June 29, 2021
Cloud-native computing is transforming data and analytics applications.
Leveraging cloud-native services and platforms, users of AI, advanced analytics, and other data-centric applications can build components as containerized microservices for distributed deployment across public, hybrid, and private cloud environments.
Enterprises generally implement cloud-native computing as a central component of IT modernization. Leveraging sophisticated cloud-computing fabrics and services, enterprises can optimize infrastructure by seamlessly distributing analytics apps, models, workloads, and data.
In the process, they can greatly improve data analytics application performance, scalability, efficiency, portability, and resilience. In addition, users can leverage cloud-native infrastructure to accelerate development and deployment of data analytics throughout multiple clouds and all the way out to edge devices.
This TDWI Checklist discusses three key best practices for migrating enterprise data analytics investments to the emerging cloud-native world of distributed containerized applications.