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Visualize Azure serverless workflow progress in realtime with pubsub

A suitable way to update a front-end from back-end processes is to use pubsub over WebSockets. In this video I'll show how to use Ably, a cloud based pubsub service, to visualize the progress of a serverless workflow implemented with Azure Functions and Durable Functions. About Ably Ably is an enterprise-grade pub/sub messaging platform. We make it easy to efficiently design, quickly ship, and seamlessly scale critical realtime functionality delivered directly to end-users. Every day, we deliver billions of realtime messages to millions of users for thousands of companies.

Universal Data Distribution with Cloudera DataFlow for the Public Cloud

The speed at which you move data throughout your organization can be your next competitive advantage. Cloudera DataFlow greatly simplifies your data flow infrastructure facilitating complex data collection and movement through a unified process that seamlessly transfers data throughout your organization. Even as you scale. With Cloudera DataFlow for Public Cloud you can collect and move any data (structured, unstructured, and semi-structured) from any source to any destination with any frequency (real-time streaming, batch, and micro-batch).

Enabling Multi-Region for Kong Konnect Cloud

Since the initial launch of Kong Konnect Cloud, one common feature request has (unsurprisingly) been Multi-Region support. Many customers look for SaaS solutions that support a distributed service architecture. Even at its inception, our goal was to support more than a single region. Today, we’re happy to announce Multi-Region Support for Kong Konnect Cloud.

Webinar: Unlocking the Value of Cloud Data and Analytics

From data lakes and data warehouses to data mesh and data fabric architectures, the world of analytics continues to evolve to meet the demand for fast, easy, wide-ranging data insights. Right now, nearly 50% of DBTA subscribers are using public cloud services, and many are investing further in staff, skills, and solutions to address key technical challenges. Even today, the amount of time and resources most organizations spend analyzing data pales in comparison to the effort expended in identifying, cleansing, rationalizing, consolidating, and transforming that data.