TIBCO BWCE and Netflix' Hystrix Circuit Breaker for Cloud Native Middleware Microservices

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These slides show how to use TIBCO BusinessWorks Container Edition (BWCE) with Netflix' Hystrix Open Source Implementation of the Design Pattern 'Circuit Breaker' to develop, deploy and monitor cloud native middleware microservices. Video recording with live demo: https://youtu.be/VL7-T6IIuZk Find more information about cloud native middleware at https://community.tibco.com/wiki/microservices-containers-and-cloud-native-architectures

Tecnología

Kai Wähner
Technology Evangelist
kontakt@kai-waehner.de
LinkedIn
@KaiWaehner
www.kai-waehner.de
Cloud Native Microservices (January 2017)
Circuit Breaker Design Pattern
with Netflix’ Hystrix and TIBCO BusinessWorks Container Edition (BWCE)

© Copyright 2000-2017 TIBCO Software Inc.
Distributed Microservice Architecture
http://blogs.gartner.com/gary-olliffe/2015/01/30/microservices-guts-on-the-outside/
”That complexity
has moved and
[…] increased [to]
the outer
architecture.”

© Copyright 2000-2017 TIBCO Software Inc.
New
Cloud Native
Design Patterns
emerging these days…

© Copyright 2000-2017 TIBCO Software Inc.
Circuit Breaker
Resilience Design Patterns
Features
• Fail fast and rapidly recover
• Prevent cascading failures
• Latency tolerance logic
• Fault tolerance logic
• Fallback Options
http://martinfowler.com/bliki/CircuitBreaker.html
https://github.com/Netflix/Hystrix/wiki
maxFailures = 5
resetTimeout = 1min
callTimeout = 10s
à maxFailures++

© Copyright 2000-2017 TIBCO Software Inc.
Netflix’ Hystrix – A Circuit Breaker Implementation
https://github.com/Netflix/Hystrix

Hystrix Dashboard
Hystrix Dashboard - Tech Talk and Demo (10min) :https://www.youtube.com/watch?v=v3pAMHdR4BM

© Copyright 2000-2017 TIBCO Software Inc.
Circuit Breaker Configuration in BWCE
Rest Consumer à Calls Rest DB Service

© Copyright 2000-2017 TIBCO Software Inc.
BWCE Documentation
https://docs.tibco.com/pub/bwce/2.2.0/doc/html/GUID-57E90053-D9FF-4C44-9BA0-FF0FA5B0327E.html

© Copyright 2000-2017 TIBCO Software Inc.
Develop Deploy
Commit
Build
Config
Demo Setup

© Copyright 2000-2017 TIBCO Software Inc.
Live Demo
Cloud-Native
Middleware Development
• TIBCO BusinessWorks Container Edition (BWCE)
• Postgres
• Docker
• Hystrix

Questions? Please contact me!
Kai Wähner
Technology Evangelist
kontakt@kai-waehner.de
@KaiWaehner
www.kai-waehner.de
LinkedIn

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The Five API Monetization Models - Rob Zazueta, RESTFest 2016

Effective IoT System on Openstack

Similar a TIBCO BWCE and Netflix' Hystrix Circuit Breaker for Cloud Native Middleware Microservices

Event-driven architectures are distributed, asynchronous, and scalable. The rise of real-time decision making, the on-demand economy, explosion of data, and the adoption of microservices have all driven the adoption of event driven architectures. Event-driven code is reactive by nature and significantly different from imperative programming. In this breakout session, we'll examine building an event-driven application and tackle the most common stumbling blocks of EDA, including: • How and where for maintaining state. • How to handle transactions that span multiple services. • REST or Kafka (or something else). • Asynchronous testing. We'll end by quickly (and easily) spinning up an event-driven application using Quarkus and Red Hat AMQ Streams (Apache Kafka).

