Cloud-Native Data Architecture: Break Away From Data Monoliths for Cloud-Native Applications

October 1, 2018
Cloud Native Application Architecture & Design best practices are well established. We would like to focus this session on Cloud Native Data, introduce the concept, and get into some detail around relevant Architectural and Design concepts. A traditional data architecture is geared towards data consolidation, multi-tenant environment, and supports mixed type of workloads. However, this introduces "data monoliths". In practice, a data monolith is just like an application monolith with the drawbacks of the tight coupling, hard to maintain, limited scalability, and difficult for performance tuning. When cloud native applications are backed by traditional monolithic data service(s), the entire solution will inherit those drawbacks (partial or all) even if the applications are well designed and implemented. What does the data integration for cloud native architecture look like? In this session, HCSC and Pivotal will illustrate some of the concepts for a "Cloud Native Data Architecture" that provides the same level of resilience, scalability, and flexibility for data, as cloud native applications provide for the application logic. Those concepts include adoption of a high performance "Dedicated Data Backing Service" by using Pivotal Cloud Cache (PCC) and the necessary data movement for supporting consolidated data use cases using "Event Driven Microservices". Speakers: Jeff Cherng Advisory Data Engineer, Pivotal Anupama Pradhan Sr Director IT Product – Data, HCSC Filmed at SpringOne Platform 2018
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