Results for “performance-benchmarking”

Create, run, configure, and review BenchmarkDotNet microbenchmarks for .NET code, covering project setup, comparison strategies, and cost-aware execution.

Profiles application performance across database queries, API call chains, memory usage, bundle sizes, network waterfalls, and frontend rendering, then produces ranked optimization recommendations with estimated impact.

Evaluates RAG pipelines using a filesystem-based benchmark with corpus/ and train.json, running evaluate_rag.py to tune retrieval and generation flags and interpret RAGAS metrics.

Compares the performance of two or more audience segments across key metrics side by side, using Adobe Analytics data to determine winners, losers, and spreads for each metric.

Optimizes SQL queries, designs database schemas, and troubleshoots performance issues. Use when a user asks why their query is slow, needs help writing complex joins or aggregations, mentions database performance issues, or wants to design or migrate a schema. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis, covering index creation, recursive queries, EXPLAIN/ANALYZE interpretation, before/after query benchmarking, or migrating queries between database dialects (PostgreSQL, MySQL, SQL Server, Oracle).