This document provides an overview of building applications using Spring Cloud Stream, Spring Boot, Apache Kafka, and Lombok. It demonstrates how to create a simple Spring Boot microservice that takes messages from a REST API, writes them to a Kafka topic, reads from the topic, and outputs the messages to the console. The tutorial explains how to set up the necessary dependencies and configurations to integrate the applications with Kafka and Spring Cloud Stream.
Event Driven Microservices with Spring Cloud Stream #jjug_ccc #ccc_ab3Toshiaki Maki
The document describes Spring Cloud Stream, an event-driven microservice framework built on Spring Boot and Spring Integration. It provides primitives for building message-driven microservices including persistent publish-subscribe messaging, consumer groups, and support for multiple message brokers like RabbitMQ and Kafka. Applications are developed as message sources, sinks and processors. Spring Cloud Stream handles mapping of applications to messaging infrastructure.
Java Microservices with Spring Boot and Spring Cloud - Denver JUG 2019Matt Raible
A lightning talk I gave at the Denver JUG meetup on December 11, 2019. This presentation shows how to build a secure microservices architecture with Spring Boot and Spring Cloud. It also shows you how you can generate the same architecture using JHipster. It's based on three blog posts I wrote:
* https://developer.okta.com/blog/2019/05/22/java-microservices-spring-boot-spring-cloud
* https://developer.okta.com/blog/2019/05/23/java-microservices-spring-cloud-config
* https://developer.okta.com/blog/2019/08/28/reactive-microservices-spring-cloud-gateway
Cloud Event Driven Architectures with Spring Cloud Stream 2.0VMware Tanzu
SpringOne Platform 2017
Oleg Zhurakousky, Pivotal; Gary Russel, Pivotal
"Event driven have never left the main stage, but with the advent of cloud-native, distributed architectures (such as microservices) it has become more popular than ever.
But it is a broad category that covers a variety of use cases, ranging from enterprise integration to data streaming. So, how to make sense of them all, and especially, what are the best tool for the task?
In this presentation we will provide an overview of the various types of event-driven architectures, and how the different message-oriented components of the Spring portfolio (Spring Kafka, Spring AMQP, Spring Integration, Spring Cloud Stream) fit into the picture."
Microservices with Spring and Cloud FoundryAlain Sahli
Cloud Foundry allows developers to deploy easily and often their applications. This is a great thing but it is only a part of the whole picture. In order to smoothly scale an application some patterns and basic architecture concepts must be taken into consideration. With Spring Boot, applications can be split into smaller parts called Microservices, which can be scaled in a more fine-grained manner. In addition Spring Cloud provides tools to quickly build some of the common patterns in distributed systems (e.g. configuration management, service discovery, circuit breakers).
Why PCF is the best platform for Spring BootToshiaki Maki
Pivotal Cloud Foundry (PCF) provides many out-of-the-box features for managing and operating Spring Boot apps, including a cloud profile, Spring Cloud Connectors, Spring Cloud Services, a Trace Exporter, Spring Actuator support in Apps Manager, and a Metrics Forwarder Service. These features simplify development and operations of microservices built with Spring technologies when deployed to PCF.
Microservice With Spring Boot and Spring CloudEberhard Wolff
Spring Boot and Spring Cloud are an ideal foundation for creating Microservices based on Java. This presentation explains basic concepts of these libraries.
Spring IO 2016 - Spring Cloud Microservices, a journey inside a financial entityToni Jara
The presentation explains the journey from a monolithic architecture to Spring Cloud Microservices for application development inside a financial entity, along with the transition to DevOps strategies… a journey that has just begun…
JOHN HUMPHREYS VP OF ENGINEERING INFRASTRUCTURE SYSTEMS, NOMURA
Spring Boot is a modern and extensible development framework that aims (and succeeds!) to take as much pain as possible out of developing with Java. With just a few Maven dependencies, new or existing programs become runnable, init.d-compliant uber-JARs or uber-WARs with embedded web-servers and virtually zero-configuration, code or otherwise. As an added freebie, Spring Boot Actuator will provide your programs with amazing configuration-free production monitoring facilities that let you have RESTFUL endpoints serving live stack-traces, heap and GC statistics, database statuses, spring-bean definitions, and password-masked configuration file audits.