Event Driven Architecture with Quarkus,Kafka and Kubernetes

Jeremy Davis

[2017년 5월 정기세미나] IBM에서 바라보는 OpenStack 이야기

OpenStack Korea Community

At Partner Summit we made a series of exciting announcements in our Cloud portfolio, including our acquisition of CliQr. Join us to learn about these new announcements and an understanding of Cisco’s Cloud Strategy. - How does CliQr fit into our existing Cloud portfolio (Metapod, APIC, Enterprise Cloud Suite, Cloud Consumption-as-a-Service)? - How does our Cloud portfolio today meet the needs of our customers? What problems are we solving? - How does our portfolio today position us for the world of Containers and Microservices? Join us for a presentation of how these announcements fit into our current environment and what they mean to your longer-term strategy.

Cisco’s Cloud Strategy, including our acquisition of CliQr

Cisco Canada

Application Centric Microservices Architecture

Ken Owens

Building cloud native microservices

Brian Pulito

Developing History at Amazon: From Monolith to Serverless Speakers: Richard Ainley, Financial Services Specialist Solutions Architect, AWS Leo Drakopoulos, Financial Services Specialist Solutions Architect, AWS In the FS industry we often observe very traditional monolithic architectures. Those architectures are hard to scale and as an application's code base grows, it often becomes complex to update, maintain and subsequently hinders the ability to deliver products to market. In this session we are going to examine the evolution of Amazon’s developing history from traditional monolithic architectures to microservices and how this evolution can dramatically accelerate and enable innovation.

From Monolith to Serverless

Amazon Web Services

TechEvent 2019: Chaos Engineering - here we go; Lothar Wieske - Trivadis

Trivadis

While service meshes may be the next "big thing" in microservices, the concept isn't new. Classical SOA attempted to implement similar technology for abstracting and managing all aspects of service-to-service communication, and this was often realized as the much-maligned Enterprise Service Bus (ESB). Several years ago similar technology emerged from the microservice innovators, including Airbnb (SmartStack for service discovery), Netflix (Prana integration sidecars), and Twitter (Finagle for extensible RPC), and these technologies have now converged into the service meshes we are currently seeing being deployed. In this talk, Daniel Bryant will share with you what service meshes are, why they're well-suited for microservice deployments, and how best to use a service mesh when you're deploying microservices. This presentation begins with a brief history of the development of service meshes, and the motivations of the unicorn organisations that developed them. From there, you'll learn about some of the currently available implementations that are targeting microservice deployments, such as Istio/Envoy, Linkerd, and NGINX Plus

microXchg 2018: "What is a Service Mesh? Do I Need One When Developing 'Cloud...

Daniel Bryant

Micro xchg 2018 - What is a Service Mesh?

Ambassador Labs

When Cisco started envisioning the future of its application development platforms, the ability to create applications that are cloud-native with elastic services, network-aware application policies, and micro-services was strategic to the company. When the decision to build and operate a Cisco cloud service delivery platform for collaboration, video, and Internet of Things (IoT) application development was made, OpenStack and micro-services became central to our application architectures and strategic to our vision as a company. This presentation will look at the journey Cisco developers took to transform to an application-centric OpenStack platform for application development in a secure, network-centric, and completely open source manner. The importance of the platform being Red Hat Enterprise Linux OpenStack Platform and using OpenShift by Red Hat and the contribution to the community will be described. The micro-services architecture and service-oriented DevOps lessons learned for enabling massive scalable and continuous delivery of software will be presented and demoed.

Application Centric Microservices from Redhat Summit 2015

Ken Owens

Stay productive while slicing up the monolith

Markus Eisele

Vancouver Microservices Meetup - Kickoff Session

Matt McLarty

About the topic: Wix transitioned from monolith to microservices around 8 years ago. Or did it? We have hundreds of microservices in production with teams working on separate independent services or groups of services with decoupled deployments and SLAs. Sounds like a microservice architecture, but there is a dark truth to it – single platform (jvm), shared libraries (framework), fat clients (binary dependencies). In industry it is called a distributed monolith. There is no easy way or incentive to get rid of it. But there is a way! Let me tell you a story on how much fun it was, what path we took and where we are now with getting to a proper polyglot microservice architecture. John About Vilius: Guild Master @ Wix with experience in different roles and companies (enterprise, start-up, you name it). No matter how much life/circumstances are pushing me to lead/management roles, I always find ways to come back and keep on hacking. Twitter: https://twitter.com/viliusl GitHub: https://github.com/viliusl

