Intelligent Operations and Maintenance (AIOps): The application of artificial intelligence technology (such as machine learning, etc.) and data science to IT operation issues, used to enhance and partially replace the main IT operation functions. According to Gartner, AIOps extracts and analyzes IT data that continues to grow in three dimensions: data volume, type, and velocity through loose coupling and scalability, thereby providing support for IT operation and maintenance management products. Promoted by new technologies, AIOps has become the trend of future operation and maintenance development and is a high-level implementation of enterprise-level DevOps on the operation and maintenance (technical operations) side. On December 26, 2022, China Academy of Information and Communications Technology grandly announced the latest batch evaluation results of the AIOps series standards for intelligent operation and maintenance.
Agricultural Bank of China Co., Ltd. (hereinafter referred to as " Agricultural Bank of China ") participated in the project of " integrated production operation and maintenance platform -data analysis platform (Kongming) " project. The project successfully passed the "Cloud Computing Intelligent Operation and Maintenance (AIOps) Capability Maturity Model" carried out by China Academy of Information and Communications Technology (hereinafter referred to as " Academy of Information and Communications Technology ") Part 2: System and Tool Technical Requirements" Standard root cause analysis module excellent level evaluation. It represents that Agricultural Bank of China’s AIOps-related capabilities have reached the domestic leading level.
This batch of evaluations will be officially awarded a license at the "2022 GOLF+ IT New Governance Leadership Forum" hosted by China Academy of Information and Communications Technology on January 6, 2023.
This time, we interviewed Mr. Cai Shizhi, deputy general manager of the R&D Center of the Agricultural Bank of China, and Mr. Jia Lei, director of the Technical Support Department of the R&D Center Beiyan, to discuss in depth the details and stories of the team’s participation in project evaluation, and to share the Agricultural Bank of China’s AIOps practice experience.
- Q&A -
Deputy General Manager of R&D Center of Agricultural Bank of China
Cai Shizhi
Q: Hello teacher, please introduce you and your company, as well as the projects participating in the evaluation this time.
Cai Shizhi: Agricultural Bank of China R&D Center, as a department directly under the head office that carries the important responsibilities of Agricultural Bank of China’s informatization construction and financial technological innovation, provides complete and reliable financial transaction support for Agricultural Bank of China’s domestic and overseas branches and holding subsidiaries in retail banking, corporate banking, investment banking, fund management, financial leasing, asset management, life insurance and other business areas, and provides efficient and stable financial transaction services to more than 800 million customers around the world.AIOps operation and maintenance data analysis platform is an important part of the integrated production and operation and maintenance system of the Agricultural Bank of China. It is an enterprise-level operation and maintenance data analysis platform built for users across the bank based on the AIOps intelligent operation and maintenance concept of "based on data, supported by algorithms, and driven by scenarios". In response to the challenges and pressures brought to operation and maintenance work in the context of business digital transformation and architecture distributed transformation, the platform has created an operation and maintenance data mart, built an operation and maintenance analysis engine, and promoted the implementation of intelligent operation and maintenance scenarios. It uses actual operation and maintenance pain points as the entry point to deeply explore the value of operation and maintenance data, actively carry out innovative practices, and effectively promote the intelligent transformation of our bank's operation and maintenance system.
Q: Congratulations on passing the CAICT AIOps standard root cause analysis module assessment. How do you feel?
Cai Shizhi: intelligent operation and maintenance has been a key direction in the transformation of our operation and maintenance work in the past two years. The successful passing of the evaluation is not only an affirmation of the work results of the project team, but also points out the direction for our subsequent optimization and improvement. In the future, we will continue to increase support and investment in intelligent operation and maintenance, and promote the further promotion and application of AIOps capabilities in Agricultural Bank of China.
Q: Your organization is participating in this evaluation of the AIOps standard root cause analysis module. What are your considerations?
Cai Shizhi: Quickly locating the root cause of faults in is the key to ensuring business continuity, and it is also one of the important goals of building a data analysis platform.In the early stage, Agricultural Bank of China completed the construction of the intelligent root cause analysis function by building a real-time evaluation system for system operation health and constructing an AI intelligent root cause positioning model to quickly locate the system operation status in response to the difficult problems faced in locating the root cause of faults. This time, I participated in the evaluation of this module. On the one hand, I want to verify whether the construction results meet industry standards. On the other hand, I also want to find shortcomings and gaps to prepare for the next step of optimization and improvement.