Event Driven Microservices with Spring Cloud Stream #jjug_ccc #ccc_ab3Toshiaki Maki
The document describes Spring Cloud Stream, an event-driven microservice framework built on Spring Boot and Spring Integration. It provides primitives for building message-driven microservices including persistent publish-subscribe messaging, consumer groups, and support for multiple message brokers like RabbitMQ and Kafka. Applications are developed as message sources, sinks and processors. Spring Cloud Stream handles mapping of applications to messaging infrastructure.
Java Microservices with Spring Boot and Spring Cloud - Denver JUG 2019Matt Raible
A lightning talk I gave at the Denver JUG meetup on December 11, 2019. This presentation shows how to build a secure microservices architecture with Spring Boot and Spring Cloud. It also shows you how you can generate the same architecture using JHipster. It's based on three blog posts I wrote:
* https://developer.okta.com/blog/2019/05/22/java-microservices-spring-boot-spring-cloud
* https://developer.okta.com/blog/2019/05/23/java-microservices-spring-cloud-config
* https://developer.okta.com/blog/2019/08/28/reactive-microservices-spring-cloud-gateway
Cloud Event Driven Architectures with Spring Cloud Stream 2.0VMware Tanzu
SpringOne Platform 2017
Oleg Zhurakousky, Pivotal; Gary Russel, Pivotal
"Event driven have never left the main stage, but with the advent of cloud-native, distributed architectures (such as microservices) it has become more popular than ever.
But it is a broad category that covers a variety of use cases, ranging from enterprise integration to data streaming. So, how to make sense of them all, and especially, what are the best tool for the task?
In this presentation we will provide an overview of the various types of event-driven architectures, and how the different message-oriented components of the Spring portfolio (Spring Kafka, Spring AMQP, Spring Integration, Spring Cloud Stream) fit into the picture."
Microservices with Spring and Cloud FoundryAlain Sahli
Cloud Foundry allows developers to deploy easily and often their applications. This is a great thing but it is only a part of the whole picture. In order to smoothly scale an application some patterns and basic architecture concepts must be taken into consideration. With Spring Boot, applications can be split into smaller parts called Microservices, which can be scaled in a more fine-grained manner. In addition Spring Cloud provides tools to quickly build some of the common patterns in distributed systems (e.g. configuration management, service discovery, circuit breakers).
Why PCF is the best platform for Spring BootToshiaki Maki
Pivotal Cloud Foundry (PCF) provides many out-of-the-box features for managing and operating Spring Boot apps, including a cloud profile, Spring Cloud Connectors, Spring Cloud Services, a Trace Exporter, Spring Actuator support in Apps Manager, and a Metrics Forwarder Service. These features simplify development and operations of microservices built with Spring technologies when deployed to PCF.
Microservice With Spring Boot and Spring CloudEberhard Wolff
Spring Boot and Spring Cloud are an ideal foundation for creating Microservices based on Java. This presentation explains basic concepts of these libraries.
Spring IO 2016 - Spring Cloud Microservices, a journey inside a financial entityToni Jara
The presentation explains the journey from a monolithic architecture to Spring Cloud Microservices for application development inside a financial entity, along with the transition to DevOps strategies… a journey that has just begun…
JOHN HUMPHREYS VP OF ENGINEERING INFRASTRUCTURE SYSTEMS, NOMURA
Spring Boot is a modern and extensible development framework that aims (and succeeds!) to take as much pain as possible out of developing with Java. With just a few Maven dependencies, new or existing programs become runnable, init.d-compliant uber-JARs or uber-WARs with embedded web-servers and virtually zero-configuration, code or otherwise. As an added freebie, Spring Boot Actuator will provide your programs with amazing configuration-free production monitoring facilities that let you have RESTFUL endpoints serving live stack-traces, heap and GC statistics, database statuses, spring-bean definitions, and password-masked configuration file audits.
Spring Cloud Function & Project riff #jsugToshiaki Maki
This document discusses Spring Cloud Function and Project Riff. It provides an overview of serverless computing and functions-as-a-service (FaaS). It introduces Spring Cloud Function as a way to write functions in Spring Boot and deploy them to various FaaS providers. It also describes Project Riff, an open source FaaS platform that runs on Kubernetes and provides event-driven functions through containers and sidecars that connect functions to event brokers. It demonstrates packaging functions as containers and connecting them to brokers through sidecars to handle event streaming and scaling of functions.
