CAICT's first batch of AIOps systems and tools evaluations, Borui Data was rated "comprehensive" for anomaly detection module

Recently, Swift-AI, the intelligent operation and maintenance algorithm platform of Borei Data, successfully passed the first batch of formal evaluations of "Intelligent Operation and Maintenance (AIOps) Capability Maturity Model Part 2: System and Tool Technical Requirements" conducted by the China Academy of Information and Communications Technology (hereinafter referred to as "CAICT"), and the "Anomaly Detection" module passed the comprehensive evaluation.

This means that the comprehensiveness and completeness of the product capabilities of Borei Data's intelligent operation and maintenance algorithm platform have been recognized by the industry, and it also means that Borei Data's AIOps systems and tools have reached the domestic leading level.

AIOps will empower operation and maintenance and bring users a new experience

In the past ten years, technological waves such as cloud computing, big data, and artificial intelligence have been surging, and the value of operation and maintenance has gradually become apparent. The underlying IT infrastructure of enterprises has become more complex, and the scale of software has increased significantly. The original traditional operation and maintenance methods have become increasingly unable to keep up with the pace of the times. At this time, AIOps came into being.

According to Gartner, AIOps extracts and analyzes the ever-growing IT data in three dimensions: volume, type and speed in a loosely coupled and scalable manner, thereby providing support for IT operation and maintenance management products.

The implementation of AIOps directly hits the pain points of traditional operation and maintenance in many aspects. AI algorithms take on the important task of analyzing massive operation and maintenance data, and can automatically and accurately discover and locate problems, improve operational efficiency from the decision-making level, and provide important support for the optimization of enterprise operations and maintenance work in terms of cost, quality and efficiency.

Talking about the future development of AIOps, Sun Li, senior director of product management at Borei Data, said that with the expansion of enterprise business scale and the rise of cloud native and microservices, the complexity of enterprise IT architecture has increased exponentially. However, traditional IT operation and maintenance methods face challenges such as difficulty in finding the cause of a failure after it occurs and long average repair time for failures, and can no longer meet new operation and maintenance requirements. Therefore, it is inevitable to use artificial intelligence to empower operation and maintenance to replace slow and error-prone human decision-making, quickly give operation and maintenance decision-making suggestions, reduce the impact of problems and warn of problems in advance. As the highest-level goal of current operation and maintenance development, AIOps will enable operation and maintenance to bring users a new experience in the future.

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At the same time, Sun Li also emphasized that many current intelligent operation and maintenance products and projects have not achieved ideal results on the enterprise side. The reasons can be classified into three points: First, data collection is separated from the AI ​​platform. The lack of correlation between multi-source data leads to a lack of high-quality data on the AI ​​platform, which in turn leads to poor model training results; second, data collection is mainly based on metrics and logs, resulting in a narrow application scenario and the existence of data island problems; third, the AI ​​platform capabilities still have room for improvement. The current implementation scenarios are mainly based on anomaly detection and intelligent alarms, and the root cause analysis and fault prediction capabilities need to be further improved in the future.

Therefore, in Sun Li's opinion, in the future, enterprises must first build an integrated monitoring and operation and maintenance platform. Integration is the foundation of intelligence. Based on the high-quality observable data collected by the integrated monitoring and operation and maintenance platform and the correlation between the data, the capabilities of AIOps will be further implemented in the integrated monitoring and operation and maintenance platform, thereby achieving the ability to accurately locate problems and gain insights.

It can be foreseen that, with the promotion of new technologies, AIOps will become the development trend of future operation and maintenance, and will be a high-level implementation of enterprises on the operation and maintenance (technical operation) side.

Integrate AIOps capabilities into the full-stack monitoring product line

As a leading APM application performance management vendor, Borei Data has actively embraced the wave of new technological changes such as artificial intelligence and machine learning for many years, and based on AI and machine learning technologies, it has independently developed a core technology system of "data access, processing, storage and analysis technology", and comprehensively deployed rich and extensive intelligent operation and maintenance functions such as intelligent baselines, anomaly detection, intelligent alarms, correlation analysis, root cause analysis, etc., and integrated AIOps capabilities into the end-to-end full-stack monitoring product line, which can provide traditional enterprises with powerful data processing, storage and analysis software tools, help customers integrate various IT operation and maintenance monitoring data, realize unified storage and correlation analysis of data, break down data silos, and build a unified IT operation and maintenance management platform to make the company's IT operation and maintenance more intelligent and automated.

On this basis, Borei Data also relies on complete IT operation and maintenance monitoring capabilities, and uses big data and machine learning technologies to continuously build advanced intelligent operation and maintenance monitoring products. In 2021, it successively launched a new generation of APM products Server7.0 equipped with AI capabilities and a new version of the unified intelligent operation and maintenance platform Dataview, and continuously implemented intelligent anomaly detection, root cause analysis, fault prediction and other scenarios. Based on the capabilities of artificial intelligence, it realizes information integration, feature correlation and business insights in operation and maintenance monitoring scenarios, helping enterprises ensure the smooth operation of digital businesses and guarantee a good digital experience.

Contributing to the development of the AIOps industry

In fact, it is not surprising that Borei Data has received such recognition. Borei Data established an AI algorithm research department very early on, continuously strengthening its product root cause analysis and prediction capabilities, and has established R&D teams in Beijing, Xiamen, Wuhan and other places, and has reached strategic cooperation with key universities to achieve algorithm upgrades and innovations through joint scientific research results.

In the future, Borei Data will continue to focus on the research and development of Swift-AI, an intelligent operation and maintenance algorithm capability platform, and continue to consolidate breakthroughs in related algorithms and capabilities in anomaly detection, fault prediction, intelligent alarm and root cause analysis.

Sun Li said that Swift-AI's capability engine will enable the intelligent experience upgrade of all Borei Data products. Based on Borei Data's integrated monitoring capabilities, AI can be implemented out of the box. Customers do not need to invest a lot of manpower and time in collecting, preparing, and cleaning data. Our intelligent probe capabilities will intelligently collect data for Metrics, Traces, Logs, and related relationships according to the needs of the AI ​​engine. Based on high-quality Telemetry data and powerful algorithm models, an AI experience that is out of the box and accurately locates faults is achieved, helping more companies achieve digital and intelligent transformation.

At the same time, Borei Data will continue to advance the technical and functional refinement of related capabilities, and is committed to working with the industry to promote the formulation of standards in emerging fields such as AIOps, jointly promote industry progress, and contribute to the development of the AIOps industry.