Vilius Lukošius - Decomposing distributed monolith with Node.js (WIX.com)

Agile Lietuva

Microservices are not for everyone! If you're a small shop, a monolith provides a great amount of value and reduces the complexities involved. However as your company grows, this monolith becomes more difficult to maintain. We’ll look at how microservices allow you to easily deploy and debug atomic pieces of infrastructure which allows for increased velocity in reliable, tested, and consistent deploys. We’ll look into key metrics you can use to identify the right time to begin the transition from monolith to microservices.

Architecture: When, how, and if to Adopt Microservices

Amazon Web Services

Introduction to Microservices Architecture, Docker, Kubernetes, Istio, Testing Strategies for Microservices based Apps. Security Best Practices. Kanban, DevOps, and SRE. Infrastructure Design Patterns - API Gateway - Service Discovery - Load Balancer - Circuit Breaker - Let-it-Crash Pattern Software Design Patterns - Hexagonal Architecture - Domain Driven Design - Event Sourcing and CQRS - Functional Reactive Programming

Microservices Docker Kubernetes Istio Kanban DevOps SRE

Araf Karsh Hamid

Cloud-native applications are fundamentally different that traditional applications, and are being developed using the Microservices architecture pattern. This session will explain what the Microservcies. Architecture pattern is and what problems it solves. The session will also deep dive into how Microservcies can be packaged into container technologies, like Docker, and then orchestrated across clouds using application orchestration solutions. The session will have live demos of Microservices applications being deployed and operated on the Cisco Intercloud using Docker and Nirmata. The Microservices approach is a new way of building composable, cloud-native applications. This session is designed for developers who are transforming existing applications to Microservices, or creating new Microservices style applications. The session will cover best practices, patterns including Service Registration and Discovery, and key development tools required for building distributed Microservices style applications. The session will also cover best practices for automating the operations of these applications, using container orchestration services.

DEVNET-1170 Intercloud Microservices with Docker and Nirmata

Cisco DevNet

Stay productive while slicing up the monolith

Markus Eisele

KCD Munich 2022: Hijack a Kubernetes Cluster - a Walkthrough

Nico Meisenzahl

Accelerate DevOps/Microservices and Kubernetes

Rick Hightower

CCCNA17 Introduction

ShapeBlue

Similar a TIBCO BWCE and Netflix' Hystrix Circuit Breaker for Cloud Native Middleware Microservices (20)

Event Driven Architecture with Quarkus,Kafka and Kubernetes

[2017년 5월 정기세미나] IBM에서 바라보는 OpenStack 이야기

Cisco’s Cloud Strategy, including our acquisition of CliQr

Application Centric Microservices Architecture

Building cloud native microservices

From Monolith to Serverless

TechEvent 2019: Chaos Engineering - here we go; Lothar Wieske - Trivadis

microXchg 2018: "What is a Service Mesh? Do I Need One When Developing 'Cloud...

Micro xchg 2018 - What is a Service Mesh?

Application Centric Microservices from Redhat Summit 2015

Stay productive while slicing up the monolith

Vancouver Microservices Meetup - Kickoff Session

Vilius Lukošius - Decomposing distributed monolith with Node.js (WIX.com)

Architecture: When, how, and if to Adopt Microservices

Microservices Docker Kubernetes Istio Kanban DevOps SRE

DEVNET-1170 Intercloud Microservices with Docker and Nirmata

Stay productive while slicing up the monolith

KCD Munich 2022: Hijack a Kubernetes Cluster - a Walkthrough

Accelerate DevOps/Microservices and Kubernetes

CCCNA17 Introduction

Más de Kai Wähner

Decentralized finance with crypto and NFTs is a huge topic these days. It becomes a powerful combination with the coming metaverse platforms across industries. This session explores the relationship between crypto technologies and modern enterprise architecture. I discuss how data streaming and Apache Kafka help build innovation and scalable real-time applications of a future metaverse. Let's skip the buzz (and NFT bubble) and instead review existing real-world deployments in the crypto and blockchain world powered by Kafka and its ecosystem.