Game of Streams: How to Tame and Get the Most from Your Messaging PlatformsVMware Tanzu
The document discusses using messaging platforms in distributed architectures and provides an overview of Spring Cloud Stream. It describes how Spring Cloud Stream can be used with different messaging platforms like Kafka and RabbitMQ. The document also provides code samples for a source service that generates aircraft position data and sends it to a processor service, which transforms the data and filters out records before sending it to a sink service.
Microservices - java ee vs spring boot and spring cloudBen Wilcock
Spring Boot and Spring Cloud provide an easier and more productive framework for building cloud-native microservices compared to Java EE. Spring Boot simplifies the development, deployment, and management of microservices. Spring Cloud adds helpful capabilities for service discovery, external configuration, load balancing, and monitoring that are missing from Java EE. While Java EE adoption is declining, the use of Spring Boot and Spring Cloud is growing rapidly among developers.
The document provides an overview of Spring Cloud, including:
- Spring Cloud aims to provide tools for building distributed systems using familiar Spring tools. It wraps other implementation stacks to be consumed via Spring.
- Core components include service discovery with Eureka, client-side load balancing with Ribbon, and circuit breaking with Hystrix.
- Additional tools include the Feign REST client, API gateway capabilities, and integration with Spring Boot.
- Examples demonstrate basic configurations for service registration, load balancing between instances, and using circuit breakers and fallback methods.
This document discusses Spring Boot, an open source framework for building microservices and web applications. It provides scaffolding to help build Spring-based services more quickly. The author chose Spring Boot for a project because it integrates well with other frameworks like Jersey and allows building services quickly. Key Spring Boot components discussed include REST frameworks, embedded servers, logging frameworks, security, and metrics. The author outlines their Spring Boot stack and package structure. They discuss using Spring Data for persistence, Swagger for API documentation, and helper libraries like Lombok. The document also covers testing approaches using REST Assured and Spring Integration.
This document discusses Angular, TypeScript, and Katana. It provides an overview of these technologies including what OWIN and Project Katana are, how to decouple the client and server, and demos of using Angular, TypeScript, and Reactive Extensions with ASP.NET. It also summarizes what Angular, TypeScript, and Reactive Extensions are and how they can be used together to build single page applications.
Microservices with Java, Spring Boot and Spring CloudEberhard Wolff
Spring Boot makes creating small Java application easy - and also facilitates operations and deployment. But for Microservices need more: Because Microservices are a distributed systems issues like Service Discovery or Load Balancing must be solved. Spring Cloud adds those capabilities to Spring Boot using e.g. the Netflix stack. This talks covers Spring Boot and Spring Cloud and shows how these technologies can be used to create a complete Microservices environment.
Microservices with Netflix OSS and Spring Cloud - Dev Day Orangeacogoluegnes
This document discusses how Netflix OSS and Spring Cloud can be used together to implement a microservices architecture. It describes various libraries like Eureka for service discovery, Hystrix for circuit breaking, Ribbon for load balancing, and Zuul for API gateway functionality. It also explains how Spring Boot simplifies application development and Spring Cloud integrates these Netflix libraries and provides additional features like a configuration server. Overall, Netflix OSS and Spring Cloud provide the tools needed to build resilient microservices with service discovery, load balancing, and other capabilities in a transparent way for developers.
Building Distributed Systems with Netflix OSS and Spring CloudMatt Stine
As presented at: http://www.meetup.com/Pivotal-Open-Source-Hub/events/219264521/
With the advent of microservice and cloud-native application architectures, building distributed systems is becoming increasingly common for the enterprise Java developer. Fortunately many of the innovators in the space, including Twitter, LinkedIn, and Netflix, have embraced the JVM as they’ve built increasingly complex systems, with Netflix open-sourcing much of its toolkit for constructing these systems at NetflixOSS.
Spring Cloud provides tools for developers to quickly build some of the common patterns in distributed systems. Many of these patterns are provided via wrapping the battle-tested components found at NetflixOSS.
Managing your Docker image continuously with Concourse CIToshiaki Maki
This document discusses managing Docker images continuously using Concourse CI. It describes using a Docker image resource in a Concourse pipeline configuration file to build a custom Docker image. The pipeline pulls from a Git repository, builds the image using a Dockerfile, and pushes the new image to a registry on each run, ensuring the image is always up to date.
