14 articles
Deep-dive into Dockerfile optimization techniques: multi-stage builds, layer caching strategies, base image selection, and BuildKit features that cut image sizes by 70-90% and speed up CI pipelines.
Master Docker multi-stage builds to create lean production images. Includes real examples for Node.js, Go, Python, and Java with size comparisons, caching strategies, and BuildKit optimizations.
Week 2 of the FAANG mock program pairs Number of Islands and Longest Increasing Subsequence. Solve each correctly, then deliver one optimization upgrade and handle a live follow-up question — the pattern that separates "passes" from "strong hire" ratings.
Master LoRA and QLoRA for efficient fine-tuning of large language models on consumer GPUs. Covers rank selection, target modules, quantization, and training LLaMA 3 and Mistral with minimal resources.
React re-renders are fast but not free. Learn when to apply React.memo, useMemo, and useCallback — and more importantly, when NOT to — using the React Profiler to guide decisions based on real measurements.
Learn how to profile, diagnose, and systematically optimize Node.js applications using built-in tools, V8 flags, and TypeScript patterns. Ideal for backend engineers building high-throughput services.
Optimize LLM inference speed by 10x. Master quantization tradeoffs, speculative decoding, KV cache management, flash attention, and batching strategies.
Reduce API payload sizes and latency through compression, streaming, pagination, and field selection. Master bandwidth optimization for global users.
A comprehensive performance checklist across all layers—database, application, caching, network, and edge.
Master Postgres query optimization using EXPLAIN ANALYZE, covering index types, query rewriting, and plan analysis for production databases.
Deploy open-source LLMs at scale with vLLM. Compare frameworks, optimize GPU memory, quantize models, and run cost-effective inference in production.
Techniques for manually and automatically optimizing prompts including structured templates, chain-of-thought, few-shot selection, compression, and DSPy automation.
Master Qdrant collections, payload filtering, quantization for cost savings, batch operations, and backup strategies for production AI systems.
Explore chunking strategies from fixed-size to semantic splitting, including sentence-window retrieval and late chunking techniques that dramatically improve retrieval quality.