Rtmt _verified_ May 2026

A. Chen, B. Kumar, C. Liu

Code, benchmarks, and configuration scripts available at: https://github.com/example/rtmt-bench Furthermore, we discuss RTMT’s built-in health probes and

The proliferation of real-time data streams in IoT, finance, and observability has exposed limitations in traditional message brokers and monitoring tools, which often sacrifice latency for throughput or reliability. This paper introduces RTMT (Real-Time Monitoring Tool/Transport), a lightweight framework that combines in-memory ring buffers, adaptive batching, and a zero-copy wire protocol to achieve sub-millisecond end-to-end latency while maintaining high throughput. We evaluate RTMT against Kafka and Redis in a microbenchmark environment, demonstrating 3.2× lower p99 latency under 10,000 events/sec and 40% less CPU overhead. Furthermore, we discuss RTMT’s built-in health probes and dynamic backpressure handling, making it suitable for real-time anomaly detection in edge-cloud systems. "Monitoring at scale

[1] Kafka, "The definitive guide," O’Reilly, 2021. [2] ZeroMQ, "Scalable real-time messaging," iMatix, 2019. [3] Prometheus, "Monitoring at scale," CNCF, 2022. "The definitive guide