The document discusses various boilerplate patterns related to building microservices using the Spring Framework and Spring Cloud. It outlines patterns for application coordination, configuration, operations for the JVM, runtime platform provisioning, and microservice operations. It also introduces Spring Cloud projects like Config Server, Eureka, Ribbon, Hystrix, Stream, and Sleuth that can help implement these patterns to build cloud-native microservice architectures.
Spring Boot on Amazon Web Services with Spring Cloud AWSVMware Tanzu
SpringOne 2021
Session Title: Spring Boot on Amazon Web Services with Spring Cloud AWS
Speakers: Maciej Walkowiak, Software Consultant at Independent; Matej Nedic, Software engineer at Ingemark
A brief introduction to OWIN and Katana, the basics and few basic details on the analysis of the internal workings of OWIN and functions, the middleware registrations and how they all compare to the traditional request processing pipelines.
Simplify Cloud Applications using Spring CloudRamnivas Laddad
This document discusses how to simplify cloud applications using Spring Cloud. It describes Spring Cloud's goals of abstracting over cloud services and environments. It covers using Java and XML configuration, scanning for services, and acquiring services. It also discusses Spring Cloud's extensibility for cloud platforms, services, and frameworks. The document includes demos of using Spring Cloud on Cloud Foundry, Heroku, and with Hadoop. It describes the integration with Spring Boot.
OWIN and Katana Project - Not Only IIS - NoIISBilal Haidar
This presentation is an introduction to OWIN and Katana project. The title states it all, NOT ONLY IIS, meaning that, we can now host Web Apps outside IIS.
Serverless with Spring Cloud Function, Knative and riff #SpringOneTour #s1tToshiaki Maki
This document summarizes a presentation about serverless computing using Spring Cloud Function, Knative, and riff. It discusses what serverless computing is, an overview of Spring Cloud Function for developing serverless applications, and how Knative and riff can be used as platforms to deploy serverless workloads on Kubernetes. Code examples are provided to demonstrate invoking functions via HTTP and messaging with Spring Cloud Function and deploying functions to Knative and riff.
The document discusses Kotlin support in Spring Framework 5. It covers how Kotlin can be used with Spring Boot and Spring's programming model through features like extension functions and reified type parameters. It provides code examples of using Kotlin idioms with Spring components like the application context, JdbcTemplate, and RestTemplate to make the code more concise and readable. It also briefly mentions new features in Spring Framework 5 like reactive support using Spring WebFlux and using router functions with Kotlin.
This session provides an overview of how to build and deploy Spring-based applications to the Cloud Foundry platform.
The session will cover application configuration parameters, binding services to your application, deployment options using using STS, the vmc command tool, as well as the new Apache Maven plugin for Cloud Foundry. Gunnar will demonstrate how to deploy applications to both micro and public Cloud Foundry and will also show how debugging works with Cloud Foundry and how you can inspect services remotely using Caldecott.
Gunnar will also show various options to keep your War-files deployable to both Cloud Foundry and stand-alone Servlet Containers using auto-reconfiguration, the cloud namespace, and Spring 3.1 profiles.
Lastly, he will give a high-level overview how you can use Cloud Foundry together with Spring Integration in order to create scalable Spring applications.
The document discusses various topics related to Spring Boot including Spring Data REST, CSRF protection, and Cloud Foundry integration. It provides code examples for exposing repositories as REST APIs with Spring Data REST, handling errors and exceptions, and securing applications with CSRF tokens. It also briefly mentions Spring Boot features like configuration properties and the Actuator.
Spark Streaming provides an easier API for streaming data than Storm, replacing Storm's spouts and bolts with Akka actors. It integrates better with Hadoop and makes time a core part of its API. This document provides instructions for setting up Spark Streaming projects using sbt or Maven and includes a demo reading from Kafka and processing a Twitter stream.
Cloud Foundry Meetup Stuttgart 2017 - Spring Cloud DevelopmentAndreas Falk
1) The document discusses Spring Boot and Spring Cloud frameworks for building cloud-native Java applications. It covers concepts like externalizing configurations, distributed tracing, logging as event streams, and integrating with Cloud Foundry.
2) The document recommends treating backing services as attached resources and binding services to applications. It also discusses storing encrypted configuration data and refreshing app configurations without restarts.
