Publications

• Confluent Blog – Using Apache Kafka to Drive Cutting-Edge Machine Learning
  
• Codemotion Magazine – Interview about Apache Kafka, Confluent, KSQL and Machine Learning
  
• Informatik Aktuell (German) – Apache Kafka vs. ETL and ESB Tools
  
• Confluent Blog – Apache Kafka vs. Enterprise Service Bus (ESB) – Friends, Enemies or Frenemies?
• DZone Javalobby – Model Serving: Stream Processing vs. RPC with Java, gRPC, Kafka Streams and TensorFlow
  
• Informatik Aktuell (German) – Apache Kafka und die DSGVO (= GDPR): Wie vergisst ein Logfile?
  
• Big Data Insider (German) – How Apache Kafka helps in Machine Learning Projects
  
• Confluent Blog – How to Write a User Defined Function (UDF) for KSQL
  
• DZone Javalobby – 5 Machine Learning Trends for 2018 Combined with Apache Kafka Ecosystem
• Confluent Blog – How to Build a User Defined Function (UDF) for KSQL
• Confluent Blog – Apache Mesos, Apache Kafka and Kafka Streams for Highly Scalable Microservices

• Confluent Blog – How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka
  
• Voxxed (Youtube Interview done at Devoxx Casablanca) – The Future of Big Data and Internet of Things
  
• Kai’s Blog – Why I Move (Back) to Open Source for Messaging, Integration and Stream Processing
  
• Informatik Aktuell – GERMAN – Blockchain 3.0 – Smart Contracts and Middleware to Build Revolutionary Applications
  
• JavaSPEKTRUM – GERMAN – The Container Wars Just Begun
• DZone – Agile Cloud-to-Cloud Integration with iPaaS, API Management and Blockchain (Hyperledger Fabric)
  
• Data Science Central – Open Source Deep Learning Frameworks and Visual Analytics
  
• Voxxed – IoT Trends – Open Source Project Engines for Edge Processing
  
• InfoQ – Data Preparation Alternatives for Machine Learning / Deep Learning Projects
• DZone Integration Guide – The Cloud: Native Development and Deployment – Cloud-Native Middleware Microservices
  
• Blockchainers – Blockchain + Streaming Analytics = Smart Distributed Applications
  
• Voxxed – Cloud-native Middleware Microservices with Netflix’ Hystrix Circuit Breaker and Eureka / Consul for Service Discovery

• InfoQ – Blockchain – The Next Big Thing for Middleware
• InfoQ – Container Wars – The Future of Docker, rkt, PaaS, Mesos, CaaS, etc.
  
• DZone Integration Guide – A Survey of Modern Integration Architectures
  
• ObjektSPEKTRUM (2016/06) – GERMAN – The Need for a Hybrid Integration Architecture
• RTInsights – Avoiding the Anti-Pattern in Analytics: Three Keys for Machine Learning Success
• RTInsights – Using Visual Analytics to Make Better Data-driven Decisions – The Death Pill Example
  
• Voxxed – The Need for a Hybrid Integration Architecture
  
• Technology Transformation Network – How to get from Microservices and Docker to Cloud-Native Middleware (Video Interview)
  
• Voxxed – Microservices, Containers and a Cloud-Native Architecture in the Middleware World
• RTInsights – How to Apply Machine Learning to Real Time Event Processing
• ObjektSPEKTRUM (2016/02) – GERMAN – Real World Use Cases for Stream Processing in a Big Data / Hadoop World
  
• ObjektSPEKTRUM (2016/01) – GERMAN – Frameworks and Products for Stream Processing and Streaming Analytics
• TIBCO Blog – How TIBCO Leverages Big Data Analytics with Apache Hadoop and Apache Spark

• TIBCO Blog – Enterprise Integration Patterns Revisited for the Era of Big Data, IoT, Cloud and Microservices
  
• TIBCO Blog – Differences between a Data Warehouse and a Live Datamart
  
• DZone – A Comparison of Streaming Analytics Frameworks and Products
  
• TIBCO Blog – BusinessWorks 6 as Leading Integration Platform
  
• TIBCO Blog – Docker Containers in the Middleware World
  
• TIBCO Blog – Do Microservices Equal the Death of the Enterprise Service Bus?
  
• TIBCO Blog – Fast Data Analytics and an Intelligent BPM Suite for Improved Customer Experience
  
• TIBCO Blog – ActiveMatrix BusinessWorks 6 + Apache Hadoop = Big Data Integration
  
• TIBCO Blog – Creating Business Value by Example: Open API and API Management at Paypal
• heise Big Data Special – In-Memory Data Grids: Concepts and Real World Use Cases
• TIBCO Blog – StreamBase + Hadoop + Impala = Fast Data Streaming Analytics
  
• TIBCO Blog – A complete guide to Microservices and DevOps
  
• Voxxed – Enterprise Integration Patterns Revisited for the Era of Big Data and Internet of Things
  
• Voxxed – A Good Microservices Architecture = Death of the Enterprise Service Bus (ESB)?

