Name: Event Streaming Microservices with Apache Kafka on Kubernetes
Start: 2019-06-06T21:55:00Z
End: 2019-06-06T21:55:54.000Z
Location: BrightTALK
Rating: 0

Confluent is building the foundational platform for data in motion. Our cloud-native offering is designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organisation. With Confluent, organisations can create a central nervous system to innovate and win in a digital-first world.

What is Apache Kafka® and how does it work?

Apache Kafka® was built with the vision to become the central nervous system that makes real-time data available to all the applications that need to use it, with numerous use cases like stock trading and fraud detection, to transportation, data integration, and real-time analytics.

In this 2 part series you will get an overview of what Kafka is, what it's used for, and the core concepts that enable it to power a highly scalable, available, and resilient real-time event streaming platform. The series begins with an introduction to the shift toward real-time data streaming and continues all the way through to best practices for developing applications with Apache Kafka® and how to integrate Kafka into your environment.

Whether you’re just getting started or have already built stream processing applications, you will find actionable insights in this series that will enable you to further derive business value from your data systems.

This training is comprised of the following topics::

1. Benefits of Stream Processing and Apache Kafka® Use Cases
2. Apache Kafka® Architecture & Fundamentals Explained
3. How Apache Kafka® Works
4. Integrating Apache Kafka® Into Your Environment
5. Confluent Cloud

Register now to learn Apache Kafka® from Confluent, the company founded by Kafka’s original developers.

Part 1: Fundamentals for Apache Kafka

Data Mesh has been gaining traction over the past year or two - and with good reason. With organizations constantly exploring the potential of data, it’s becoming increasingly clear that it’s Data Mesh that may be the key to enabling businesses to truly realize their data-driven initiatives.

In this Confluent webinar, experts are coming together to discuss how Data Mesh has emerged as a paradigm shift in data architecture and to share how teams can be empowered to harness the power of their data at scale. Join Lyndon Hedderly - Director of Customer Solutions at Confluent and Piethein Strengholt - Chief Data Officer (The Netherlands) at Microsoft as they explore:

- The core principles and fundamentals of Data Mesh 
- Best practices for implementing a Data Mesh into your organization, including how businesses can foster a culture of data ownership, accountability, and autonomy 
- What Data Mesh challenges may arise and how to navigate them 
- The stakeholders involved in implementing and managing a Data Mesh
- The business value and new revenue streams a Data Mesh can help realize

Unlocking the Power of Data Mesh: Decentralizing and Democratizing Data

Confluent is hosting a technical thought leadership session to discuss how leading organisations move to real-time architecture to support business growth and enhance customer experience. This is a forum to discuss use cases with your peers to understand how other digital-native companies are utilising data in motion to drive competitive advantage.

The session will be virtual and led by Kai Waehner, a Technical Evangelist and a thought leader in this space. Register today to network with your peers and hear about the use cases that are transforming business.

Data in Motion Use Cases for the CTO

Data is becoming more crucial by the day to the financial services industry. Financial institutions are using their expanded data pools and cloud infrastructure to make better loans, improve their services and offerings to customers, comply with regulations, and detect fraud. 

Many companies, however, are not using data to its full potential. The old ‘data at rest model’ is becoming outdated as new ‘data in motion’ systems provide companies the ability to see how data changes as it flows through their organizations, enabling them to provide new applications and services to their customers and build out more efficient operating systems for their business. 

In this session, we explore how data in motion platforms empower financial services companies to make better decisions when it comes to the way they conduct operations and offer services. 

We discuss: 
-How financial institutions have incorporated data into their operations
-The ways a ‘data in motion’ system differs from the old ‘data at rest’ system 
-How a ‘data in motion’ system helps companies improve their operations and expand their services
-What the future of data looks like for financial services companies

Our speakers:
Duncan Ash is VP of Global Industries at Confluent. He has spent the last 25 years working at the intersection of business and technology to solve complex data and analytics problems, with a specific focus on the financial services industry. Duncan has spearheaded a diverse range of solutions for low-latency trading, market risk, fraud detection, and wealth management, most recently at Splunk, and previously at Qlik, SAS, and Sybase.

