Online or onsite, 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 "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Apache Kafka training can be carried out locally on customer premises in the US or in NobleProg corporate training centers in the US.
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.
NobleProg -- Your Local Training Provider
Testimonials
Informative and had correct level of detail I believe.
Asif Akhtar
Course: Distributed Messaging with Apache Kafka
I really was benefit from the easy to follow.
Zach Henke
Course: Distributed Messaging with Apache Kafka
The exercises, and especially when they didn't work (obviously my fault but fault finding is part of the job).
Peter Hendriks
Course: Distributed Messaging with Apache Kafka
I mostly liked the knowledge of the Trainer.
Christian Langer
Course: Distributed Messaging with Apache Kafka
I genuinely liked the detail explanations, well prepared document.
Allen Jeong
Course: Distributed Messaging with Apache Kafka
I was benefit from the practical advice (for Kafka configuration and management).
OLAmobile
Course: Distributed Messaging with Apache Kafka
I was benefit from the practical examples, trainer new what he is talking about.
Rumos
Course: Distributed Messaging with Apache Kafka
The trainer really knows Kafka very well, and has a lot of production experience in the matter.
Matej Puntra
Course: Distributed Messaging with Apache Kafka
The training was steered in the direction what the team wanted. The trainer is too good with vast experience in handling concepts like capability, performance, development and deployment standards and very swift in the training in addressing queries from different levels like regarding code, design, architecture and best practices etc.
Sarita Velagapudi - Welcome Real-time (ASPAC) Pte Ltd
Course: Distributed Messaging with Apache Kafka
Concepts, the way it presented, very communicative, very helpful, wide knowledge.
Sreenivasulu Narasingu - Welcome Real-time (ASPAC) Pte Ltd
Course: Distributed Messaging with Apache Kafka
I mostly enjoyed the amount of topics covered.
Ipreo
Course: Distributed Messaging with Apache Kafka
Be able to talk easily with the trainer.
VSC Technologies
Course: Distributed Messaging with Apache Kafka
Recalling/reviewing keypoints of the topics discussed.
Paolo Angelo Gaton - SMS Global Technologies Inc.
Course: Building Stream Processing Applications with Kafka Streams
-
Roxane Santiago - SMS Global Technologies Inc.
Course: Building Stream Processing Applications with Kafka Streams
The lab exercises. Applying the theory from the first day in subsequent days.
Dell
Course: A Practical Introduction to Stream Processing
The trainer was passionate and well-known what he said I appreciate his help and answers all our questions and suggested cases.
Course: A Practical Introduction to Stream Processing
The course was excellent. Our trainer Andreas was very prepared and answered all the questions that we asked. Also he helped us when we have troubles and explained in details when needed. The best course that i have ever been part of.
Bozhidar Marinov - Пейсейф България ЕООД
Course: Microservices with Spring Cloud and Kafka
The lecturer regularly checked up on us and showed us how we can deal with some commonly seen issues when working with these tools.
Пейсейф България ЕООД
Course: Microservices with Spring Cloud and Kafka
The trainer was very knowledgeable about the topic.
Zhivko Stanishev - Пейсейф България ЕООД
Course: Microservices with Spring Cloud and Kafka
That every topic was an extension of the previous. The trainer was very nice and helpful.
Pavel Ignatov - Пейсейф България ЕООД
Course: Microservices with Spring Cloud and Kafka
It was a great overview of the landscape of the technologies involved, allowing me to find the place in it of all pieces I have tried and many other I have previously missed on microservices. Andreas put them in the context of the real use and showed their role and why they are used that way. The course is a solid basis for elaboration and studying the details in that context and I find it very valuable. The organization of the course is with prepared in advance projects to download, change in the exercises, make them run and build the next exercises upon them. This helped me to participate, understand and connect the matter presented. The selected contents of the course was well thought and presented in a conscious and understandable way.
Пейсейф България ЕООД
Course: Microservices with Spring Cloud and Kafka
I liked his pace for training, it was optimum.
Edwards Mukasa - AFRINIC Ltd.
Course: Microservices with Spring Cloud and Kafka
the preparation of virtual environments for participants to use and perform hands on learning.
marcus lim
Course: Distributed Messaging with Apache Kafka
Summary for the day, using white board to explain things step by step and the personal use cases that we are tasked to do.
Chee Meng Lee - CSIT
Course: Distributed Messaging with Apache Kafka
Explanations, demonstrations and exercises
CSIT
Course: Distributed Messaging with Apache Kafka
The documents
Jing Li - 思科系统(中国)研发有限公司杭州分公司
Course: Distributed Messaging with Apache Kafka
teamwork
思科系统(中国)研发有限公司杭州分公司
Course: Distributed Messaging with Apache Kafka
Some practices
思科系统(中国)研发有限公司杭州分公司
Course: Distributed Messaging with Apache Kafka
The trainer was passionate and well-known what he said I appreciate his help and answers all our questions and suggested cases.
Course: A Practical Introduction to Stream Processing
Apache Kafka Course Outlines
Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
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.
14 hours
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
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
7 hours
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
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
21 hours
In this instructor-led, live training in the US (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.
- Integrate the most appropriate stream processing library with enterprise 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.
- Integrate the most appropriate stream processing library with enterprise applications and microservices.
14 hours
This instructor-led, live training (online or onsite) 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.
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
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.