3) The document promotes principles of 12-factor apps like declaring explicit dependencies, maximizing robustness with fast startup/shutdown, and treating logs as event streams. It suggests pushing apps to Cloud Foundry with "cf push" and not worrying about infrastructure details.
Spring Cloud Function & Project riff #jsugToshiaki Maki
This document discusses Spring Cloud Function and Project Riff. It provides an overview of serverless computing and functions-as-a-service (FaaS). It introduces Spring Cloud Function as a way to write functions in Spring Boot and deploy them to various FaaS providers. It also describes Project Riff, an open source FaaS platform that runs on Kubernetes and provides event-driven functions through containers and sidecars that connect functions to event brokers. It demonstrates packaging functions as containers and connecting them to brokers through sidecars to handle event streaming and scaling of functions.
Game of Streams: How to Tame and Get the Most from Your Messaging PlatformsVMware Tanzu
The document discusses using messaging platforms in distributed architectures and provides an overview of Spring Cloud Stream. It describes how Spring Cloud Stream can be used with different messaging platforms like Kafka and RabbitMQ. The document also provides code samples for a source service that generates aircraft position data and sends it to a processor service, which transforms the data and filters out records before sending it to a sink service.
Microservices - java ee vs spring boot and spring cloudBen Wilcock
Spring Boot and Spring Cloud provide an easier and more productive framework for building cloud-native microservices compared to Java EE. Spring Boot simplifies the development, deployment, and management of microservices. Spring Cloud adds helpful capabilities for service discovery, external configuration, load balancing, and monitoring that are missing from Java EE. While Java EE adoption is declining, the use of Spring Boot and Spring Cloud is growing rapidly among developers.
The document provides an overview of Spring Cloud, including:
- Spring Cloud aims to provide tools for building distributed systems using familiar Spring tools. It wraps other implementation stacks to be consumed via Spring.
- Core components include service discovery with Eureka, client-side load balancing with Ribbon, and circuit breaking with Hystrix.
- Additional tools include the Feign REST client, API gateway capabilities, and integration with Spring Boot.
- Examples demonstrate basic configurations for service registration, load balancing between instances, and using circuit breakers and fallback methods.
This document discusses Spring Boot, an open source framework for building microservices and web applications. It provides scaffolding to help build Spring-based services more quickly. The author chose Spring Boot for a project because it integrates well with other frameworks like Jersey and allows building services quickly. Key Spring Boot components discussed include REST frameworks, embedded servers, logging frameworks, security, and metrics. The author outlines their Spring Boot stack and package structure. They discuss using Spring Data for persistence, Swagger for API documentation, and helper libraries like Lombok. The document also covers testing approaches using REST Assured and Spring Integration.
This document discusses Angular, TypeScript, and Katana. It provides an overview of these technologies including what OWIN and Project Katana are, how to decouple the client and server, and demos of using Angular, TypeScript, and Reactive Extensions with ASP.NET. It also summarizes what Angular, TypeScript, and Reactive Extensions are and how they can be used together to build single page applications.
Microservices with Java, Spring Boot and Spring CloudEberhard Wolff
Spring Boot makes creating small Java application easy - and also facilitates operations and deployment. But for Microservices need more: Because Microservices are a distributed systems issues like Service Discovery or Load Balancing must be solved. Spring Cloud adds those capabilities to Spring Boot using e.g. the Netflix stack. This talks covers Spring Boot and Spring Cloud and shows how these technologies can be used to create a complete Microservices environment.
Microservices with Netflix OSS and Spring Cloud - Dev Day Orangeacogoluegnes
This document discusses how Netflix OSS and Spring Cloud can be used together to implement a microservices architecture. It describes various libraries like Eureka for service discovery, Hystrix for circuit breaking, Ribbon for load balancing, and Zuul for API gateway functionality. It also explains how Spring Boot simplifies application development and Spring Cloud integrates these Netflix libraries and provides additional features like a configuration server. Overall, Netflix OSS and Spring Cloud provide the tools needed to build resilient microservices with service discovery, load balancing, and other capabilities in a transparent way for developers.
Building Distributed Systems with Netflix OSS and Spring CloudMatt Stine
As presented at: http://www.meetup.com/Pivotal-Open-Source-Hub/events/219264521/
With the advent of microservice and cloud-native application architectures, building distributed systems is becoming increasingly common for the enterprise Java developer. Fortunately many of the innovators in the space, including Twitter, LinkedIn, and Netflix, have embraced the JVM as they’ve built increasingly complex systems, with Netflix open-sourcing much of its toolkit for constructing these systems at NetflixOSS.