Apache Kafka as Data Hub for Crypto, NFT, Metaverse (Beyond the Buzz!)

Kai Wähner

Apache Kafka is the de facto standard for data streaming to process data in motion. With its significant adoption growth across all industries, I get a very valid question every week: When NOT to use Apache Kafka? What limitations does the event streaming platform have? When does Kafka simply not provide the needed capabilities? How to qualify Kafka out as it is not the right tool for the job? This session explores the DOs and DONTs. Separate sections explain when to use Kafka, when NOT to use Kafka, and when to MAYBE use Kafka. No matter if you think about open source Apache Kafka, a cloud service like Confluent Cloud, or another technology using the Kafka protocol like Redpanda or Pulsar, check out this slide deck. A detailed article about this topic: https://www.kai-waehner.de/blog/2022/01/04/when-not-to-use-apache-kafka/

When NOT to use Apache Kafka?

Kai Wähner

Live commerce combines instant purchasing of a featured product and audience participation. This talk explores the need for real-time data streaming with Apache Kafka between applications to enable live commerce across online stores and brick & mortar stores across regions, countries, and continents in any retail business. The discussion covers several building blocks of a live commerce enterprise architecture, including transactional data processing, omnichannel, natural language processing, augmented reality, edge computing, and more.

Kafka for Live Commerce to Transform the Retail and Shopping Metaverse

Kai Wähner

If there were a buzzword of the hour, it would certainly be "data mesh"! This new architectural paradigm unlocks analytic data at scale and enables rapid access to an ever-growing number of distributed domain datasets for various usage scenarios. As such, the data mesh addresses the most common weaknesses of the traditional centralized data lake or data platform architecture. And the heart of a data mesh infrastructure must be real-time, decoupled, reliable, and scalable. This presentation explores how Apache Kafka, as an open and scalable decentralized real-time platform, can be the basis of a data mesh infrastructure and - complemented by many other data platforms like a data warehouse, data lake, and lakehouse - solve real business problems. There is no silver bullet or single technology/product/cloud service for implementing a data mesh. The key outcome of a data mesh architecture is the ability to build data products; with the right tool for the job. A good data mesh combines data streaming technology like Apache Kafka or Confluent Cloud with cloud-native data warehouse and data lake architectures from Snowflake, Databricks, Google BigQuery, et al.

The Heart of the Data Mesh Beats in Real-Time with Apache Kafka

Kai Wähner

Enterprise integration is more challenging than ever before. The IT evolution requires the integration of more and more technologies. Applications are deployed across the edge, hybrid, and multi-cloud architectures. Traditional middleware such as MQ, ETL, ESB does not scale well enough or only processes data in batch instead of real-time. This presentation explores why Apache Kafka is the new black for integration projects, how Kafka fits into the discussion around cloud-native iPaaS (Integration Platform as a Service) solutions, and why event streaming is a new software category. A concrete real-world example shows the difference between event streaming and traditional integration platforms respectively cloud-native iPaaS. Video Recording of this presentation: https://www.youtube.com/watch?v=I8yZwKg_IJc&t=2842s Blog post about this topic: https://www.kai-waehner.de/blog/2021/11/03/apache-kafka-cloud-native-ipaas-versus-mq-etl-esb-middleware/

Apache Kafka vs. Cloud-native iPaaS Integration Platform Middleware

Kai Wähner

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a presentation. The slides cover technologies such as Apache Kafka, Apache Spark, Confluent, Databricks, Snowflake, Elasticsearch, AWS Redshift, GCP with Google Bigquery, and Azure Synapse.

Data Warehouse vs. Data Lake vs. Data Streaming – Friends, Enemies, Frenemies?