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
This instructor-led, live training in the US (online or onsite) is aimed at developers who wish to transform traditional architecture into a highly concurrent microservices-based architecture using Spring Cloud, Kafka, Docker, Kubernetes and Redis.
By the end of this training, participants will be able to:
- Set up the necessary development environment for building microservices.
- Design and implement a highly concurrent microservices ecosystem using Spring Cloud, Kafka, Redis, Docker and Kubernetes.
- Transform monolithic and SOA services to microservice based architecture.
- Adopt a DevOps approach to developing, testing and releasing software.
- Ensure high concurrency among microservices in production.
- Monitor microservices and implement recovery strategies.
- Carry out performance tuning.
- Learn about future trends in microservices architecture.
By the end of this training, participants will be able to:
- Set up the necessary development environment for building microservices.
- Design and implement a highly concurrent microservices ecosystem using Spring Cloud, Kafka, Redis, Docker and Kubernetes.
- Transform monolithic and SOA services to microservice based architecture.
- Adopt a DevOps approach to developing, testing and releasing software.
- Ensure high concurrency among microservices in production.
- Monitor microservices and implement recovery strategies.
- Carry out performance tuning.
- Learn about future trends in microservices architecture.
7 hours
This instructor-led, live training in the US (online or onsite) is aimed at developers who wish to integrate Apache Kafka with existing databases and applications for processing, analysis, etc.
By the end of this training, participants will be able to:
- Use Kafka Connect to ingest large amounts of data from a database into Kafka topics.
- Ingest log data generated by an application servers into Kafka topics.
- Make any collected data available for stream processing.
- Export data from Kafka topics into secondary systems for storage and analysis.
By the end of this training, participants will be able to:
- Use Kafka Connect to ingest large amounts of data from a database into Kafka topics.
- Ingest log data generated by an application servers into Kafka topics.
- Make any collected data available for stream processing.
- Export data from Kafka topics into secondary systems for storage and analysis.
7 hours
This instructor-led, live training in the US (online or onsite) is aimed at developers who wish to implement Apache Kafka stream processing without writing code.
By the end of this training, participants will be able to:
- Install and configure Confluent KSQL.
- Set up a stream processing pipeline using only SQL commands (no Java or Python coding).
- Carry out data filtering, transformations, aggregations, joins, windowing, and sessionization entirely in SQL.
- Design and deploy interactive, continuous queries for streaming ETL and real-time analytics.
By the end of this training, participants will be able to:
- Install and configure Confluent KSQL.
- Set up a stream processing pipeline using only SQL commands (no Java or Python coding).
- Carry out data filtering, transformations, aggregations, joins, windowing, and sessionization entirely in SQL.
- Design and deploy interactive, continuous queries for streaming ETL and real-time analytics.
21 hours
This instructor-led, live training in the US (online or onsite) is aimed at sysadmins who wish to set up, deploy, manage and optimize an enterprise-grade Kafka cluster.
By the end of this training, participants will be able to:
- Set up and administer a Kafka Cluster.
- Evaluate the benefits and disadvantages of deploying Kafka on-premise vs in the cloud.
- Deploy and monitor Kafka in using various on-premise and cloud environment tools.
By the end of this training, participants will be able to:
- Set up and administer a Kafka Cluster.
- Evaluate the benefits and disadvantages of deploying Kafka on-premise vs in the cloud.
- Deploy and monitor Kafka in using various on-premise and cloud environment tools.
7 hours
This instructor-led, live training in the US (online or onsite) is aimed at software testers who wish to implement network security measures into an Apache Kafka application.
By the end of this training, participants will be able to:
- Deploy Apache Kafka onto a cloud based server.
- Implement SSL encryption to prevent attacks.
- Add ACL authentication to track and control user access.
- Ensure credible clients have access to Kafka clusters with SSL and SASL authentication.
By the end of this training, participants will be able to:
- Deploy Apache Kafka onto a cloud based server.
- Implement SSL encryption to prevent attacks.
- Add ACL authentication to track and control user access.
- Ensure credible clients have access to Kafka clusters with SSL and SASL authentication.
14 hours
This instructor-led, live training in the US (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture for processing big data.
- Develop a cluster infrastructure with Apache Mesos and Docker.
- Analyze data with Spark and Scala.
- Manage unstructured data with Apache Cassandra.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture for processing big data.
- Develop a cluster infrastructure with Apache Mesos and Docker.
- Analyze data with Spark and Scala.
- Manage unstructured data with Apache Cassandra.
7 hours
This instructor-led, live training in the US (online or onsite) is aimed at data engineers, data scientists, and programmers who wish to use Spark Streaming features in processing and analyzing real-time data.
By the end of this training, participants will be able to use Spark Streaming to process live data streams for use in databases, filesystems, and live dashboards.
By the end of this training, participants will be able to use Spark Streaming to process live data streams for use in databases, filesystems, and live dashboards.
7 hours
This instructor-led, live training in the US (online or onsite) is aimed at data engineers, data scientists, and programmers who wish to use Apache Kafka features in data streaming with Python.
By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.
By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.
Last Updated:
Upcoming Apache Kafka Courses
01/04/2022 - 09:30
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01/12/2022 - 09:30
14 hours
01/13/2022 - 09:30
14 hours
02/01/2022 - 09:30
21 hours
03/09/2022 - 09:30
14 hours
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