ArchitectureConference50min
Modern Microservices for Enterprise AI: Patterns, Pitfalls, and Practices
This session explores integrating AI into enterprise applications using microservices. It covers best practices for service design, managing evolving AI models, event-driven architectures, data consistency, and minimizing AI hallucinations. Attendees will learn practical strategies, design patterns, and resources for building trustworthy, adaptable AI-powered systems across diverse technology stacks.
talk.summaryAiDisclaimer
Wei HuOracle USA
talkDetail.whenAndWhere
Thursday, June 18, 11:30-12:20
Room 2
talks.roomOccupancytalks.noOccupancyInfo
AI is quickly becoming a must-have for businesses that want to stay competitive. To reduce time-to-value, most efforts involve adding AI features to existing apps using existing frameworks. Microservices can be a great approach for this. Structuring your app as microservices make it easy to incorporate new functionality, mix languages (like Java for the core business logic and Python for AI), and makes it simpler to update new AI features as needs change.
In this session, we'll share what we've learned working with developers on real enterprise projects powered by AI. We’ll talk about practical topics like figuring out the right number of microservices, keeping up with fast-changing AI models, designing event-driven systems so agents can talk to each other, and managing workflows that blend traditional code with AI-driven components. We’ll also touch on smart ways to handle your data, so you get the right balance between isolation and sharing - while making sure everything stays consistent. Along the way, we will cover design practices that make it easier to build with AI. This include organizing services so you can trust AI-generated code and tips for minimizing hallucinations.
While we won’t have live demos during the session, we’ll share links to hands-on labs and code examples you can try afterwards. Our examples will use Spring, Java, and Oracle Database, but these ideas work across lots of tech stacks and programming languages.
In this session, we'll share what we've learned working with developers on real enterprise projects powered by AI. We’ll talk about practical topics like figuring out the right number of microservices, keeping up with fast-changing AI models, designing event-driven systems so agents can talk to each other, and managing workflows that blend traditional code with AI-driven components. We’ll also touch on smart ways to handle your data, so you get the right balance between isolation and sharing - while making sure everything stays consistent. Along the way, we will cover design practices that make it easier to build with AI. This include organizing services so you can trust AI-generated code and tips for minimizing hallucinations.
While we won’t have live demos during the session, we’ll share links to hands-on labs and code examples you can try afterwards. Our examples will use Spring, Java, and Oracle Database, but these ideas work across lots of tech stacks and programming languages.
Wei Hu
Wei Hu is the Senior Vice President of Development for the Oracle Database High Availability. He leads the development of mission-critical database capabilities including Maximum Availability Architecture, Globally Distributed Databases, Active Data Guard, Recovery, and RAC Cache Fusion. Mr. Hu also leads the development of technologies related to AI Microservices, Kubernetes, FinTech, and Blockchain. In addition to product development, Mr. Hu and his team have worked with customers worldwide to architect and deploy their mission-critical applications.
Mr. Hu has B.S. and M.S. degrees from the Massachusetts Institute of Technology (MIT). He has been with Oracle since 1998 and holds more than 50 patents.
Mr. Hu has B.S. and M.S. degrees from the Massachusetts Institute of Technology (MIT). He has been with Oracle since 1998 and holds more than 50 patents.