StackPractices

Tag: performance

Browse 86 practical software engineering resources tagged with "performance". Discover code recipes, design patterns, documentation templates, and in-depth guides to help you build, deploy, and maintain production-ready solutions involving performance. Each resource is written for engineers who ship real systems, with copy-paste examples and practical trade-offs.

Performance Engineering

Performance is the result of deliberate design decisions across the stack. It includes efficient algorithms, caching, database indexing, network optimization, and runtime tuning. Without measurement, optimization becomes guesswork.

The resources below show how to identify bottlenecks, profile code, optimize queries, implement caching layers, and tune web delivery. Each recipe connects theory to measurable outcomes.

Every resource includes clear explanations, copy-paste code, and practical warnings. Use them to make informed decisions, avoid production pitfalls, and speed up your delivery. If you are just getting started, read the beginner-friendly articles first; if you are experienced, jump straight to the advanced patterns and architecture guides. New resources are added regularly, so bookmark this page and check back for the latest patterns.

CDN Cache Invalidation Strategies and Patterns

Implement CDN cache invalidation using purge APIs, surrogate keys, tag-based invalidation, and...

Multi-Level Cache with In-Memory L1 and Redis L2

Implement a two-level cache combining in-memory L1 and Redis L2 for low-latency reads with...

Implement an LRU Cache in Node.js

Build a least-recently-used cache in Node.js with O(1) get and set operations using a Map-based...

Cache Function Results with Redis and TTL in Python

Build a Python decorator that caches function return values in Redis with configurable TTL, key...

Implement the Cache-Aside Pattern with Redis

Use the cache-aside pattern to read and write data through Redis, handling cache misses, stale...

Batch Processing Patterns

Design reliable batch processing pipelines for large datasets with retry logic, idempotency, and...

Caching & Memoization in Python, JavaScript, and Java

How to cache expensive computations and API responses using in-memory LRU, TTL, and distributed...

High-Performance DataFrame Operations with Polars

How to use Polars for fast DataFrame operations with lazy evaluation, expression API, streaming,...

UUID Generation: v4, v7, and ULID Comparison

Compare UUID v4, v7, ULID, and nanoid for generating unique identifiers with different tradeoffs in...

Database Connection Pooling

Configure and tune database connection pools to maximize throughput while preventing connection...

Database Replication

Set up and manage database replication for high availability, read scaling, and disaster recovery...

Node.js Caching with Redis: Cache-Aside and TTL Patterns

Cache API responses in Node.js with Redis using cache-aside and TTL patterns

PostgreSQL Query Optimization and Indexing Strategies

Analyze and optimize slow PostgreSQL queries using EXPLAIN, proper indexing, partial indexes, and...

Redis Cache Patterns for High-Performance Applications

How to implement cache-aside, write-through, and write-behind patterns with Redis to reduce...

Analyze and Optimize SQL Indexes with EXPLAIN

Identify missing, unused, and inefficient indexes by reading execution plans and measuring query...

Partition Large Tables by Date or Range

Split huge SQL tables into smaller partitions by date, range, or list to improve query performance...

Bash Parallel Execution

How to run shell commands in parallel with xargs, GNU parallel, and Bash background jobs while...

Stream Process Large Files in Node.js Without Memory Issues

Process GB-sized files in Node.js using streams. Covers readline, transform streams, pipeline,...

Debounce and Throttle Functions in JavaScript

Control function execution rate with debounce and throttle. Covers leading and trailing edge,...

JavaScript Event Loop

Understand how the JavaScript event loop works internally and how to write non-blocking code.