Name: The Data Mesh and why consider the architectural paradigm
Start: 2022-11-01T18:35:00Z
End: 2022-11-01T18:35:54.000Z
Location: BrightTALK
Rating: 4.2

Join this channel to learn best practices and insights on how to: containerize existing apps for increased cost efficiency, deliver new cloud-native and process-driven apps using microservice architectures, take an agile approach to integrate APIs and data, and do it all in a culture of collaboration using DevOps best practices.

Managing sensitive resources is a fact of life for any developer﹘whether it be credentials for users, access to data sources, or application programming interface (API) keys and tokens. When using Kubernetes as a development and deployment platform, being able to handle these concerns are just as important as the applications themselves. However, the native primitives provided by Kubernetes do not offer the level of protection that many would require from a security perspective. In this session, learn about the various tools and approaches that are available to properly manage sensitive assets when working in a Kubernetes environment, including each of the tradeoffs that need to be considered with each approach. While there is no single solution that can apply to every situation, the strategies discussed can be used to not only raise awareness to the concerns that need to be examined, but to aid in the design of a more robust security posture for working with Kubernetes.

Presenters:
Rob Sedor - Chief Architect, Application Development, Red Hat
Jeremy Davis - Chief Architect, Application Development, Red Hat 
Andrew Block - Distinguished Architect, Red Hat

Red Hat’s developer corner managing secrets in Kubernetes

Realizing when mechanical devices (e.g. pump data, manufacturing devices) are having mechanical issues and are showing signs of failure (via sensors) are important items to know when you need to keep them running 24/7. Therefore, creating failure prediction algorithms and/or model(s) are essential parts of your mechanical equipment maintenance toolbox, but how do you get started?
 
Failure prediction in real time on time series data (gathered by sensors) can be realized with the use of Open Source tools. In this session we will take you through creating data science applications on the edge and how we secure data, models and edge devices.

Dancing with Data Science and Security on the Edge

Companies everywhere are implementing DevOps practices to bring fast innovation of software to market. Frequent pushes of small, microservice updates are in high demand. Federal agencies want in on the action too, and they bring their own sets of challenges.
 
When working within air-gapped environments, security is of the utmost importance, so how do you make it work? Open source solutions don’t always seem like the first choice to turn to. Many of them demand constant Internet access for updates. With the right strategy in place, open source solution can often not only be an option, but the best option. In this session, Jay Hancock, DevOps Manager at Parsons Corporation, will discuss how he and his team have addressed some of the challenging requirements of the defense and intelligence community. He will provide a detailed viewpoint into using open source technologies like kubernetes, containers, and more.

Delivering Innovation in Classified Environments

Quantum computers today are expensive, rare, highly specialized resources, but hold tremendous promise for the future. Realizing this promise will require deep consideration of how to enable useful access to these resources, how to enable all developers (not just quantum specialists) to use them, and bridging classical and quantum applications for developers and operators alike. We’ll discuss the constraints QCs have and how building a hybrid, DevOps approach can unlock quantum computing in the future.

Operationalizing Quantum Computing with DevOps

As opportunities for data science and machine learning flourish across the enterprise, there’s a growing friction between desires to build new systems and responsibilities to extract more value from legacy systems. With a survey of experiences across industries over the last decade – including Federal Government, Oil & Gas, Financial Services, and Precision Healthcare – we’ll explore what it takes to succeed with a modular open systems approach and how it can ease the friction.

Data Science and Machine Learning: What does it take to succeed?

Software engineering has changed dramatically over the years with better collaborative development practices, migration from monoliths to microservices and more. But what about machine learning? How has machine learning based development evolved over the years? In this session, we'll discuss early ML setup and practices and how it's evolved into today's collaborative data science and streamlined ML deployment and MLOps best practices.

Building Modern Machine Learning Pipelines

In this session, we will discuss real, tangible use cases for leveraging artificial intelligence and applied machine learning models to solve problems that affect everyone. We will walk through what it takes to build software that serves more people by creating inclusive teams that are empathetic and courageous.

HumAIn: Empowering Inclusion with Technology

Partner panel with Kyndryl

Featuring:
David Kerr, Red Hat Global Alliance Leader, Kyndryl 
Otto Konopa, Global Red Hat GTM Lead, AWS 
Todd Winey, AWS Global Ecosystem Leader, Red Hat

Partner panel with Red Hat, AWS, and Kyndryl

Hear about the advantages of using Red Hat OpenShift Service over standard Kubernetes and learn the advantages of the managed Kubernetes solution on AWS, Red Hat OpenShift Service on AWS.