Jim Zucker is Lead Architect at Ness Financial Services vertical. With over 25 years of experience, Jim is an expert in digital transformation of risk, trading, credit, derivatives and compliance systems. Before joining Ness, Jim held senior leadership positions at Salomon Brothers, Citi and Calypso and was CTO of EZOPS. He is a US Army Veteran.

Data in Motion: the New Paradigm in Financial Services

Microservices have emerged as a widely discussed and adopted way to build modern and scalable applications. They are easier to build, manage and maintain than monoliths due to smaller code bases; they isolate complexity, allowing for smaller, more agile teams to create services, and they are flexible—allowing the use of various platforms, programming languages, and tools since these choices affect only an individual service and a small team at a time.



While a microservices architecture provides a good pattern for application modernization efforts, refactoring applications and modernizing existing applications is no small feat. Enterprises must do this thoughtfully or risk adopting a short-sighted strategy for their innovation and business needs.



During this webinar, you’ll see how Confluent empowers your developers to innovate faster while incrementally refactoring and migrating your existing applications. Register today.

Application Modernization Through Event-Driven Microservices

This webinar explores the state of data streaming for the Financial Services Industry in 2023. Join this webinar to learn more about:

- What disruptive trends in financial services are driving the pace of innovation
- How data streaming provides the ability to integrate and correlate data in real-time at any scale.
- Which enterprise architectures are trending in the FinServ industry globally

The State of Data Streaming for Financial Services in 2023

Data mesh is a new approach to designing data architectures by embracing organisational and data-centric constructs, such as data management and governance. The idea is that data should be easily accessible and interconnected across the entire business.

In this talk, will cover:
 
- The basics of building a streaming data mesh with Kafka & how Confluent enables this. 
- The four principles of the data mesh: domain-driven decentralisation, data as a product, self-service data platform, and federated governance.
- The differences between working with event streams versus centralised approaches.
- How to onboard data from existing systems into a mesh, modelling the communication within the mesh
- How to deal with changes to your domain’s “public” data, give examples of global standards for governance
- The importance of taking a product-centric view of data sources and the data sets they share.

Apache Kafka®, Confluent, and the Data Mesh

Organisations are struggling to deliver on the promise of the DevOps culture and have instead defaulted to 'you build; you run it!' For many DevOps professionals, this approach is fruitless and ready for a reset. One solution is to take a PaaS approach which provides best-in-class tools to developers allowing them to build and deploy apps as needed.



Join the Confluent team on January 24th to learn how Confluent Cloud enables your developer community. By attending, you will:



1. Learn more about the basic principles of the DevOps culture,
2. Get 'hands-on' with Confluent Cloud by building a pipeline that meets the needs of any development team.
3. Hear a discussion of the CI/CD cycle
4. Learn about SRE and Platform Engineering
5. Discover how to transition from Infrastructure to Environment as a Code

Confluent Cloud, DevOpS and beyond: Managing your environments like a pro

What is Apache Kafka® and how does it work?

Apache Kafka® was built with the vision to become the central nervous system that makes real-time data available to all the applications that need to use it, with numerous use cases like stock trading and fraud detection, to transportation, data integration, and real-time analytics.

This 2 part series you will get an overview of what Kafka is, what it's used for, and the core concepts that enable it to power a highly scalable, available and resilient real-time event streaming platform. The series begins with an introduction to the shift toward real-time data streaming, and continues all the way through to best practices for developing applications with Apache Kafka® and how to integrate Kafka into your environment.

Whether you’re just getting started or have already built stream processing applications, you will find actionable insights in this series that will enable you to further derive business value from your data systems.

This training is comprised of the following topics::

1.Benefits of Stream Processing and Apache Kafka® Use Cases
2.Apache Kafka® Architecture & Fundamentals Explained
3.How Apache Kafka® Works
4. Integrating Apache Kafka® Into Your Environment
5. Confluent Cloud

Register now to learn Apache Kafka® from Confluent, the company founded by Kafka’s original developers.

Part 2: Fundamentals for Apache Kafka

Noam Berman delivers the motivation behind Wix's move from on-premise Kafka to Confluent Cloud.  In addition, he discusses the challenges faced and lessons learned by the Wix team after migrating over 2000 services between Kafka deployments across five regions - with (almost) no downtime to Confluent Cloud.

