WD Analyzer-WAN

With a distributed deployment architecture, WatchDog can expand data collection flexibly and use Vertica and Flink to create a data analytics platform, meeting the data collection needs of networks of any size. It supports analyzing millions of flows per minute. Incorporating gRPC Telemetry second-level data collection capacity of network device operation data, WD Analyzer provides visibility to the network operating status in real time.

Embracing new application data stream collection technologies such as iNQA, WD Analyzer can provide insights into application traffic and analytics about application quality. Supports traffic collection through the NetStream application, and displays application flow state information in a multi-dimensional manner. Supports traditional data collection protocols, and a variety of advanced data collection technologies, allowing comprehensive or specific data collection as needed.

WD Analyzer uses big data technologies to implement massive data collection and distributed storage and computation, providing real-time visibility into network operating status and enabling refined operation and maintenance. It is Relying on big data technologies, WD Analyzer can track historical network running states, which helps in fault location and supports O&M tasks such as performance analytics and behavior auditing.

Using distributed computing engines and AI algorithms, WD Analyzer provides both online and offline data analytics to meet intelligent O&M requirements across various scenarios.

WD Analyzer enables full network visibility through comprehensive data collection and analysis, including network device status data, protocol message data, traffic forwarding data, user access process data, and log data. Leveraging machine learning (ML) algorithms and expert systems, it detects network faults in real time, identifies root causes intelligently, and guides administrators in resolving issues. AI-driven analysis uses large-scale data to evaluate network quality, user experience, and application performance, delivering optimization capabilities and ensuring key service assurance.

It utilizes high-performance data collection, real-time expert systems, and AI algorithms to perform fault isolation environment verification, detect faults, assess impact, and execute isolated data forwarding to the analyzer. Through continuous AI analysis of historical network data, WD Analyzer predicts potential faults and performance bottlenecks, enabling O&M teams to take proactive actions and plan in advance.

Combine network device state data analysis with service data quality analysis to accurately reflect the overall health of the network.

Analyze comprehensive, detailed, and real-time metric data from network devices to directly identify the operational state, faults, and risks of the system plane, control plane, and data forwarding plane, enabling white-box diagnostic analysis of the network.

Obtain quality data of TWAMP/NQA probe packets through software-level sniffing services to indirectly analyze service data traffic quality in the network, thereby identifying issues and risks and achieving gray-box insight analysis.