Kafka Operator for Kubernetes – Confluent Operator to establish a Cloud-Native Apache Kafka Platform

Posted in Apache Kafka, Apache Mesos, Cloud, Cloud-Native, Confluent, Docker, Kafka Connect, Kafka Streams, KSQL, Kubernetes, Microservices on July 29th, 2019 by Kai Wähner

Confluent Operator is now GA for production deployments (Download Confluent Operator for Kafka here). This is a Kafka Operator for Kubernetes which provides automated provisioning and operations of an Apache Kafka cluster and its whole ecosystem (Kafka Connect, Schema Registry, KSQL, etc.) on any Kubernetes infrastructure.

Confluent Operator Kafka Operator for Kubernetes Download

I want to share a slide deck which explains:

  • Why Kubernetes is getting more and more traction to build a cloud-native infrastructure
  • Why this is relevant for Apache Kafka and Confluent Platform
  • The challenges running Kafka on Kubernetes
  • How Confluent Operator solves these problems providing a powerful Kafka Operator for Kubernetes
Tags: , , , , , , , , , , , , , , ,

Apache Kafka vs. Middleware (MQ, ETL, ESB) – Slides + Video

Posted in Apache Kafka, Big Data, Confluent, EAI, ESB, In Memory, Integration, Kafka Connect, Kafka Streams, KSQL, Messaging, Microservices, Middleware, Open Source, SOA, Stream Processing on March 7th, 2019 by Kai Wähner

Learn the differences between an event-driven streaming platform like Apache Kafka and middleware like Message Queues (MQ), Extract-Transform-Load (ETL) and Enterprise Service Bus (ESB). Including best practices and anti-patterns, but also how these concepts and tools complement each other in an enterprise architecture.

This blog post shares my slide deck and video recording. I discuss the differences between Apache Kafka as Event Streaming Platform and integration middleware. Learn if they are friends, enemies or frenemies.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Model Serving: Stream Processing vs. RPC / REST with Java, gRPC, Apache Kafka, TensorFlow

Posted in Analytics, Apache Kafka, Big Data, Confluent, Deep Learning, Java / JEE, Kafka Streams, KSQL, Machine Learning, Microservices, Open Source, Stream Processing on July 9th, 2018 by Kai Wähner

Machine Learning / Deep Learning models can be used in different ways to do predictions. My preferred way is to deploy an analytic model directly into a stream processing application (like Kafka Streams or KSQL). You could e.g. use the TensorFlow for Java API. This allows best latency and independence of external services. Several examples can be found in my Github project: Model Inference within Kafka Streams Microservices using TensorFlow, H2O.ai, Deeplearning4j (DL4J).

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Visualisation from my Apache Kafka + Mesos Session at OOP 2018

Posted in Apache Kafka, Apache Mesos, Big Data, Kafka Connect, Kafka Streams, KSQL, Kubernetes, Microservices, Open Source on February 18th, 2018 by Kai Wähner

I did some talks about “Apache Kafka + Apache Mesos = Highly Scalable Microservices” in the last months… See my blog post with notes and slides from MesosCon Europe.

I did an updated version at OOP 2018 conference in Munich. The conference organizers invited some great people who do live drawings during some of the talks. The result of the live whiteboard drawing of my session is really awesome. Take a look:

Whiteboard Drawing Kafka Streams Mesos Microservices

Thanks to the guys from Remarker. Great visualisation! Love it…

Tags: , , , , , , , , , , , , , ,

Apache Kafka + Kafka Streams + Mesos = Highly Scalable Microservices

Posted in Apache Kafka, Apache Mesos, Big Data, Confluent, Docker, Java / JEE, Kafka Streams, KSQL, Microservices, Middleware, Open Source, Stream Processing on January 12th, 2018 by Kai Wähner

My latest article about Apache Kafka, Kafka Streams and Apache Mesos was published on Confluent’s blog:

Apache Mesos, Apache Kafka and Kafka Streams for Highly Scalable Microservices

This blog post discusses how to build a highly scalable, mission-critical microservice infrastructure with Apache Kafka, Kafka Streams, and Apache Mesos respectively in their vendor-supported platforms from Confluent and Mesosphere.