Featuring:
Sai Vennam, AWS

Accelerate Container Adoption with Red Hat OpenShift Service on AWS

Join us for an introductory explanation and demonstration of how a ROSA cluster is deployed, configured and managed.

This session will help anyone understand the available approaches when using ROSA for the first time and then the solutions architecture and the recommended approaches to day 2 management of the clusters.

Featuring:
Jim Garrett, Principal Solutions Architect & AWS Alliance - Chief Architect, Red Hat 
Nicholas Gerasimatos, Partner Solutions Architect, AWS

An introduction on how to technically use ROSA and its standard configurations

This webinar showcases how customers can take advantage of the same consistent Red Hat OpenShift experience by migrating from OCP 3 to ROSA.

Featuring:

The benefits of migrating to Red Hat OpenShift Service on AWS

Hear from our Red Hat and AWS leaders about why companies are moving to the cloud and are considering cloud services versus doing things themselves.

Featuring:
Chuck Svoboda, Sr. Director of Managed Services, Red Hat 
Ryan Niksch, Sr. Partner Solutions Architect, AWS

Building and managing containerized apps in the cloud

In the beginning of the pandemic, digital acceleration was viewed largely as a way to enable remote work and ensure business continuity. More than two years later, research indicates that organizations now see digital acceleration as a more permanent fixture in the business landscape. 

In a survey from Harvard Business Review Analytic Services, 91% of IT executives said they plan to maintain the faster speed of digital transformation—or possibly increase it—even after the pandemic ends. Now, IT leaders have a powerful role to play in rethinking the nature of work, enabling hybrid teams to thrive, and setting a new precedent for digital innovation across their organizations. 

During this session, we’ll dive into four focus areas for CIOs and IT leaders as they work toward enabling greater flexibility, resilience, and momentum for digital transformation. From reimagining work, to building digital acumen across the enterprise, to creating more agile operating models, discover what leading CIOs say they’re prioritizing.

Featuring:
Shabnoor Shah, Principal Open Leadership Global Lead & Executive Coach, Red Hat 
Alex Clemente, Managing Director, Harvard Business Review Analytic Services

Four strategies to accelerate digital transformation without burning out talent

Digital transformation has accelerated at a pace that was unthinkable pre-pandemic. In response, companies sped up the creation and delivery of digital products and services, evolving to entirely new operating models. Those transformation speed gains have created some big questions for businesses: For starters, how much of that accelerated pace is sustainable over the long term?

Now, IT leaders have a powerful role to play in rethinking the nature of work, enabling hybrid teams to thrive, and setting a new precedent for digital innovation across their organizations. During this session, we’ll discuss key focus areas for CIOs and IT leaders as they work toward enabling greater flexibility, resilience, and momentum to drive better business outcomes. 

Featuring:
Moderator: Susanna Song  - Storyteller/Podcaster in Tech & Cybersecurity, High Wire Networks; Thought-leading 
Speaker: Rashim Mogha - Product and Business Executive, Founder at eWOW; 
Sponsor Speaker: Shabnoor Shah - Principal Open Leadership Global Lead & Executive Coach, Red Hat

Maintaining Momentum: Strategies to Accelerate Digital Transformation

Join us as we sit down with Michael Tiemann, Red Hat’s former Vice President of Open Source Affairs, who is a true open source software pioneer. Every week, for more than 10 years, Michael Tiemann was one of the first people to welcome new associates to Red Hat. As the founder of the world's first open source software company, Cygnus Solutions, Tiemann provided these new hires with a grounding in open source history, but also open source currency as it related to Red Hat's strategy and opportunities for individual success at Red Hat. 

Michael will discuss why and how enterprise leaders are choosing the open source development model and technologies built with this model to transform their enterprise and differentiate their business.  He’ll share the history of open source,  dispel its myths and share its many benefits, give examples of how it is being used today, and explain why it is gaining in popularity. You’ll learn how to harness its power for success in a world where fear, uncertainty, and doubt continue to prevent people and companies from reaching their true potential. 

Featuring:
Michael Tiemann, Red Hat’s Former Vice President of Open Source Affairs 
Adam Clater, Red Hat Chief Architect

Red Hat Coffee Hour with Michael Tiemann

In this fourth and final session we'll discuss and demonstrate scaling cloud native capabilities to the edge using Red Hat’s industry-leading OpenShift ecosystem.

