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The Data Dichotomy: Rethinking Data & Services with Streams

Typically when we build service based apps, microservices, SOA and the like, we use REST or some RPC framework. But building such applications becomes tricky as they get larger, more complex and share more data. We can trace this trickiness back to a dichotomy that underlies the way systems interact: Data systems are designed to expose data, to make it freely accessible. But services, instead, focus on encapsulation. Restricting the data each service exposes. These two forces inevitably compete as such systems evolve.

This talk will look at a different approach. One where a distributed log can be used to hold data that is shared between services. Then stateful stream processors are embedded right in each service, providing facilities for joining and reacting to the shared streams. The result is a very different way to architect and build service-based applications, but one with some unique benefits as we scale.


Ben Stopford

Ben is a technologist in the Office of the CTO at Confluent where he has worked on a wide range of projects, from implementing the latest version of Kafka’s replication protocol through to developing strategies for streaming applications. Before Confluent Ben led the design and build of a company-wide data platform for a large financial institution, as well as working on a number of early service-oriented systems, both in finance and at Thoughtworks.