Kai Wähner

Apache Kafka in conjunction with Apache Spark became the de facto standard for processing and analyzing data. Both frameworks are open, flexible, and scalable. Unfortunately, the latter makes operations a challenge for many teams. Ideally, teams can use serverless SaaS offerings to focus on business logic. However, hybrid and multi-cloud scenarios require a cloud-native platform that provides automated and elastic tooling to reduce the operations burden. This session explores different architectures to build serverless Apache Kafka and Apache Spark multi-cloud architectures across regions and continents. We start from the analytics perspective of a data lake and explore its relation to a fully integrated data streaming layer with Kafka to build a modern data Data Lakehouse. Real-world use cases show the joint value and explore the benefit of the "delta lake" integration.

Serverless Kafka and Spark in a Multi-Cloud Lakehouse Architecture

Kai Wähner

Hybrid cloud architectures are the new black for most companies. A cloud-first strategy is evident for many new enterprise architectures, but some use cases require resiliency across edge sites and multiple cloud regions. Data streaming with the Apache Kafka ecosystem is a perfect technology for building resilient and hybrid real-time applications at any scale. This talk explores different architectures and their trade-offs for transactional and analytical workloads. Real-world examples include financial services, retail, and the automotive industry. Video recording: https://qconlondon.com/london2022/presentation/resilient-real-time-data-streaming-across-the-edge-and-hybrid-cloud

Resilient Real-time Data Streaming across the Edge and Hybrid Cloud with Apac...

Kai Wähner

Agenda: 1) Defence, Modern Warfare, and Cybersecurity in 202X 2) Data in Motion with Apache Kafka as Defence Backbone 3) Situational Awareness 4) Threat Intelligence 5) Forensics and AI / Machine Learning 6) Air-Gapped and Zero Trust Environments 7) SIEM / SOAR Modernization Technologies discussed in the presentation include Apache Kafka, Kafka Streams, kqlDB, Kafka Connect, Elasticsearch, Splunk, IBM QRadar, Zeek, Netflow, PCAP, TensorFlow, AWS, Azure, GCP, Sigma, Confluent Cloud,

Data Streaming with Apache Kafka in the Defence and Cybersecurity Industry

Kai Wähner

Real-World Deployments of Data Streaming with Apache Kafka across the Healthcare Value Chain using open source and cloud-native technologies and serverless SaaS: 1) Legacy Modernization and Hybrid Cloud: Optum (UnitedHealth Group, Centene, Bayer) 2) Streaming ETL (Bayer, Babylon Health) 3) Real-time Analytics (Cerner, Celmatix, CDC/Centers for Disease Control and Prevention) 4) Machine Learning and Data Science (Recursion, Humana) 5) Open API and Omnichannel (Care.com, Invitae)

Apache Kafka in the Healthcare Industry

Kai Wähner

The Rise of Data in Motion in the Healthcare Industry - Use Cases, Architectures and Examples powered by Apache Kafka. Use Cases for Data in Motion in the Healthcare Industry: - Know Your Patient (= “Customer 360”) - Operations (Healthcare 4.0 including Drug R&D, Patient Care, etc.) - IT Perspective (Cybersecurity, Mainframe Offload, Hybrid Cloud, Streaming ETL, etc) Real-world examples include Covid-19 Electronic Lab Reporting, Cerner, Optum, Centene, Humana, Invitae, Bayer, Celmatix, Care.com.

Apache Kafka in the Healthcare Industry

Kai Wähner

Apache Kafka for Real-time Supply Chainin the Food and Retail Industry

Kai Wähner

Not all workloads allow cloud computing. Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration. This session explores architectures and design patterns for software and hardware considerations to deploy hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell and Confluent Cloud.

