Big Data Spain: Talk about KSQL – The Streaming SQL Engine for Apache Kafka

Posted in Apache Kafka, Big Data, Kafka Streams, KSQL, Open Source on November 15th, 2018 by Kai Wähner

In November 2018, I was back in Madrid to speak at Big Data Spain. A great event all about big data, analytics and machine learning. One of the largest tech companies in Spain. A perfect event to talk about KSQL – The Streaming SQL Engine for Apache Kafka.

Big Data Spain is held in Kinepolis, a big cinema. One of my favorite locations for a tech conference – for speakers and audience.

All talks at Big Data Spain are recorded. Video recording and slides below.

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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).

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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.

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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.

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Apache Kafka Streams + Machine Learning (Spark, TensorFlow, H2O.ai)

Posted in Analytics, Apache Kafka, Apache Spark, Big Data, Confluent, Hadoop, Integration, Kafka Connect, Kafka Streams, Machine Learning, Messaging, Microservices, Open Source, Stream Processing on May 23rd, 2017 by Kai Wähner

I started at Confluent in May 2017 to work as Technology Evangelist focusing on topics around the open source framework Apache Kafka. I think Machine Learning is one of the hottest buzzwords these days as it can add huge business value in any industry. Therefore, you will see various other posts from me around Apache Kafka (messaging), Kafka Connect (integration), Kafka Streams (stream processing), Confluent’s additional open source add-ons on top of Kafka (Schema Registry, Replicator, Auto Balancer, etc.). I will explain how to leverage all this for machine learning and other big data technologies in real world production scenarios.

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Why I Move (Back) to Open Source for Messaging, Integration and Stream Processing

Posted in Analytics, API Management, Big Data, Blockchain, Cloud, Cloud-Native, Docker, ESB, Hadoop, Internet of Things, Java / JEE, Machine Learning, Microservices, Middleware, SOA on May 1st, 2017 by Kai Wähner

After three great years at TIBCO Software, I move back to open source and join Confluent, a company focusing on the open source project Apache Kafka to build mission-critical, scalable infrastructures for messaging, integration and streaming analytics. Confluent is a Silicon Valley startup, still in the beginning of its journey, with a 700% growing business in 2016, and is exjustpected to grow significantly in 2017 again.

In this blog post, I want to share why I see the future for middleware and big data analytics in open source technologies, why I really like Confluent, what I will focus on in the next months, and why I am so excited about this next step in my career.

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Visual Analytics + Open Source Deep Learning Frameworks

Posted in Analytics, Big Data, Cloud, Hadoop, Machine Learning on April 24th, 2017 by Kai Wähner

Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in analytics, when to use it, and how Visual Analytics allows business analysts to leverage the analytic models built by a (citizen) data scientist.

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Blockchain, Integration, Streaming Analytics, Ethereum, Hyperledger

Posted in Analytics, Blockchain, ESB, Machine Learning, Middleware, SOA on February 24th, 2017 by Kai Wähner

In the fast few weeks, I have published a few articles, slide decks and videos around Blockchain, Middleware, Integration, Streaming Analytics, Ethereum, Hyperledger. I want to share the links here…

Blockchain – The Next Big Thing for Middleware

InfoQ article: “Blockchain – The Next Big Thing for Middleware”

Key takeaways:

  • Blockchain is not just for Bitcoin
  • A blockchain is a protocol and ledger for building an immutable historical record of transactions
  • There is no new technology behind blockchain, just established components combined in a new way
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Comparison: Data Preparation vs. Inline Data Wrangling in Machine Learning and Deep Learning Projects

Posted in Analytics, Big Data, Business Intelligence, Hadoop on February 13th, 2017 by Kai Wähner

I want to highlight a new presentation about Data Preparation in Data Science projects:

“Comparison of Programming Languages, Frameworks and Tools for Data Preprocessing and (Inline) Data Wrangling  in Machine Learning / Deep Learning Projects”

Data Preparation as Key for Success in Data Science Projects

A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 80% of the whole project.

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Streaming Analytics Comparison of Open Source Frameworks, Products, Cloud Services

Posted in Analytics, Big Data, Business Intelligence, Cloud, Hadoop on November 15th, 2016 by Kai Wähner

In November 2016, I am at Big Data Spain in Madrid for the first time. A great conference with many awesome speakers and sessions about very hot topics such as Apache Hadoop, Spark Spark, Streaming Processing / Streaming Analytics and Machine Learning. If you are interested in big data, then this conference is for you! My two talks:

  • How to Apply Machine Learning to Real Time Processing” (see slides and video recording from a similar conference talk).
  • Comparison of Streaming Analytics Options” (the reason for this blog post; an updated version of my talk from JavaOne 2015)
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