A Java library for accurate latency measurement and statistics, correcting for coordinated omission in in-process tracking.
LatencyUtils is a Java library for tracking and reporting latency statistics, specifically designed to correct for coordinated omission in in-process latency measurements. It solves the problem of skewed latency data caused by system pauses, providing accurate statistics for performance analysis.
Java developers and performance engineers who need precise latency tracking for in-process operations, such as database queries or API calls, in environments where system pauses can affect measurements.
Developers choose LatencyUtils for its automatic correction of coordinated omission, ensuring accurate latency statistics without manual intervention, and its simple drop-in integration using the LatencyStats class.
Utilities for latency measurement and reporting
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Transparently corrects for coordinated omission caused by system pauses, ensuring latency statistics are accurate without manual intervention, as the README emphasizes this core feature.
Supports customizable pause detectors and interval estimators, allowing flexible adaptation to different environments and pause patterns, which enhances integration versatility.
The LatencyStats class provides an easy-to-use object for recording latencies with minimal code changes, making it straightforward to adopt in existing Java applications.
Generates percentile distribution reports for collected data via Histogram objects, facilitating in-depth performance analysis and benchmarking, as shown in the example code.
Designed only for tracking latencies within a single JVM process, making it unsuitable for distributed system monitoring without additional tools or custom extensions.
The correction mechanisms and pluggable detectors may introduce measurable overhead, which could impact high-throughput or low-latency applications, a trade-off not quantified in the README.
Lacks native support for real-time streaming, dashboards, or alerts; users must manually extract and process histograms, adding complexity for operational visibility.