Kafka for Real-Time Replication between Edge and Hybrid Cloud

Kai Wähner

The manufacturing industry is moving away from just selling machinery, devices, and other hardware. Software and services increase revenue and margins. Equipment-as-a-Service (EaaS) even outsources the maintenance to the vendor. This paradigm shift is only possible with reliable and scalable real-time data processing leveraging an event streaming platform such as Apache Kafka. This talk explores how Kafka-native Condition Monitoring and Predictive Maintenance help with this innovation. More details: https://www.kai-waehner.de/blog/2021/10/25/apache-kafka-condition-monitoring-predictive-maintenance-industrial-iot-digital-twin/ Video recording: https://youtu.be/tfOuN5KeI9w

Apache Kafka for Predictive Maintenance in Industrial IoT / Industry 4.0

Kai Wähner

Today, in 2022, Apache Kafka is the central nervous system of many applications in various areas related to the automotive and manufacturing industry for processing analytical and transactional data in motion across edge, hybrid, and multi-cloud deployments. This presentation explores the automotive event streaming landscape, including connected vehicles, smart manufacturing, supply chain optimization, aftersales, mobility services, and innovative new business models. Afterwards, many real-world examples are shown from companies such as Audi, BMW, Porsche, Tesla, Uber, Grab, and FREENOW. More detail in the blog post: https://www.kai-waehner.de/blog/2022/01/12/apache-kafka-landscape-for-automotive-and-manufacturing/

Apache Kafka Landscape for Automotive and Manufacturing

Kai Wähner

Real-time data beats slow data. That’s true for almost every use case. Nevertheless, enterprise architects build new infrastructures with the Lambda architecture that includes separate batch and real-time layers. This video explores why a single real-time pipeline, called Kappa architecture, is the better fit for many enterprise architectures. Real-world examples from companies such as Disney, Shopify, Uber, and Twitter explore the benefits of Kappa but also show how batch processing fits into this discussion positively without the need for a Lambda architecture. The main focus of the discussion is on Apache Kafka (and its ecosystem) as the de facto standard for event streaming to process data in motion (the key concept of Kappa), but the video also compares various technologies and vendors such as Confluent, Cloudera, IBM Red Hat, Apache Flink, Apache Pulsar, AWS Kinesis, Amazon MSK, Azure Event Hubs, Google Pub Sub, and more. Video recording of this presentation: https://youtu.be/j7D29eyysDw Further reading: https://www.kai-waehner.de/blog/2021/09/23/real-time-kappa-architecture-mainstream-replacing-batch-lambda/ https://www.kai-waehner.de/blog/2021/04/20/comparison-open-source-apache-kafka-vs-confluent-cloudera-red-hat-amazon-msk-cloud/ https://www.kai-waehner.de/blog/2021/05/09/kafka-api-de-facto-standard-event-streaming-like-amazon-s3-object-storage/

Kappa vs Lambda Architectures and Technology Comparison

Kai Wähner

I see the following topics coming up more regularly in conversations with customers, prospects, and the broader Kafka community across the globe: Kappa Architecture: Kappa goes mainstream to replace Lambda and Batch pipelines (that does not mean that there is no batch processing anymore). Examples: Kafka-powered Kappa architectures from Uber, Disney, Shopify, and Twitter. Hyper-personalized Omnichannel: Retail and customer communication across online and offline channels becomes the new black, including context-specific upselling, recommendations, and location-based services. Examples: Omnichannel Retail and Customer 360 in Real-Time with Apache Kafka. Multi-Cloud Deployments: Business units and IT infrastructures span across regions, continents, and cloud providers. Linking clusters for bi-directional replication of data in real-time becomes crucial for many business models. Examples: Global Kafka deployments. Edge Analytics: Low latency requirements, cost efficiency, or security requirements enforce the deployment of (some) event streaming use cases at the far edge (i.e., outside a data center), for instance, for predictive maintenance and quality assurance on the shop floor level in smart factories. Examples: Edge analytics with Kafka. Real-time Cybersecurity: Situational awareness and threat intelligence need to process massive data in real-time to defend against cyberattacks successfully. The many successful ransomware attacks across the globe in 2021 were a warning for most CIOs. Examples: Cybersecurity for situational awareness and threat intelligence in real-time.

