With the launch of the Cloudera Public Cloud 7.2.12, the Streams Messaging for Data Hub deployments have gotten some interesting new features! From this release, Streams Messaging templates will support scaling with automatic rebalancing allowing you to grow or shrink your Apache Kafka cluster based on demand.
There are many good uses of data. With data, we can monitor our business, the overall business, or specific business units. We can segment based on the customer verticals or whether they run in the public or private cloud. We can understand customers better, see usage patterns and main consumption drivers. We can find customer pain points, see where they get stuck, and understand how different bugs affect them.
By Jean-Baptiste Thomas, Pure Storage & Yaron Haviv, Co-Founder & CTO of Iguazio You trained and built models using interactive tools over data samples, and are now working on building an application around them to bring tangible value to the business. However, a year later, you find that you have spent an endless amount time and resources, but your application is still not fully operational, or isn’t performing as well as it did in the lab. Don’t worry, you are not alone.
With the latest release of Cloudera DataFlow for the Public Cloud (CDF-PC) we added new CLI capabilities that allow you to automate data flow deployments, making it easier than ever before to incorporate Apache NiFi flow deployments into your CI/CD pipelines. This blog post walks you through the data flow development lifecycle and how you can use APIs in CDP Public Cloud to fully automate your flow deployments.
