Tuning

WPF Performance Tips

Practical techniques for diagnosing and fixing sluggish WPF UIs — from visual tree bloat to binding overhead and GC pressure.

WCF Throttling

Learn how ServiceThrottlingBehavior caps concurrent calls, sessions, and instances to protect a WCF service from being overwhelmed under load.

Performance Tuning

Practical techniques for tuning Spark jobs: partitioning, caching, join strategies, memory configuration, and avoiding data skew.

Execution Plans and Tuning

How to read SQL Server execution plans, identify costly operators, and apply indexing and query rewrites to improve performance.

Performance Tips in Julia

Practical techniques for writing fast, type-stable Julia code, from avoiding global variables to benchmarking with BenchmarkTools.jl.

Connection and Buffer Tuning

How worker, connection, and buffer settings determine Nginx's throughput ceiling, and how to tune them safely for high-concurrency workloads.

PostgreSQL Performance Tuning

Learn how to diagnose slow queries and tune PostgreSQL configuration, indexing, and query plans for production workloads.

RabbitMQ Performance Tuning

Practical techniques for maximizing RabbitMQ throughput and minimizing latency, covering prefetch, publisher confirms, queue type choice, and memory/disk alarm…

Elasticsearch Performance Tuning

Practical techniques for tuning indexing throughput, query latency, and resource usage in Elasticsearch.

Kafka Performance Tuning

Practical tuning levers on the producer, consumer, and broker sides for maximizing Kafka throughput and minimizing latency.

Performance Tuning Basics

Practical techniques for diagnosing and fixing slow MongoDB queries, covering the profiler, index hygiene, schema design, and working-set memory.

Hyperparameter Tuning

Explore systematic strategies — grid search, random search, and cross-validation-based tuning — for choosing model settings that are not learned directly from…

Ensemble Methods Cheat Sheet

How bagging, boosting, and stacking combine multiple models to improve accuracy and robustness, with implementations using scikit-learn and XGBoost.

LLM Fine-Tuning Basics Cheat Sheet

Covers full fine-tuning versus parameter-efficient methods like LoRA and QLoRA, and shows how to configure PEFT for fine-tuning with Hugging Face.