Results for “cache-estimation”

Implements multi-level caching with strategies for invalidation, stampede prevention, and performance monitoring.

Evaluates a containerized framework for deploying distributed big data workloads, measuring execution time and cloud cost scaling from four to eight nodes.

Improve cache efficiency, latency, and throughput for AMS deployments using the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration.

Detects and triages explicitly-unbounded AEM queries (p.limit=-1 or setLimit(-1)) that cause OOMs, safely capping only where provably safe and escalating others for human pagination.

Benchmark, load test, capacity plan, and cache with k6, JMeter, Locust, and pgbench. Use when the user says "slow", "performance", "load test", "stress test", "how many users can it handle", "capacity", "cache", "benchmark", "k6".

Maps external dependencies and I/O boundaries, generates chaos tests for failure modes like timeouts and connection errors, runs them, and reports resilience gaps with fixes.

Measure performance baselines, detect regressions before and after PRs, and compare stack alternatives using browser, API, and build benchmarks.

Measures performance baselines, detects regressions before and after PRs, and compares stack alternatives.

Evaluates computational throughput and real-time efficiency of embedded CPU and GPU platforms by measuring peak FLOPS via a matrix rotation kernel and assessing inference latency and power consumption on a robotic vision pipeline.