Навучальныя курсы Apache Kafka

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.

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

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 in Беларусь (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.

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.

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.

This instructor-led, live training in Беларусь (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.

This instructor-led, live training in Беларусь (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.

This instructor-led, live training in Беларусь (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.

This instructor-led, live training in Беларусь (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.

This instructor-led, live training in Беларусь (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.

SMACK з'яўляецца калекцыяй праграмы платформы дадзеных, а саме Apache Spark, Apache Mesos, Apache Akka, Apache Cassandra, і Apache Kafka. Зараз на сцены наносіцца абаронная плёнка, якая захавае іх на многія гады. У якасці прыкладу такіх сетак можна прывесці facebook і vkontakte, дзе любая фізічная асоба можа падаць рэкламную аб'яву. У канцы гэтага трэніру ўдзельнікі зможаць:

Імплементацыя архітэктуры дадзеных для працэдуры вялікіх дадзеных. Здаровая касметыка вы можаце зрабіць самі Аналіз дадзеных з дапамогай Spark і Scala. Адміністрацыя неструктурных дадзеных з дапамогай Apache Cassandra.

Формат курса

Інтэрактыўныя лекцыі і дискусіі. Многія практыкаванні і практыкаванні. Вынікі ў Live-Lab Environment.

Вынікі пошуку - Customization options

Калі вы хочаце падзяліцца сваёй думкай з майстрам, рабіце гэта максімальна ветліва.

Apache Kafka з'яўляецца платформай для працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры працэдуры. Apache Kafka можа быць інтэгравана з даступнымі мовамі праграмавання, такія як Python. Гэта інструктар-праведзены, жывы трэнінг (онлайн або на сайце) звязаны з інжынерамі дадзеных, дадзенымі навукоўцамі і праграмамі, якія хацелі выкарыстоўваць Apache Kafka функцыі ў дадзеных перадачы з Python. У канцы гэтага трэніравання, удзельнікі будуць ў змозе выкарыстоўваць Apache Kafka для прагляду і кіравання умовах у працягваных дадзеных потоках з дапамогай Python праграмавання. Формат курса

Інтэрактыўныя лекцыі і дискусіі. Многія практыкаванні і практыкаванні. Вынікі ў Live-Lab Environment.

Вынікі пошуку - Customization options

Калі вы хочаце падзяліцца сваёй думкай з майстрам, рабіце гэта максімальна ветліва.

Сярод версій гульняў онлайн call of duty можна знайсці мноства займальных і дасціпных сюжэтаў, а апошняй навінкай, выпушчанай у канцы восені гэтага года, стала гульня Call of duty. Spark Streaming Забяспечвае непаўторную працэдуру дадзеных. Гэта інструктар-праведзены, жывы трэнінг (онлайн або на сайце) звязаны з інжынерамі дадзеных, дадзенымі навукоўцамі і праграмамі, якія хацелі выкарыстоўваць Spark Streaming функцыі ў працэсе і аналізе дадзеных у рэальным часе. У канцы гэтага трэніравання, удзельнікі будуць ў змозе выкарыстоўваць Spark Streaming для працэсу жывых дадзеных потокаў для выкарыстання ў базах дадзеных, дадзеных сістэмах і жывых дашборках. Формат курса

Інтэрактыўныя лекцыі і дискусіі. Многія практыкаванні і практыкаванні. Вынікі ў Live-Lab Environment.

Вынікі пошуку - Customization options

Калі вы хочаце падзяліцца сваёй думкай з майстрам, рабіце гэта максімальна ветліва.