
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. The Philippines onsite live Apache Kafka trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
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
Recalling/reviewing keypoints of the topics discussed.
Paolo Angelo Gaton - SMS Global Technologies Inc.
Course: Building Stream Processing Applications with Kafka Streams
Wiedza i elastycznść prowadzącego - kafka jako core szkolenia ubrane w ciekawe offtopy i przydatne informacje.
Course: Distributed Messaging with Apache Kafka
Trainers openness to questions.
Course: Distributed Messaging with Apache Kafka
Dobrze przygotowane ćwiczenia i maszyna wirtualna.
Course: Distributed Messaging with Apache Kafka
DADesktop feature, exercises difficulty, quality and quantity of examples
Course: Distributed Messaging with Apache Kafka
Zadanka były ok/
Course: Distributed Messaging with Apache Kafka
Good prepared testing envoirment
Maciej Grabski
Course: Distributed Messaging with Apache Kafka
Sufficient hands on, trainer is knowledgable
Chris Tan
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 lab exercises. Applying the theory from the first day in subsequent days.
Dell
Course: A Practical Introduction to Stream Processing
I liked his pace for training, it was optimum.
Edwards Mukasa - AFRINIC Ltd.
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
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
The trainer was very knowledgeable about the topic.
Zhivko Stanishev - 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 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 training was well organized, the trainer was well prepared and was willing to help and answer all the questions.
ATOS PGS sp. z o.o.
Course: Kafka for Administrators
Nice presentation skill
Md Maruf Hossain - ATOS PGS sp. z o.o.
Course: Kafka for Administrators
Jorge was amazing- he is super knowledgeable and has a lot of Information to share.
Nadia Naidoo, Jembi Health Systems NPC
Course: SMACK Stack for Data Science
very interactive...
Richard Langford - Nadia Naidoo, Jembi Health Systems NPC
Course: SMACK Stack for Data Science
Wiedza i elastycznść prowadzącego - kafka jako core szkolenia ubrane w ciekawe offtopy i przydatne informacje.
Course: Distributed Messaging with Apache Kafka
Trainers openness to questions.
Course: Distributed Messaging with Apache Kafka
Dobrze przygotowane ćwiczenia i maszyna wirtualna.
Course: Distributed Messaging with Apache Kafka
DADesktop feature, exercises difficulty, quality and quantity of examples
Course: Distributed Messaging with Apache Kafka
Zadanka były ok/
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 in the Philippines
- Develop Kafka producers and consumers to send and read data from Kafka.
- Integrate Kafka with external systems using Kafka Connect.
- Write streaming applications with Kafka Streams & ksqlDB.
- Integrate a Kafka client application with Confluent Cloud for cloud-based Kafka deployments.
- Gain practical experience through hands-on exercises and real-world use cases.
- 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.
- Developers
- Part lecture, part discussion, exercises and heavy hands-on practice
- 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
- Developers
- Part lecture, part discussion, exercises and heavy hands-on practice
- To request a customized training for this course, please contact us to arrange
- 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.
- 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.
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
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