A technical talk on architecture choices that help build data-driven microservices with loose coupling and bounded contexts. The workflow and data flows have to be architected together, as concepts of CRUD, CQRS, Event sourcing, and Sagas come to the forefront of app, message, and data scaling. Built on a modern cloud platform, we illustrate a sample food ordering application with microservices patterns that can be applied in any project. A containerized converged database architecture with a variety of data types on the cloud can make it simple to build and operate the data layer, but these principles can be applied to special purpose databases too. The app and data interfaces are explored with support from the data layer making the app coding simpler, especially with Messaging patterns and Saga APIs that reduce the load on the Java developer using a Microservices framework. A free self-service hands-on-lab is available for developers to go through on their own to test these.
KEYNOTE: Oracle -- Simplifying Data-Driven Microservices with a Converged Data Architecture
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Currently the Vice President of Product Management for Messaging and Microservices in the Oracle Database Cloud team, solving data architecture problems for large enterprise customers. Prior product lead in AI/ML and Big Data at HP/Autonomy, HPC developer tools at Intel, and HPC Systems at Sun. He has done a short stint founding a media tech startup in Social Ads and TV Ads platform
Data and transaction processing dev lead for the mid-tier at Oracle for 19 years.