Yang Jinquan
VP of research and development at Tingyun
He is one of the first batch of creators and practitioners of commercialized APM tools in China, currently focusing on the product development and commercial operation of the intelligent observability platform, with a deep understanding and insight into the APM and observability industry. He has been serving head clients in the financial, operator and high-tech industries for many years, providing them with professional technical solutions and product services.
Topic
APM's Next Stop: Harmonizing Observability
With the rapid development of generative artificial intelligence technology, big models are becoming a key engine for driving technological innovation and business change. In this era of big models, whether it is to improve user experience, employee experience, partner experience, supply chain efficiency, or to accelerate IT innovation and product delivery, the enterprise's need for digital transformation has never been more urgent.IT operation and maintenance is facing brand new challenges, which requires transformative technologies to break the data silos, clarify the system operation status, realize faster fault response, more accurate root cause localization, and less user impact, so as to ensure system stability and drive digital transformation. The new challenge for IT O&M is to break down data silos, clarify system operation status, achieve faster fault response, more accurate root cause location, less user impact, and ensure system stability to drive digital transformation. Traditional monitoring tools in the cloud-native context, it is difficult to effectively help enterprises to solve the problem of fault discovery and fault location. Existing tools and analysis models are not intelligent enough, and O&M data has not yet been fully transformed into valuable O&M knowledge. Enterprises urgently need transformative technology solutions to address IT O&M pain points. Transformer's Big Language Modeling technology, combined with the Observability Platform, has become a popular and innovative solution in the field of intelligent O&M. This sharing will delve into the experiences and challenges of applying deterministic AI in observability platforms and intelligent O&M, discussing solutions and best practices. Outline: 1.Challenges brought by digital transformation to IT O&M 2.Challenges and technical solutions encountered in the landing of observability platforms in enterprises 3. Deterministic AI in the field of observability landing practice 4.Exploration of the application of big model technology in the field of observability
