React Performance Optimization
A practical guide to making React apps fast: memoization, virtualization, code splitting, the Profiler, and the patterns that actually matter in production.
1745 posts · page 18 of 37
A practical guide to making React apps fast: memoization, virtualization, code splitting, the Profiler, and the patterns that actually matter in production.
Learn how useRef works in React — DOM access, persisting values across renders, and common patterns that avoid unnecessary re-renders.
Learn async Rust — futures, async/await syntax, the tokio runtime, spawning tasks, channels, and common async patterns.
Handle errors idiomatically in Rust — Result, Option, the ? operator, custom error types, and the thiserror/anyhow ecosystem.
Understand Rust's ownership model — move semantics, borrowing, references, lifetimes, and why the borrow checker exists.
Master Rust's pattern matching — match expressions, if let, while let, destructuring, guards, and patterns in function parameters.
Master Rust traits and generics — defining traits, trait bounds, default methods, trait objects, and generic data structures.
A practical guide to SQL Common Table Expressions: the WITH clause, recursive CTEs, readability improvements, materialization hints, and when CTEs outperform subqueries.
Practical SQL query optimization: reading EXPLAIN plans, choosing the right indexes, avoiding N+1 queries, understanding query planner decisions, and knowing when denormalization makes sense.
Understanding SQL transactions and isolation levels: ACID properties, read phenomena, read committed, repeatable read, serializable isolation, deadlocks, and practical concurrency patterns.
Extract reusable components from Tailwind utility classes: @apply, component extraction patterns, the plugin API, design tokens, and strategies for maintaining consistency at scale.
Build responsive layouts with Tailwind CSS: mobile-first breakpoints, responsive utilities, container queries, and practical patterns for real-world responsive components.
A system design deep dive into building search autocomplete: trie data structures, ranking algorithms, caching strategies, data collection pipelines, and real-time update mechanisms.
Write reliable E2E tests with Cypress — selectors, assertions, network stubbing, custom commands, and CI integration.
Understand the tradeoffs between unit tests and integration tests. Learn the testing pyramid, trophy, and practical strategies for effective test suites.
Learn when and how to mock dependencies in unit tests. Covers stubs, spies, fakes, mock patterns, and how to avoid over-mocking.
Master pytest fixtures for reusable test setup and teardown. Covers scopes, parameterization, factories, autouse, and fixture composition.
Learn to test React components the right way with React Testing Library. Covers rendering, queries, user events, async testing, and best practices.
Go beyond basic generics — constraints, conditional types, mapped types, infer, and real-world patterns for writing type-safe reusable code.
Understand the difference between AI agents and AI pipelines, when to choose each, and how to design systems that combine both for reliability and flexibility.
A practical overview of evaluation frameworks for AI applications: what they measure, how they differ, and how to pick one that matches your workflow.
How to design guardrails and content filters for AI applications, including input checks, output checks, layered defenses, and trade-offs between safety and usefulness.
How Stable Diffusion turns text prompts into images: the latent diffusion architecture, sampling loop, and the practical knobs that shape what you get.
How knowledge distillation lets a small student model learn from a large teacher model, why it works, and how to use it to ship smaller, faster models in production.
An introduction to multimodal AI models that handle text, images, audio, and video, including how they work, how to use them, and where they shine.
A practical comparison of leading open source language models: Llama, Mistral, Qwen, Gemma, and Phi families, with guidance on licenses, sizes, and where each fits.
A practical tour of modern recommendation systems: collaborative filtering, content-based methods, hybrid stacks, and how AI ranking models fit on top of candidate generation pipelines.
How RLHF turns raw language models into helpful assistants: the three-stage pipeline, reward modeling, PPO, and the trade-offs that drive newer alternatives like DPO.
A practical introduction to vector search with FAISS: how indexes work, which index to pick, and how to wire it into a real retrieval pipeline for embeddings.
Why bigger context windows are not always better: cost, attention degradation, retrieval design, and how to architect for long-context tasks.
How LLMOps differs from classical MLOps: evaluation, prompts as code, drift, cost, and the workflows that actually work in production.
How prompt injection attacks work, why simple filters fail, and the layered defenses production LLM systems should deploy.
Build a typed blog with Astro content collections, including Zod schemas, references, and dynamic routes generated from Markdown files.
Master Astro's built-in Image and Picture components to ship responsive, lazy-loaded, modern-format images without external services.
Understand the difference between Astro integrations and adapters, when to reach for each, and how they shape your deployment pipeline.
Learn how Astro ships zero JavaScript by default and only hydrates the interactive components you mark as islands.
Use Astro middleware to run code on every request: auth gates, locals injection, redirects, and response headers. Learn the onRequest signature, the next() flow, sequencing, and common production patterns.
Add fast, static, client-side search to an Astro site using Pagefind. Learn how the index is built, how to wire up the UI, how to scope and weight content, and pitfalls around build order and large sites.
Build JSON APIs and dynamic responses directly in Astro using server endpoints. Learn the file conventions, request and response shapes, dynamic params, and how to mix endpoints with static and SSR pages.
Learn how to add smooth, native page transitions to your Astro site using the View Transitions API with practical examples and gotchas.
Compare Astro and Next.js across rendering models, performance defaults, ecosystem, and use cases to pick the right framework for your project.
CQRS and event sourcing are often mentioned together but solve different problems. This post separates them, shows how they combine, and when each is worth the complexity.
Use circuit breakers to stop cascading failures, with state transitions, timeouts, and tuning advice for production microservices.
A practical guide to evolving production databases safely: expand and contract, online schema changes, dual writes, backfills, and the trade-offs behind each strategy.
Compare range, hash, and directory-based sharding strategies, with guidance on choosing shard keys and operating sharded systems.
Learn how idempotency keys make APIs safe to retry, with patterns for storage, expiry, conflict handling, and common pitfalls.
Compare popular message brokers across delivery guarantees, ordering, throughput, and operations to pick the right tool for the job.
Compare monoliths and microservices across team size, deploy cadence, complexity, and operational overhead to choose the right architecture.