Spring CloudとKafkaを使用したマイクロサービスのトレーニングコース

この講師主導のライブトレーニング（オンラインまたはオンサイト）では、開発者が既存のデータベースやアプリケーションを統合して処理、分析などを行うことを目指しています。

このトレーニングの終了時には、参加者は以下のことができるようになります:

• Kafka Connectを使用して、データベースから大量のデータをKafkaトピックに取り込む。
• アプリケーションサーバーによって生成されたログデータをKafkaトピックに取り込む。
• 収集したすべてのデータをストリーム処理のために利用可能にする。
• Kafkaトピックからデータを二次システムにエクスポートして、保存や分析を行う。

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.

In this instructor-led, live training in 日本 (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.

このインストラクター主導のライブトレーニング（オンラインまたはオンサイト）は、Spring Boot と Spring Cloud のような Java フレームワークを使用して、マイクロサービスベースのアプリケーションを設計、開発、デプロイ、および維持管理したい中級レベルの Java 開発者を対象としています。

このトレーニングの終了時には、参加者は以下のことができるようになります：

• マイクロサービスアーキテクチャの原理と利点を理解する。
• Java と Spring Boot を使用してマイクロサービスを構築およびデプロイする。
• サービスディスカバリ、設定管理、API ゲートウェイを実装する。
• マイクロサービスを効果的にセキュア化し、監視し、スケーリングする。
• Docker と Kubernetes を使用してマイクロサービスをデプロイする。

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.

This instructor-led, live training in 日本 (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 日本 (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.

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 日本, participants will learn how to evaluate different technologies and approaches for the design of a services-based system architecture. The training begins with a discussion and comparison of monolithic systems and service architectures, then digs into the details of microservice architecture.

Participants are given a chance to put their knowledge into practice as they step through the creation and deployment of a set of proof-of-concept microservices built with Spring Cloud, Spring Boot and Docker.
Finally, the relevant infrastructure building blocks are examined to help participants determine the most suitable tools and approaches to use for different organizational requirements.
By the end of this training, participants will have a solid understanding of Service-Oriented Architecture (SOA) and Microservice Architecture as well practical experience using Spring Cloud and related Spring technologies for rapidly developing their own cloud-scale, cloud-ready microservices.

このインストラクター主導のライブトレーニングでは、参加者はSpring CloudとDockerを使用してマイクロサービスを構築する基本を学びます。参加者は演習を通じて知識を試し、サンプルのマイクロサービスを段階的に開発します。

このトレーニング終了時には、参加者は以下のことが Able to できます：

• マイクロサービスの基本を理解する。
• Dockerを使用してマイクロサービスアプリケーションのコンテナを構築する。
• Spring CloudとDockerを使用してコンテナ化されたマイクロサービスを構築およびデプロイする。
• マイクロサービスを発見サービスとSpring Cloud API Gatewayと統合する。
• Docker Composeを使用してエンドツーエンドの統合テストを行う。

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

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

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.

This instructor-led, live training in 日本 (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.

In this instructor-led, live training in 日本, we start with a discussion of microservice architecture. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

By the end of this training, participants will have a solid understanding of how to use Spring Cloud and related Spring technologies to rapidly develop their own cloud-scale, cloud-ready microservices.

Spring Cloud is an open-source lightweight microservices framework for building Java applications for the cloud. Netflix OSS is a set of frameworks and libraries for developing microservices. Spring Cloud integrates nicely with Netflix components using auto configuration and convention over configuration.

In this instructor-led, live training, participants will learn the fundamental concepts of building microservices using Spring Cloud and Netflix OSS. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

By the end of this training participants will have a solid understanding of how to use Spring Cloud and related Spring technologies together with Netflix OSS to rapidly develop their own cloud-scale, cloud-ready microservices.

Audience

• Java Developers

Format of the course

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