Agricultural Bank of China
Director of the Technical Support Department of Beiyan R&D Center, Jia Lei
Q: What changes have been brought to enterprises and teams through the AIOps standard root cause analysis module assessment?
Jia Lei: has successfully passed the formal evaluation of the AIOps capability maturity standard. On the one hand, it is an affirmation of the achievements in the intelligent operation and maintenance construction of the Agricultural Bank of China. On the other hand, through comparison with the standards, it has clarified the current shortcomings of the platform and the direction in which it can be improved in the future. At the same time, during this evaluation process, through learning about AIOps standards and communicating with experts in the industry, our operation and maintenance analysis team also benefited a lot and absorbed many advanced concepts, which provided guidance for the team's subsequent optimization direction.
Q: What are the next steps for the development of AIOps work?
Jia Lei: Agricultural Bank of China will continue to promote the construction of AIOps operation and maintenance capabilities. On the one hand, it will promote AIOps capabilities to new technology stacks and comprehensively improve full-link monitoring, analysis, positioning, and processing capabilities under complex distributed architectures such as cloud platforms and microservices. On the other hand, it will pay more attention to AIOps. In applications in the field of business continuity, we further strengthen the capacity building of "supervision, control and analysis" from a business perspective, conduct in-depth analysis and comprehensive linkage of various front-end and back-end operation and maintenance data, identify business fluctuation risks in advance, achieve early discovery, early intervention, early assessment and early processing, and ensure the stable operation of the system.
Q: What are your thoughts on the future direction of AIOps?
Jia Lei: mainly has three aspects. First, AIOps is gradually developing from single to systematic, from using machine learning algorithms to realize specific scenarios to platform-based and systematic development, and providing systematic intelligent operation and maintenance services through the data service capabilities, algorithm service capabilities and scenario construction capabilities provided by the platform; secondly, AIOps Gradually developing from passive response to active prevention, while still paying attention to traditional scenarios such as fault alarms and anomaly detection, it has gradually begun to pay attention to fault prediction, risk discovery and other pre-event scenarios, focusing on improving risk discovery, traceability, management and disposal capabilities; finally, AIOps will be more diversified in empowering areas. In addition to traditional quality and efficiency scenarios, empowering operations and maintenance management, security control and other fields is also the next key direction of AIOps.
project evaluation site picture:
project display
Intelligent operation and maintenance (AI Ops) Capability Maturity Model Introduction
The "Intelligent Operations and Maintenance AIOps Capability Maturity Model" series of standards is led by the China Academy of Information and Communications Technology, Cloud Computing Open Source Industry Alliance, dbaplus community, BATJ and other top Internet companies, as well as major financial and communication companies, jointly developed the first domestic and foreign intelligent operation and maintenance (AIOps) international standard , and was published in the International Telecommunications Union Thirteenth Study Group ITU-T SG13 project successfully established!
Currently, 8 modules have been opened based on the "Cloud Computing Intelligent Operations (AIOps) Capability Maturity Model Part 2: System and Tool Technical Requirements" assessment: anomaly detection, fault prediction, alarm convergence, root cause analysis, fault self-healing, fault prevention, capacity prediction, and knowledge base construction.
dbaplus community joins hands with China Academy of Information and Communications Technology
drives the digital upgrading of the industry
dbaplus community, as a strategic partner of China Academy of Information and Communications Technology Cloud Institute, will jointly promote the promotion and implementation of "Intelligent Operations and Maintenance (AIOps) Capability Maturity Model" series of standards. In addition, in the development and implementation of standards such as "Data Security Governance Capability Assessment (DSG)", "Distributed System Stability Guarantee Capability Assessment", "Financial Big Data Capability Model (DataOps)", "Data Management Capability Maturity Assessment Model (DCMM)" and other standards, the dbaplus community will also continue to carry out in-depth cooperation with the China Academy of Information and Communications Technology to jointly promote Chinese enterprises to consolidate digital support capabilities and accelerate the digital transformation of various industries.
Regarding the "Intelligent Operations and Maintenance (AIOps) Capability Maturity Model" series of standards, intelligent operation and maintenance (AIOps) system and tool evaluation and other related matters, you can contact:
Part of this article Content comes from: CAICT Digital Governance
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