The Top 5 Apache Kafka Use Cases and Architectures in 2022

Kai Wähner

Technical thought leadership presentation to discuss how leading organizations 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 utilizing data in motion to drive competitive advantage. Agenda: - Data in Motion with Event Streaming and Apache Kafka - Streaming ETL Pipelines - IT Modernisation and Hybrid Multi-Cloud - Customer Experience and Customer 360 - IoT and Big Data Processing - Machine Learning and Analytics

Event Streaming CTO Roundtable for Cloud-native Kafka Architectures

Kai Wähner

The Rise of Data in Motion in the Public Sector powered by event streaming with Apache Kafka. Citizen Services: - Health services, e.g. hospital modernization, track & trace - Covid distance control - Public administration - reduce bureaucracy, data democratization across government departments - eGovernment - Efficient and digital citizen engagement, e.g. personal ID application process Smart City - Smart driving, parking, buildings, environment Waste management - Open exchange – e.g. mobility services (1st and 3rd party) Energy - Smart grid and utilities infrastructure (energy distribution, smart home, smart meters, smart water, etc.) - National Security Law enforcement, surveillance, police/interior security data exchange - Defense and military (border control, intelligent solider) Cybersecurity for situational awareness and threat intelligence

Apache Kafka in the Public Sector (Government, National Security, Citizen Ser...

Kai Wähner

Telco 4.0 - Payment and FinServ Integration for Data in Motion with 5G and Ap...

Kai Wähner

Más de Kai Wähner (20)

Apache Kafka as Data Hub for Crypto, NFT, Metaverse (Beyond the Buzz!)

When NOT to use Apache Kafka?

Kafka for Live Commerce to Transform the Retail and Shopping Metaverse

The Heart of the Data Mesh Beats in Real-Time with Apache Kafka

Apache Kafka vs. Cloud-native iPaaS Integration Platform Middleware

Data Warehouse vs. Data Lake vs. Data Streaming – Friends, Enemies, Frenemies?

Serverless Kafka and Spark in a Multi-Cloud Lakehouse Architecture

Resilient Real-time Data Streaming across the Edge and Hybrid Cloud with Apac...

Data Streaming with Apache Kafka in the Defence and Cybersecurity Industry

Apache Kafka in the Healthcare Industry

Apache Kafka for Real-time Supply Chainin the Food and Retail Industry

Kafka for Real-Time Replication between Edge and Hybrid Cloud

Apache Kafka for Predictive Maintenance in Industrial IoT / Industry 4.0

Apache Kafka Landscape for Automotive and Manufacturing

Kappa vs Lambda Architectures and Technology Comparison

The Top 5 Apache Kafka Use Cases and Architectures in 2022

Event Streaming CTO Roundtable for Cloud-native Kafka Architectures

Apache Kafka in the Public Sector (Government, National Security, Citizen Ser...

Telco 4.0 - Payment and FinServ Integration for Data in Motion with 5G and Ap...

Último

Handwritten Text Recognition for manuscripts and early printed texts

Maria Levchenko

Choosing the right accounts payable services provider is a strategic decision that can significantly impact your business's financial performance and operational efficiency. By considering factors such as expertise, range of services, technology infrastructure, scalability, cost, and reputation, businesses can make informed decisions and select a provider that aligns with their unique needs and objectives. Partnering with the right provider can streamline accounts payable processes, drive cost savings, and position your business for long-term success. https://katprotech.com/accounts-payable-and-purchase-order-automation/

Factors to Consider When Choosing Accounts Payable Services Providers.pptx

Katpro Technologies

[2024]Digital Global Overview Report 2024 Meltwater.pdf

hans926745

Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

Driving Behavioral Change for Information Management through Data-Driven Gree...

Enterprise Knowledge

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Explore 'The Codex of Business: Writing Software for Real-World Solutions,' a compelling SlideShare presentation that delves into digital transformation in healthcare. Discover through a detailed case study how Agile methodologies empower healthcare providers to develop, iterate, and refine digital solutions that address real-world challenges. Learn how strategic planning, user feedback, and continuous improvement drive success in deploying technologies that enhance patient care and operational efficiency. Ideal for healthcare professionals, IT specialists, and digital transformation advocates seeking actionable insights and practical examples of technology making a real difference.

