The modern data stack has become increasingly popular in the analytics community. Patterns like domain-driven design, known from classical software development, are finding their way into analytics contexts. This is the basis of a new paradigm, like Data Mesh. In a Data Mesh, every domain - like a different department for example - wants to solve similar problems with their own business data. Therefore, it’s vital to implement a flexible, lightweight, and manageable, but also secured and monitorable central self-service data platform. With the containerization of services, and using Kubernetes as a runtime, you can build flexible data architectures. Data visualization, data ingestion, orchestration, and ETL tools, as well as Cloud Data Warehouses, should all live together in a kind of a mesh. In this session, learn how Kong's CNCF Sandbox, project Kuma, provides the next level of security when handling data, other business domains, and exchanging data with external systems. Uncover the advantages of end-to-end tracing, data collection, and external access from outside of the mesh using Data APIs.