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Cloud-native environment considerations for decision makers—a webinar series

November 28, 2021, 8:29 a.m. UTC
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Cloud-native environment considerations for decision makers—a webinar series

In this 3-webinar series, we’ll explore several considerations around cloud-native application development, design, and operations. The webinars in this series include:

  • Choose your cloud-native path—an executive checklist
  • Cloud-native, event-driven design for high-value use cases
  • How explainable, predictive decision making can help us trust our AI models

Webinar 1: Choose your cloud-native path—an executive checklist

Speaker: Brian Gracely & Stu Miniman

With a cloud-native strategy, organizations can begin the culture, process, and technology evolutions needed to meet new demands and deliver business innovations faster. 

In this webinar, we’ll discuss how to make decisions that benefit your business, developers, and IT operations teams, including how to:

  • Boost developer productivity
  • Maximize future choice and maintain control of your environment
  • Capitalize on existing investments
  • Make security a top priority

Webinar 2: Cloud-native, event-driven design for high-value use cases

Speaker: David Codelli

Event-driven architecture (EDA) is as old as computing itself, and some would say even older. The basic principle is quite clear: software should react immediately to changes sensed in the relevant environment. However, application of EDA and the design of EDA systems is different in the world of microservices. Additionally, the dramatic decrease in the cost of computing resources has whole new classes of problems that were previously intractable. These problems are addressable using a combination of technology, practices, and above all, a careful attention to design.

In this webinar, we’ll review some of these technologies and practices, and show how carefully designed systems are solving some of the most complex challenges the world faces.


Webinar 3: How explainable, predictive decision making can help us trust our AI models

Speakers: Matteo Mortari & Daniele Zonca

The demand has never been greater for transparent, explainable decision making that is accurate, consistent, and effective. Legislations like GDPR are a result of increasing concerns about privacy, safety, and transparency in general. While AI/ML solutions are great at making sense of high volumes of data, the reasoning process is usually quite opaque, sometimes leaving us baffled as to why it made a particular recommendation.

In this webinar, you’ll hear about the latest research in eXplainable AI (XAI), an approach that combines AI/ML and traditional business rules to better understand the factors that contribute to an automated decision. We’ll introduce you to the latest standards for representing decision logic, and we’ll demonstrate an XAI solution built from open source components that will show how we can finally answer questions about why an automated decision was made.


Brian Gracely

Senior Director of Product Strategy, Cloud Platforms, Red Hat

Brian Gracely  is the Senior Director of Product Strategy for Red Hat cloud platforms, focusing on Red Hat OpenShift. He has 20+ years of experience in strategy, product management, systems engineering, marketing, and mergers and acquisitions. Prior to Red Hat, Brian gained his experience at Wikibon, EMC, Virtustream, NetApp, and Cisco.

Stu Miniman

Director of Market Insights, Cloud Platforms, Red Hat

Stu Miniman is Director of Market Insights on the Red Hat Cloud Platforms team. Prior to Red Hat, he was an analyst and host of theCUBE where he wrote about and interviewed thousands of industry leaders about the intersection of business and enterprise tech.

David Codelli

Product Marketing Manager, Red Hat

David Codelli is a Product Marketing Manager in Red Hat’s Application Services group. Previously, he spent many years in development, product management, and marketing with SeeBeyond and Sun Microsystems, rising to Director of Product Marketing. At various times in his career David has written software for Verizon, McKesson, TIBCO, and General Atomics.

Matteo Mortari

Senior Software Engineer, Red Hat

Matteo Mortari is a Software Engineer at Red Hat, where he contributes in Drools development and support for the decision model and notation (DMN) standard. Matteo believes there is a whole range of unexplored applications for Expert Systems (AI) within corporate business; additionally, he believes defining the business rules on the business rules management system (BRMS) system not only enables knowledge inference from raw data but, most importantly, helps to shorten the distance between experts and analysts, and among developers, end-users, and business stakeholders.

Daniele Zonca

Principal Software Engineer, Red Hat

Daniele Zonca is an Architect of Red Hat Decision Manager and the TrustyAI initiative where he contributes to open source Drools and Kogito projects focusing on predictive model runtime support (PMML), ML explainability, runtime tracing, and decision monitoring. Prior to that, Daniele led the Big Data Development team in one of the major European banks designing and implementing analytical engines.