• ObjektSPEKTRUM – Open API and API Management as Game Changer for New Business Models
• Voxxed – API Management as Game Changer for Cloud, Big Data and IoT: Product Comparison and Evaluation
• InfoQ – Stream Processing as Game Changer in a Big Data / Hadoop World
• JAXenter.com – A new Front for SOA – Open API and API Management
• JavaSPEKTRUM – Apache Hadoop and its Ecosystem – How to choose the right frameworks and products?
• ObjektSPEKTRUM  – How to create an intelligent Business Process thanks to Big Data
• Software Developer’s JOURNAL – Big Data and Apache Hadoop – A perfect addon for BPM?

2013

• ObjektSPEKTRUM – How to choose the right Enterprise Service Bus
• NoSQL Roadshow Interview 9/2013 – Past, Present and Future of NoSQL
• InfoQ 7/2013  – How to choose the Right Big Data / Hadoop Platform
• JavaSPEKTRUM 3/2013 – Apache Camel Series (Part 6): Combination with the Actor Framework “Akka”
• InfoQ 4/2013 – Choosing the right Enterprise Service Bus for your Integration Needs
• JavaSPEKTRUM 2/2013 – Apache Camel Series (Part 5): Cloud Integration

• ObjektSPEKTRUM – How to choose the right Enterprise Service Bus
• NoSQL Roadshow Interview 9/2013 – Past, Present and Future of NoSQL
• InfoQ 7/2013  – How to choose the Right Big Data / Hadoop Platform
• JavaSPEKTRUM 3/2013 – Apache Camel Series (Part 6): Combination with the Actor Framework “Akka”
• InfoQ 4/2013 – Choosing the right Enterprise Service Bus for your Integration Needs
• JavaSPEKTRUM 2/2013 – Apache Camel Series (Part 5): Cloud Integration

• JavaSPEKTRUM 01/2013 – Apache Camel Series (Part 4): Leveraging Groovy and Scala
• JavaSPEKTRUM 06/2012 – Apache Camel Series (Part 3): Deployment and Tool Support
• JavaSPEKTRUM 05/2012 – Apache Camel Series (Part 2): Advanced Topics
• JavaSPEKTRUM 04/2012 – Apache Camel Series (Part 1): Introduction
• heise developer – Report from JavaOne 2012
• heise developer – Report from Cloud Ops Summit 2012
• heise developer – How to do Business Process Management correctly?
• The H – The Showdown: Free integration framework on the Java platform
• heise developer – Lightweight Integration Frameworks Apache Camel, Spring Integration or Mule – When to use them instead of a heavyweight ESB
• Service Technology Magazine – Lessons Learned: Best Practices for a Successful Introduction of Business Process Management (BPM)
• No Fluff Just Stuff – Spoilt for Choice: Which Integration Framework to use?
• Sigs Datacom – One Week in the Life of an IT Consultant
  
• JavaMagazin 04/2012  – Apache Camel goes Enterprise
• heise developer 02/2012 – Lessons learned: Using modern JVM languages besides Java (Groovy, Scala, Clojure, JRuby, etc.)

• Java Spektrum 09/2011 – Einsatz und Grenzen von Java Server Faces 2.0 – Teil 3: Grenzen von JSF
• heise Developer 08/2011 – Potentiale und Grenzen von Spring Roo
• JavaMagazin 07/2011 – Lessons Learned: GWT 2.0 in der Praxis
• Java Spektrum 07/2011 – Einsatz und Grenzen von Java Server Faces 2.0 – Teil 2: Erweiterungen von JSF
• iX 06/2011 – MyBatis als Alternative zu SQL (JDBC) oder ORM (JPA, Hibernate)
• Java Spektrum 05/2011 – Einsatz und Grenzen von Java Server Faces 2.0 – Teil 1: Grundlagen von JSF
• JAVAaktuell 05/2011 – Buchreview “Camel in Action”
• heise Developer 04/2011 – CONFESS_2011: Software für Enterprise-Anwendungen im Mittelpunkt
• heise Developer 04/2011 – Oracle: Kritik an Suns Java-Release-Zyklen
• heise Developer 03/2011 – Potenzial von JVM und Java EE im Fokus des TheServerSide Java Symposium 2011 (Bericht der IT-Konferenz aus Las Vegas)
• JAVAaktuell 02/2011 – Die Java-Zertifizierung “Sun Certified Java Programmer” (SCJP, zukünftig OCJP) – Ein Erfahrungsbericht
• JavaMagazin 02/2011 – Web-Frameworks im Java-Umfeld – Einsatzmöglichkeiten mit Beispielen aus der Praxis
• JavaMagazin 01/2011 – Kategorisierung von Web-Frameworks im Java-Umfeld