Apache Kafka Training in Östergötland

Apache Kafka Training in Östergötland

Local, instructor-led live Apache Kafka training courses demonstrate through interactive discussion and hands-on practice how to set up and operate a Kafka message broker.

Kafka training is available as "onsite live training" or "remote live training". Onsite live Apache Kafka trainings in Östergötland can be carried out locally on customer premises or in NobleProg corporate training centers. Remote live training is carried out by way of an interactive, remote desktop.

Kafka training courses cover integration of Kafka with other Big Data systems as well as how to set up real-time data pipelines for streaming applications.

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Linköping
Learn Apache Kafka in our training center in Östergötland. Scandic Linköping City is a modern conference place. It's located in central Linkoping and also close to Linkoping Cathedral and Linkopings Garden Society. Read more

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Kafka Course Events - Östergötland

Kafka Course Outlines in Östergötland

Title
Duration
Overview
Title
Duration
Overview
14 hours
Overview
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to use Confluent (a distribution of Kafka) to build and manage a real-time data processing platform for their applications.

By the end of this training, participants will be able to:

- Install and configure Confluent Platform.
- Use Confluent's management tools and services to run Kafka more easily.
- Store and process incoming stream data.
- Optimize and manage Kafka clusters.
- Secure data streams.

Format of the Course

- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.

Course Customization Options

- This course is based on the open source version of Confluent: Confluent Open Source.
- To request a customized training for this course, please contact us to arrange.
7 hours
Overview
Apache Kafka is a distributed streaming platform. It is de facto a standard for building data pipelines and it solves a lot of different use-cases around data processing: it can be used as a message queue, distributed log, stream processor, etc.

We'll start with some theory behind data pipelines in general, then continue with fundamental concepts behind Kafka. We'll also discover important components like Kafka Streams and Kafka Connect.
21 hours
Overview
Stream Processing refers to the real-time processing of "data in motion", that is, performing computations on data as it is being received. Such data is read as continuous streams from data sources such as sensor events, website user activity, financial trades, credit card swipes, click streams, etc. Stream Processing frameworks are able to read large volumes of incoming data and provide valuable insights almost instantaneously.

In this instructor-led, live training (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices.

By the end of this training, participants will be able to:

- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming
- Understand and select the most appropriate framework for the job
- Process of data continuously, concurrently, and in a record-by-record fashion
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
- Integrating the most appropriate stream processing library with enterprise applications and microservices

Audience

- Developers
- Software architects

Format of the Course

- Part lecture, part discussion, exercises and heavy hands-on practice

Notes

- To request a customized training for this course, please contact us to arrange.
14 hours
Overview
This course is for enterprise architects, developers, system administrators and anyone who wants to understand and use a high-throughput distributed messaging system. If you have more specific requirements (e.g. only system administration side), this course can be tailored to better suit your needs.
7 hours
Overview
Kafka Streams is a client-side library for building applications and microservices whose data is passed to and from a Kafka messaging system. Traditionally, Apache Kafka has relied on Apache Spark or Apache Storm to process data between message producers and consumers. By calling the Kafka Streams API from within an application, data can be processed directly within Kafka, bypassing the need for sending the data to a separate cluster for processing.

In this instructor-led, live training, participants will learn how to integrate Kafka Streams into a set of sample Java applications that pass data to and from Apache Kafka for stream processing.

By the end of this training, participants will be able to:

- Understand Kafka Streams features and advantages over other stream processing frameworks
- Process stream data directly within a Kafka cluster
- Write a Java or Scala application or microservice that integrates with Kafka and Kafka Streams
- Write concise code that transforms input Kafka topics into output Kafka topics
- Build, package and deploy the application

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Notes

- To request a customized training for this course, please contact us to arrange
14 hours
Overview
Apache Samza is an open-source near-realtime, asynchronous computational framework for stream processing. It uses Apache Kafka for messaging, and Apache Hadoop YARN for fault tolerance, processor isolation, security, and resource management.

This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.

By the end of this training, participants will be able to:

- Use Samza to simplify the code needed to produce and consume messages.
- Decouple the handling of messages from an application.
- Use Samza to implement near-realtime asynchronous computation.
- Use stream processing to provide a higher level of abstraction over messaging systems.

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
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