本地，有指导的现场Apache Kafka培训课程通过交互式讨论和实践练习，展示如何设置和操作Kafka消息代理。卡夫卡培训可作为“现场实地培训”或“远程实时培训”。现场实地培训可在当地客户现场进行中国或者在NobleProg公司的培训中心中国 。远程实时培训通过交互式远程桌面进行。 Kafka培训课程涵盖Kafka与其他大数据系统的整合，以及如何为流式应用程序设置实时数据管道。 NobleProg您当地的培训提供商。
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客户评论
老师能很好的解答学员的疑惑。
陈 老师 - DHL
课程: Distributed Messaging with Apache Kafka
教练给他的时间来解释这些话题，并且我们在安装必要的软件的过程中看到了很多细节，让kafka corriendp -
Juan Manuel Del Alto - Hewlett Packard Centro de Servicios Globales S de RL
课程: Distributed Messaging with Apache Kafka
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我相信信息性和正确的细节水平。
Asif Akhtar
课程: Distributed Messaging with Apache Kafka
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我真的受益于易于遵循。
Zach Henke
课程: Distributed Messaging with Apache Kafka
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练习，特别是当它们不起作用时（显然我的错，但找错是工作的一部分）。
Peter Hendriks
课程: Distributed Messaging with Apache Kafka
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我大多喜欢培训师的知识。
Christian Langer
课程: Distributed Messaging with Apache Kafka
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我真的很喜欢细节解释，准备充分的文件。
Allen Jeong
课程: Distributed Messaging with Apache Kafka
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我受益于实用建议（对于Kafka配置和管理）。
OLAmobile
课程: Distributed Messaging with Apache Kafka
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我从实际的例子中受益，培训师新的他正在谈论的内容。
Rumos
课程: Distributed Messaging with Apache Kafka
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培训师非常了解卡夫卡，并且在此事上有很多生产经验。
Matej Puntra
课程: Distributed Messaging with Apache Kafka
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培训是按照团队想要的方向进行的。培训师在处理可扩展性，性能，开发和部署标准等概念方面具有丰富的经验，并且在处理来自不同级别（如代码，设计，架构和最佳实践等）的查询方面的培训非常迅速。
Sarita Velagapudi - Welcome Real-time (ASPAC) Pte Ltd
课程: Distributed Messaging with Apache Kafka
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概念，它呈现的方式，非常沟通，非常有帮助，广泛的知识。
Sreenivasulu Narasingu - Welcome Real-time (ASPAC) Pte Ltd
课程: Distributed Messaging with Apache Kafka
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我大多喜欢涵盖的主题。
Ipreo
课程: Distributed Messaging with Apache Kafka
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能够与培训师轻松交谈。
VSC Technologies
课程: Distributed Messaging with Apache Kafka
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教练的方法，转移知识的方式。
Ośrodek Przetwarzania Informacji-Państwowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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进行方式，实践练习
darek lesiak - Ośrodek Przetwarzania Informacji-Państwowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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主题
Ośrodek Przetwarzania Informacji-Państwowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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互动性，与培训师的联系及其客观性
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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与听众保持良好的联系，对培训师有相当的了解。
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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有趣的练习例子
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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有趣的练习，在图表上展示Apache Kafka的架构和操作。
Damian Niesteruk - Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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知识是讲师无可置疑的优势。
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
课程: Distributed Messaging with Apache Kafka
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回顾所讨论的主题的关键点。
Paolo Angelo Gaton - SMS Global Technologies Inc.
课程: Building Stream Processing Applications with Kafka Streams
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Roxane Santiago - SMS Global Technologies Inc.
课程: Building Stream Processing Applications with Kafka Streams
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实验练习。从随后几天的第一天开始应用该理论。
Dell
课程: A Practical Introduction to Stream Processing
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每个主题都是前一个主题的扩展。培训师非常好，乐于助人。
Pavel Ignatov - Пейсейф България ЕООД
课程: Microservices with Spring Cloud and Kafka
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培训师具有丰富的知识和经验，他能够回答培训领域中提出的每个问题。您所要做的就是问他们。
Powszechny Zakład Ubezpieczeń Spółka Akcyjna
课程: Kafka for Administrators
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良好的理论锻炼比例，在理论学习过程中具有很好的兴趣吸引听众的能力
Powszechny Zakład Ubezpieczeń Spółka Akcyjna
课程: Kafka for Administrators
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所有。
Jean-Michel Bidon
课程: Kafka for Administrators
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Apache Kafka课程大纲
课程名称
课程时长
课程概览
课程名称
课程时长
课程概览
14小时
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小时
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小时
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小时
In this instructor-led, live training in 中国 (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小时
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小时
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小时
Spring Cloud是一个用于为云构建Java应用程序的微服务框架。这些微服务通常作为Kubernetes集群内的Docker容器运行。其他组件包括消息代理（如Kafka）以启用服务间通信，而数据库（如Redis）则用于存储和缓冲应用程序数据。
这一由讲师指导的实时培训（现场或远程）面向的是希望使用Spring Cloud、Kafka、Docker、Kubernetes、Redis将传统架构转换为高度并发、基于微服务的架构的开发人员。
在本次培训结束后，学员将能够：
- 为构建微服务建立必要的开发环境。
- 使用Spring Cloud、Kafka、Redis、Docker、Kubernetes设计和实现高度并发的微服务生态系统。
- 将单片和SOA服务转换为基于微服务的架构。
- 采用DevOps方法开发、测试、发布软件。
- 确保生产中的微服务之间的高并发性。
- 监控微服务并实施恢复策略。
- 进行性能调整。
- 了解微服务架构的未来趋势。
课程形式
- 互动讲座和讨论。
- 大量练习和实操。
- 在现场实验室环境中动手实现。
课程自定义选项
- 如需本课程的定制培训，请联系我们以作安排。
这一由讲师指导的实时培训（现场或远程）面向的是希望使用Spring Cloud、Kafka、Docker、Kubernetes、Redis将传统架构转换为高度并发、基于微服务的架构的开发人员。
在本次培训结束后，学员将能够：
- 为构建微服务建立必要的开发环境。
- 使用Spring Cloud、Kafka、Redis、Docker、Kubernetes设计和实现高度并发的微服务生态系统。
- 将单片和SOA服务转换为基于微服务的架构。
- 采用DevOps方法开发、测试、发布软件。
- 确保生产中的微服务之间的高并发性。
- 监控微服务并实施恢复策略。
- 进行性能调整。
- 了解微服务架构的未来趋势。
课程形式
- 互动讲座和讨论。
- 大量练习和实操。
- 在现场实验室环境中动手实现。
课程自定义选项
- 如需本课程的定制培训，请联系我们以作安排。
7小时
This instructor-led, live training in 中国 (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小时
This instructor-led, live training in 中国 (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小时
This instructor-led, live training in 中国 (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小时
This instructor-led, live training in 中国 (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小时
This instructor-led, live training in 中国 (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小时
This instructor-led, live training in 中国 (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小时
This instructor-led, live training in 中国 (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:
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