, where it breaks, and how to ship it in React, Next.js, and Astro without breaking users on unsupported browsers.
Building a Real-Time Classification Pipeline: Streaming Inference, Feature Extraction, and Low-Latency Predictions in Production
Serving ML predictions at low latency is a systems problem as much as a modeling problem. This article covers the full stack: streaming feature extraction, online feature stores, model serving infrastructure, batching strategies, latency budgets, fallbacks, and drift monitoring in TypeScript.
Building a Real-Time Content Moderation Pipeline: Text Classification, Image Safety, and Human Review Workflows in Production
How to build a production content moderation system that handles text and images at scale, covering multi-layer classification, image safety, human review queues, and the feedback loop that keeps model accuracy improving over time.
Text-to-SQL with LLMs: Schema Mapping, Query Validation, and Safe Database Access for AI Applications
LLMs can translate natural language to SQL well enough for internal tools and AI agents, but naive implementations leak schema details, produce invalid queries, and run unguarded against your production database. Here is how to build the pipeline correctly.
Database Reliability Engineering: Automated Failover, Read Replicas, and Recovery Testing for Production Postgres
Most startups treat Postgres as a black box until it breaks. This covers streaming replication, read replica routing, automated failover with Patroni and pg_auto_failover, connection handling during promotion, chaos testing for databases, replication lag monitoring, and how self-managed compares to RDS, Neon, Supabase, and Crunchy Bridge.
Kubernetes Networking Explained: Services, Ingress, Network Policies, and DNS Resolution
Kubernetes networking has a flat model and a surprisingly rich set of abstractions built on top of it. This guide covers the pod network model, all four Service types, Ingress controllers, Network Policies, CoreDNS, and the debugging techniques you reach for when traffic stops flowing.
Multi-Cloud Strategy in Practice: Avoiding Lock-In, Managing Complexity, and When Portability Is Worth the Tax
Multi-cloud sounds like risk mitigation, but it often trades vendor risk for operational complexity. Here is the honest breakdown of lock-in costs, portability taxes, and the decision framework that actually applies in production.
Engineering Sprint Planning That Works: Estimation, Capacity Planning, and Protecting Maker Time
Most sprint planning fails because teams ignore overhead, refuse to leave slack, and treat estimation as a commitment. This is a practical guide to estimation techniques, realistic capacity formulas, and calendar strategies that protect the time engineers need to actually build things.
Running Engineering Through a Hiring Freeze: Prioritization Frameworks, AI Tooling, and Fractional Technical Leadership
66% of CEOs are freezing headcount while expecting AI feature delivery. Here is how engineering managers and CTOs can prioritize ruthlessly, multiply output with AI tooling, and use fractional leadership to fill gaps without breaking the team.