During the event, we will demonstrate:

- How Red Hat is extending cloud-native operations to the edge, in all its various forms, to drive innovative, next-generation smart systems
- How Red Hat is mitigating risk for revenue-impacting and/or safety critical edge systems by addressing the key challenges of security, management and scale

Scaling to a cloud environment while innovating your business at the edge

CognitiveScale’s Cortex platform helps enable a robust AI Engineering discipline by seamlessly scaling AI applications across cloud platforms via RedHat’s OpenShift. The Cortex platform is embedded on OpenShift deployments providing trust and governance across all models and applications. Cortex brings multiple data models together, composes the AI solution, orchestrates execution, deploys it on any cloud, and optimizes the business impact. This allows for business and IT leaders to work together and leverage a platform that deploys repeatable patterns for AI solution success.

Scale AI applications across cloud platforms

In this session, we will talk about the evolution from Dashboards to Business Intelligence, and Operational Intelligence; and how everything is evolving into a new framework where we use AI/ML that also requires a higher degree of monitoring. We will explore the amount of monitoring required by MLOps, and how Openshift can agnostically host the monitoring applications required to keep an eye on how the operation is doing. This session will conclude with an example of Grafana application hosted in an Openshift environment.

From Business Objectives to Monitoring Dashboards for MLOps using OC

Applying AI to IT Operations(AIOps) is the thing of the hour. Most IT organizations generate a large amount of operations data in the process of operating their software and are beginning to embrace the adoption of AI to support IT operations. Yet, real-world operations data is rarely available as a public dataset. Moreover, most AIOps tools out there are closed source.

In this session, the speakers introduce AI4CI(AI for Continuous Integration), a set of open source AIOps tools involving open operations data from Kubernetes CI/CD platforms. They demonstrate a set of Jupyter Notebooks that are automated using Kubeflow Pipelines into reproducible workflows that collect data from open CI/CD data sources, calculate and visualize key performance indicator metrics, and build AI/ML services to support operations. They also introduce how to build and deploy ML services which can answer questions like “how can we optimize the running time of our tests and prevent bottlenecks in our CI/CD pipeline”, “how to an ML model to efficiently triage a new issue or a pull request”, and “how to preemptively detect patterns in failing tests or builds by looking at the logs”.

By making the tools and relevant data openly accessible, AI4CI aims to cultivate an open source community that fosters collaboration between data scientists and DevOps engineers. 
 
By the end of the talk, the audience will learn how to build AIOps monitoring tools and automated metric dashboards that can help provide more visibility into their tests to better support their CI/CD processes.

Using AIOps to Speed up CI/CD processes

Realizing when mechanical devices (e.g. pump data, manufacturing devices)  are having mechanical issues and are showing signs of failure (via sensors) are important items to know when you need to keep your mechanical devices running 24/7.  Therefore creating failure prediction algorithms and/or model(s) are essential parts of your mechanical equipment maintenance toolbox.  But how do you get started?  Is it hard to curate sensor data? How do you create, train and deploy failure prediction algorithms and models?  What kind of platform do you use for these items?

Failure prediction in real time on time series data (gathered by sensors) can be realized with the use of Open Source tools. We will deliver an overall view of how to start with the generation of new raw sensor data (typically captured by an Edge device), create a failure prediction model and end up with a real time graph that shows alerts warning that a failure is imminent for a mechanical device. 

But that’s not where the story ends.  We also need to address ‘security’.  From transferring and storing data to working with models, security is vital to working with sensors at the Edge.  Taking lessons learned from Cyber Security Crime we will discuss how Edge and IoT hardware can be easy to exploit.  We will then outline what security fundamentals are important to have in place along with common technology mitigations.  
Join us while we take you through creating data science applications on the edge and how we secure data, models and edge devices.

Data Science Day 2022

Most companies have been working to modernize their applications. And yet, when asked, "what do you view as the main driver of innovation at your company?" The response is nearly always that data is the primary driver of innovation. In this talk, we will look at what a data mesh is and how we can transition from a monolithic approach to data, to an approach which can become the data platform for our microservices as we modernize our application architectures.

The Data Mesh and why consider the architectural paradigm

Data Platform

Application Development

Security

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Application Management

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The Data Mesh and why consider the architectural paradigm

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