ONES details network latency measurement backend with nanosecond precision

ONES has introduced a network latency measurement backend designed to deliver precise latency data crucial for managing data center network performance. This capability allows enterprise IT and security teams to monitor network health, ensure service quality, and plan capacity with detailed latency insights.

Technical Overview

The backend operates by deploying agents on SONiC switches and servers that send periodic probes using either ICMP or Transmission Control Protocol (TCP) protocols. This method allows continuous observation of network latency across various paths, capturing real-time data essential for performance evaluation.

The system's architecture enables it to model latency measurement comparably to an optical channel, sending packet bursts to calculate latency with nanosecond-level precision. This approach avoids the overhead associated with per-request correlation, making it well-suited for high-throughput and low-latency environments.

Core Features and Protocol Support

Users can select between ICMP and TCP protocols for measurements, specify destination Intrusion Prevention System (IPS), and configure ports for TCP traffic. This flexibility supports diverse network configurations and monitoring needs.

Periodic latency calculations serve multiple operational purposes, including identifying network bottlenecks, validating compliance with Service Level Agreements (SLAs), and establishing baseline network behavior. The system supports scheduled latency assessments at defined intervals, enabling proactive network management.

Nanosecond Precision Applications

The backend's nanosecond-level accuracy is targeted at environments demanding ultra-low latency such as real-time communications, edge computing deployments, and high throughput networks. This precision facilitates detailed analysis and optimization of network segments critical to these applications.

Scalability and Resilience

Designed to handle high volumes of simultaneous probes, the infrastructure maintains accuracy and stability in dynamic data center environments. It allows for seamless addition of nodes and sustained performance under heavy network loads, supporting enterprise scalability requirements.

Use Cases

ONES' latency measurement backend supports real-time monitoring between endpoints, detection of performance bottlenecks in leaf-spine topologies, optimization of Remote Direct Memory Access (DMA) (RDMA) over Converged Ethernet traffic, and validation of edge computing responsiveness. It aids capacity planning and early detection of network issues to sustain service responsiveness in Artificial Intelligence (AI) and cloud-based data centers.

This Blog Signals brief summarizes the data presented in the vendor blog to assist enterprise IT decision-makers in understanding the technical capabilities and operational implications of ONES network latency measurement backend.