The Codex of Business Writing Software for Real-World Solutions 2.pptx

Malak Abu Hammad

GenCyber Cyber Security Day Presentation

Michael W. Hawkins

The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

Artificial Intelligence: Facts and Myths

Joaquim Jorge

Real Time Object Detection Using Open CV

Khem

Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Safe Software

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

UK Journal

With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

Boost PC performance: How more available memory can improve productivity

Principled Technologies

As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments

TrustArc

Tata AIG General Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

The Raspberry Pi 5 was announced on October 2023. This new version of the popular embedded device comes with a new iteration of Broadcom’s VideoCore GPU platform, and was released with a fully open source driver stack, developed by Igalia. The presentation will discuss some of the major changes required to support this new Video Core iteration, the challenges we faced in the process and the solutions we provided in order to deliver conformant OpenGL ES and Vulkan drivers. The talk will also cover the next steps for the open source Raspberry Pi 5 graphics stack. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://eoss24.sched.com/event/1aBEx

Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...

Igalia

Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

debabhi2

Advantages of Hiring UIUX Design Service Providers for Your Business

Pixlogix Infotech

Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “The Role of Taxonomy and Ontology in Semantic Layers” at a webinar hosted by Progress Semaphore on April 16, 2024. Taxonomies at their core enable effective tagging and retrieval of content, and combined with ontologies they extend to the management and understanding of related data. There are even greater benefits of taxonomies and ontologies to enhance your enterprise information architecture when applying them to a semantic layer. A survey by DBP-Institute found that enterprises using a semantic layer see their business outcomes improve by four times, while reducing their data and analytics costs. Extending taxonomies to a semantic layer can be a game-changing solution, allowing you to connect information silos, alleviate knowledge gaps, and derive new insights. Hedden, who specializes in taxonomy design and implementation, presented how the value of taxonomies shouldn’t reside in silos but be integrated with ontologies into a semantic layer. Learn about: - The essence and purpose of taxonomies and ontologies in information and knowledge management; - Advantages of semantic layers leveraging organizational taxonomies; and - Components and approaches to creating a semantic layer, including the integration of taxonomies and ontologies

The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf

Enterprise Knowledge

Automating Google Workspace (GWS) & more with Apps Script

wesley chun

Scaling API-first – The story of a global engineering organization

Radu Cotescu

TIBCO BWCE and Netflix' Hystrix Circuit Breaker for Cloud Native Middleware Microservices

1. Kai Wähner Technology Evangelist kontakt@kai-waehner.de LinkedIn @KaiWaehner www.kai-waehner.de Cloud Native Microservices (January 2017) Circuit Breaker Design Pattern with Netflix’ Hystrix and TIBCO BusinessWorks Container Edition (BWCE)

2. © Copyright 2000-2017 TIBCO Software Inc. Distributed Microservice Architecture http://blogs.gartner.com/gary-olliffe/2015/01/30/microservices-guts-on-the-outside/ ”That complexity has moved and […] increased [to] the outer architecture.”

4. © Copyright 2000-2017 TIBCO Software Inc. Circuit Breaker Resilience Design Patterns Features • Fail fast and rapidly recover • Prevent cascading failures • Latency tolerance logic • Fault tolerance logic • Fallback Options http://martinfowler.com/bliki/CircuitBreaker.html https://github.com/Netflix/Hystrix/wiki maxFailures = 5 resetTimeout = 1min callTimeout = 10s à maxFailures++

6. Hystrix Dashboard Hystrix Dashboard - Tech Talk and Demo (10min) :https://www.youtube.com/watch?v=v3pAMHdR4BM

11. Questions? Please contact me! Kai Wähner Technology Evangelist kontakt@kai-waehner.de @KaiWaehner www.kai-waehner.de LinkedIn

TIBCO BWCE and Netflix' Hystrix Circuit Breaker for Cloud Native Middleware Microservices

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