Recently, the global ICT authoritative consulting and analysis firm Gartner released the “Hype Cycle for ICT in China 2020”, and AisaInfo’s AISWare AIOps intelligent operation and maintenance platform product is listed among the typical vendors of Gartner2020 Hype Cycle. This is the first time that AsiaInfo’s AI products being listed on the Gartner Hype Cycle for ICT, indicating that AsiaInfo’s intelligent operation and maintenance products and solutions have achieved a leading position in this field.
The Gartner Hype Cycle is an authoritative assessment system for evaluating the maturity and development stages of new technologies worldwide. The results can be regarded as an important standard and basis for evaluating the trend, technical potential and commercial potential of new digital technology for global manufacturers. The Gartner Hype Cycle typical vendors list is used to recommend representatives of vendors with mature products and unique values in the field, and has sweeping influence in the global ICT industry.
Figure1: Hype Cycle for ICT in China 2020 (Source: Gartner)
AIOps platform technology is one of the important emerging technologies in the ICT field. Compared with 2019, in 2020, AIOps will develop more rapidly in China. According to the Gartner ICT Hype Cycle, the adoption rate of AIOps platform will continue to increase over the next two to five years. Enterprises introduce AIOps to enhance the capability of IT systems in event correlation and analysis, anomaly detection, root cause analysis, etc. Promoting business growth has become an inevitable trend.
AsiaInfo’s intelligent operation and maintenance platform (AISWare AIOps) can be widely used in communication, radio and television, finance, electric power, energy and other industries. It can give full play to the role of technology engine in driving enterprises to improve the intelligent operation and maintenance level and promoting enterprise business development. In particular, it has accumulated a lot of excellent enterprising practices in the intelligent operation and maintenance business of major domestic telecom operators. At present, the AISWare AIOps can support more than 40 scenarios in terms of quality assurance, cost management and efficiency improvement, etc. It can also realize second-level root cause localization and hour-level risk early warning. With powerful functions, advanced technology and good commercial results, the product is highly recognized and praised by the industry and clients. In the past two years, the product has won a number of industry awards, including the runner-up of the 2020 Third International AIOps Challenge, the 2020 Big Data Industry Innovative Technology Breakthrough Award, the “Best Catalyst Award” of TMF Asia Summit, and the Top 100 of China Intelligent Operation and Maintenance in 2019.
Figure 2: Some of the Industry Awards AISWare AIOps Has Won
In the field of AIOps, AsiaInfo is committed to creating intelligent operation and maintenance products and solutions, and actively participates in technology research and development and industry standard setting. Centering on the problems of operation and maintenance monitoring system, AISWare AIOps focuses on the whole process of fault discovery, diagnosis, disposal and prevention, as well as the typical scene requirements of intelligent question and answer and resource optimization to promote AI algorithm innovation and intelligent operation and maintenance ability of component packaging, so as to bring intelligent support and energy for the operation and maintenance system. The product has already applied for a number of technical patents and international standards.
AsiaInfo will continue to promote the AIOps technology, create high-quality intelligent operation and maintenance products and solutions, accumulate best practices of AIOps scenes, set the industry benchmark, and promote the development of intelligent operation and maintenance technology and market in China.
AISWare AIOps of AsiaInfo Brings Intelligent Support and Energy to the Global Operation and Maintenance Systems
AISWare AIOps of AsiaInfo is positioned to provide AIOps capability engine, which brings intelligent support and energy to the global operation and maintenance systems. Based on the AI platform algorithm model of AsiaInfo and in terms of the three aspects of quality assurance, cost management and efficiency improvement, the product provides component packaging for the whole process of fault discovery, diagnosis, disposal and prediction, as well as the intelligent solutions for intelligent decision making, intelligent question and answer, capacity planning and resource optimization scenarios. This builds reusable and evolving operation and maintenance learning software, provides capabilities to the outside world in the form of Open API, supports the rapid implementation of intelligent operation and maintenance requirements, simplifies the docking process, and reduces the cost of operation and maintenance system intelligence integration and intelligence injection.
Figure 3: Product Structure of AISWare AIOps
Improve the overall operation and maintenance efficiency: support intelligent fault location root cause and provide disposal strategy, reduce personnel experience dependence, greatly shorten fault location time and improve the overall operation and maintenance efficiency;
Ensure the operation quality of the system: when the index cracking occurs, the fault warning engine can give early warning to the business and system risks in time, so as to avoid production failures and ensure the operation quality of the system;
Properly control operating costs: support intelligent evaluation and optimization of resource efficiency, carry out reasonable planning of capacity, improve resource utilization efficiency, and further control the operating costs;
Enhance per capita operation and maintenance capacity: through the introduction of AIOps capabilities and technology, operation and maintenance personnel can be liberated from the complex alarm and high-frequency repetition problems, so as to enhance the per capita operation and maintenance capabilities.
High cohesion operation and maintenance components: starting from the three aspects of quality assurance, cost management and efficiency improvement, it provides scenario-based operation and maintenance learning software with high cohesion and low coupling, realizes lightweight capacity docking production, and supports the rapid landing of intelligent operation and maintenance requirements, and is easy to copy and popularize.
Standardized API interfaces: the algorithm model and inference protocol are encapsulated inside the learning software and integrated with the third-party system through Open API interface and component mode, so as to bring intelligent support and energy;
One-stop development and operation: support operation and maintenance developers to invoke existing services according to their business scenario requirements, quickly define, train and release personalized operation and maintenance learning software, and provide operation management and operation monitoring services.
Rich scenarios: Comprehensively support quality assurance, cost management, efficiency improvement and other scenarios, realize the rapid implementation of intelligent operation and maintenance requirements based on the capabilities of operation and maintenance learning software, and solve the actual operation and maintenance problems;
Algorithm accumulation: facing the requirements of complex operation and maintenance scenarios, it builds the capabilities of learning software based on long-term accumulation and self-developed algorithm model. Compared with the open source algorithm, it can better adapt to the actual scenes and achieve better results;
Component integration: decouple from the operation and maintenance system, provide chemical component capabilities, integrate with related systems by means of Open API, simplify the introduction method, avoid repeated construction and reduce the cost of intelligence integration;
Platform support: realize intelligent operation and maintenance capability support with the combination of “platform + learning software”, and provide integrated services of learning software construction, opening, operation and management.
Case 1: Gold Index Anomaly Detection
AISWare AIOps has been introduced by a communication operator to monitor and alert various indicators such as Kafka Topic traffic, traffic volume and load balancing response delay. It has realized the anomaly detection of intelligent dynamic threshold value, the average daily call is more than 12 million times, the fault recall rate is 99%, the precision rate is about 90%, and many failures have been successfully predicted.
Case 2: Alarm Root Cause Analysis and Convergence
AISWare AIOps has been introduced into the O domain alarm convergence scenario of a communication operator. It locates root cause alarm in real time by dynamic mining of alarm RCA rules. Currently, the alarm convergence rate reaches 98%, effectively alleviating the warning storm.
Case 3: Fault Location of Microservice Application System
AISWare AIOps has been introduced into the fault location real-world scenario of a microservice call chain. In terms of full link, it locates the root cause node of the call chain by synthetically analyzing the running state and call relationship of each service. It also combines the platform index operation data and topological relations to further intelligently reason and locate the actual root cause of failures. The actual detection data shows that the average fault recall rate is over 85%, the precision rate is 80%, and the fault location time is greatly shortened.