Wix's Migration to Confluent

Avec ce webinar retail & e-commerce pouver découvrir: 

un cas réel d'utilisation de Data In Motion et l'importance stratégique de Data in Motion
Comment optimiser la chaîne d'approvisionnement en améliorant l'efficacité et en réduisant les coûts
Le rôle de Kafka dans un système d'inventaire en temps réel, le client 360, la détection des fraudes et le Machine Learning.
Architecture microservices avec Kafka
Les possibilités offertes par les déploiements Edge/Hybrid/Multi-Cloud

Retail in Motion avec Confluent

Vous pouvez découvrir la transformation digital de Manufactoring: 

Avec des exemples concrets d'implémentation
une meilleure compréhension des composants logiciel de l'écosystème Confluent pour la mise en oeuvre
comment positionner Confluent dans vos approches actuelles d'Industrie 5.0
comment appréhender les bénéfices métier et techniques d'une adoption de Confluent

Kafka & Confluent: la pièce maîtresse pour vos projets d'Industrie 5.0

From digital banking to industry 4.0 the nature of business is changing. Increasingly businesses are becoming software. And the lifeblood of software is data. Dealing with data at the enterprise level is tough, and there have been some missteps along the way.

This session will consider the increasingly popular idea of a 'data mesh' - the problems it solves and, perhaps most importantly, how a data in motion or event streaming platform forms the bedrock of this new paradigm.

Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.

In this talk, we'll cover: 
- building a streaming data mesh with Kafka 
-the four principles of the data mesh: domain-driven decentralisation, data as a product, self-service data platform, and federated governance. 
-the differences between working with event streams versus centralised approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. 
- how to onboard data from existing systems into a mesh, modelling the communication within the mesh
-how to deal with changes to your domain’s “public” data, give examples of global standards for governance
-the importance of taking a product-centric view on data sources and the data sets they share.

Apache Kafka® and the Data Mesh

Retailers that have embraced the opportunities of the prolonged pandemic are emerging leaner and stronger than before. Contrary to expectations, many senior leadership teams have used the last 18 months to re-invent existing and deploy new business models and practices. Many of these models have data and software at their core rather than tagged on as an afterthought. Consequently, many retailers have captured the attention of a younger demographic, thereby refreshing and extending their relevance.  Urban Outfitters' launch of Nuuly, a clothing subscription rental service, exemplifies this trend.  For over 40 years, Urban Outfitters has been creating unique shopping experiences through well-respected brands that include Anthropologie and Free People. To add Nuuly to this roster, Urban Outfitters engineers built and deployed an event-driven architecture in just six months. The success of this project illustrates the importance of harnessing the power of data in motion and Apache Kafka®.
 
Hear Lawrence Stoker, Senior Solutions Engineer at Confluent, walk through the data in motion use cases that are re-inventing the retail business including:
 
1. Customer 360 and loyalty programs
2. Personalized recommendations and real-time offers
3. Omnichannel experiences
4. Real-time Inventory
5. Real-time analytics and fraud detection
6. Real-time data sharing and supply chain optimization

Data in Motion & Apache Kafka® Use Cases for Retail and eCommerce

Introduction to the Data in Motion 
Use Cases in Financial Services 
Modernizing how you access data and build apps
Logical Architecture

Data in Motion Use Cases for Financial

Microservices, events, containers, and orchestrators are dominating our vernacular today. As operations teams adapt to support these technologies in production, cloud-native platforms like Pivotal Cloud Foundry and Kubernetes have quickly risen to serve as force multipliers of automation, productivity and value. 

Apache Kafka® is providing developers a critically important component as they build and modernize applications to cloud-native architecture.  

This talk will explore:
        • Why cloud-native platforms and why run Apache Kafka on Kubernetes?
        • What kind of workloads are best suited for this combination?
        • Tips to determine the path forward for legacy monoliths in your application portfolio 
        • Demo: Running Apache Kafka as a Streaming Platform on Kubernetes

Event Streaming Microservices with Apache Kafka on Kubernetes

Apache Kafka

Microservices

Cloud-native

Pivotal Cloud Foundry

Pivotal

Confluent

Confluent Platform

Confluent Operator

Kubernetes

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Event Streaming Microservices with Apache Kafka on Kubernetes

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