Alden developed a performance benchmarking suite for store indexing in the zarr-python repository, focusing on realistic latency modeling to enhance test coverage and reliability. Using Python, he introduced the LatencyStore component, which simulates various latency scenarios to stress-test indexing paths under different conditions. The benchmarks were parameterized to support both sharded and local store configurations, enabling comprehensive performance evaluation across multiple storage backends. This work established a foundation for ongoing performance health checks and regression detection, strengthening the testing framework and aligning with reliability goals. Alden’s contributions demonstrated depth in performance benchmarking and testing within Python-based data infrastructure.