Apache Mesos, Apache Kafka and Kafka Streams for Highly Scalable Microservices

Have fun reading it and let me know if you have any feedback…

Tags: , , , , , , , , , , , , ,

Apache Kafka + Kafka Streams + Mesos / DCOS = Scalable Microservices

Posted in Apache Kafka, Apache Mesos, Big Data, Confluent, Docker, Hadoop, Java / JEE, Kafka Connect, Kafka Streams, KSQL, Kubernetes, Microservices, Open Source on October 27th, 2017 by Kai Wähner

I had a talk at MesosCon 2017 Europe in Prague about building highly scalable, mission-critical microservices with Apache Kafka, Kafka Streams and Apache Mesos / DCOS. I would like to share the slides and a video recording of the live demo.

Abstract

Microservices establish many benefits like agile, flexible development and deployment of business logic. However, a Microservice architecture also creates many new challenges. This includes increased communication between distributed instances, the need for orchestration, new fail-over requirements, and resiliency design patterns.

Tags: , , , , , , , , , , , , , , , , , , , , ,

Deep Learning in Real Time with TensorFlow, H2O.ai and Kafka Streams (Slides from JavaOne 2017)

Posted in Analytics, Apache Kafka, Big Data, Business Intelligence, Confluent, Deep Learning, Docker, Java / JEE, Kafka Streams, Machine Learning, Microservices, Open Source, Stream Processing on October 4th, 2017 by Kai Wähner

Early October… Like every year in October, it is time for JavaOne and Oracle Open World in San Francisco… I am glad to be back at this huge event again. My talk at JavaOne 2017 was all about deployment of analytic models to scalable production systems leveraging Apache Kafka and Kafka Streams. Let’s first look at the abstract. After that I attach the slides and refer to further material around this topic.

Tags: , , , , , , , , , , , , , , , , , , , , ,

Cloud Native Middleware Microservices – 10 Lessons Learned (O’Reilly Software Architecture 2017, New York)

Posted in API Management, Cloud, Cloud-Native, Docker, EAI, ESB, Microservices, Middleware, SOA on April 5th, 2017 by Kai Wähner

I want to share my slide deck and video recordings from the talk “10 Lessons Learned from Building Cloud Native Middleware Microservices” at O’Reilly Software Architecture April 2017 in New York, USA in April 2017.

Abstract
Microservices are the next step after SOA: Services implement a limited set of functions; services are developed, deployed, and scaled independently; continuous delivery automates deployments. This way you get shorter time to results and increased flexibility. Containers improve things even more, offering a very lightweight and flexible deployment option.

Tags: , , , , , , , , , , , , , , , , , , ,

Case Study: From a Monolith to Cloud, Containers, Microservices

Posted in API Management, Cloud, Cloud-Native, Docker, EAI, ESB, Java / JEE, Microservices, Middleware, SOA on February 24th, 2017 by Kai Wähner

The following shows a case study about successfully moving from a very complex monolith system to a cloud-native architecture. The architecture leverages containers and Microservices. This solve issues such as high efforts for extending the system, and a very slow deployment process. The old system included a few huge Java applications and a complex integration middleware deployment.

The new architecture allows flexible development, deployment and operations of business and integration services. Besides, it is vendor-agnostic so that you can leverage on-premise hardware, different public cloud infrastructures, and cloud-native PaaS platforms.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , ,

Comparison of Open Source IoT Integration Frameworks

Posted in API Management, Cloud, Cloud-Native, Microservices, SOA on November 3rd, 2016 by Kai Wähner

In November 2016, I attended Devoxx conference in Casablanca. Around 1500 developers participated. A great event with many awesome speakers and sessions. Hot topics this year besides Java: Open Source Frameworks, Microservices (of course!), Internet of Things (including IoT Integration), Blockchain, Serverless Architectures.

I had three talks:

  • How to Apply Machine Learning to Real Time Processing
  • Comparison of Open Source IoT Integration Frameworks
  • Tools in Action – Live Demo of Open Source Project Flogo

In addition, I was interviewed by the Voxxed team about Big Data, Machine Learning and Internet of Things. The video will be posted on Voxxed website in the next weeks.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,