Spring Cloud provides tools for developers to quickly build some of the common patterns in distributed systems. Many of these patterns are provided via wrapping the battle-tested components found at NetflixOSS.
Managing your Docker image continuously with Concourse CIToshiaki Maki
This document discusses managing Docker images continuously using Concourse CI. It describes using a Docker image resource in a Concourse pipeline configuration file to build a custom Docker image. The pipeline pulls from a Git repository, builds the image using a Dockerfile, and pushes the new image to a registry on each run, ensuring the image is always up to date.
The document discusses various boilerplate patterns related to building microservices using the Spring Framework and Spring Cloud. It outlines patterns for application coordination, configuration, operations for the JVM, runtime platform provisioning, and microservice operations. It also introduces Spring Cloud projects like Config Server, Eureka, Ribbon, Hystrix, Stream, and Sleuth that can help implement these patterns to build cloud-native microservice architectures.
Spring Boot on Amazon Web Services with Spring Cloud AWSVMware Tanzu
SpringOne 2021
Session Title: Spring Boot on Amazon Web Services with Spring Cloud AWS
Speakers: Maciej Walkowiak, Software Consultant at Independent; Matej Nedic, Software engineer at Ingemark
A brief introduction to OWIN and Katana, the basics and few basic details on the analysis of the internal workings of OWIN and functions, the middleware registrations and how they all compare to the traditional request processing pipelines.
Simplify Cloud Applications using Spring CloudRamnivas Laddad
This document discusses how to simplify cloud applications using Spring Cloud. It describes Spring Cloud's goals of abstracting over cloud services and environments. It covers using Java and XML configuration, scanning for services, and acquiring services. It also discusses Spring Cloud's extensibility for cloud platforms, services, and frameworks. The document includes demos of using Spring Cloud on Cloud Foundry, Heroku, and with Hadoop. It describes the integration with Spring Boot.
OWIN and Katana Project - Not Only IIS - NoIISBilal Haidar
This presentation is an introduction to OWIN and Katana project. The title states it all, NOT ONLY IIS, meaning that, we can now host Web Apps outside IIS.
Serverless with Spring Cloud Function, Knative and riff #SpringOneTour #s1tToshiaki Maki
This document summarizes a presentation about serverless computing using Spring Cloud Function, Knative, and riff. It discusses what serverless computing is, an overview of Spring Cloud Function for developing serverless applications, and how Knative and riff can be used as platforms to deploy serverless workloads on Kubernetes. Code examples are provided to demonstrate invoking functions via HTTP and messaging with Spring Cloud Function and deploying functions to Knative and riff.
The document discusses Kotlin support in Spring Framework 5. It covers how Kotlin can be used with Spring Boot and Spring's programming model through features like extension functions and reified type parameters. It provides code examples of using Kotlin idioms with Spring components like the application context, JdbcTemplate, and RestTemplate to make the code more concise and readable. It also briefly mentions new features in Spring Framework 5 like reactive support using Spring WebFlux and using router functions with Kotlin.
This session provides an overview of how to build and deploy Spring-based applications to the Cloud Foundry platform.
The session will cover application configuration parameters, binding services to your application, deployment options using using STS, the vmc command tool, as well as the new Apache Maven plugin for Cloud Foundry. Gunnar will demonstrate how to deploy applications to both micro and public Cloud Foundry and will also show how debugging works with Cloud Foundry and how you can inspect services remotely using Caldecott.
Gunnar will also show various options to keep your War-files deployable to both Cloud Foundry and stand-alone Servlet Containers using auto-reconfiguration, the cloud namespace, and Spring 3.1 profiles.
Lastly, he will give a high-level overview how you can use Cloud Foundry together with Spring Integration in order to create scalable Spring applications.
The document discusses various topics related to Spring Boot including Spring Data REST, CSRF protection, and Cloud Foundry integration. It provides code examples for exposing repositories as REST APIs with Spring Data REST, handling errors and exceptions, and securing applications with CSRF tokens. It also briefly mentions Spring Boot features like configuration properties and the Actuator.
Spark Streaming provides an easier API for streaming data than Storm, replacing Storm's spouts and bolts with Akka actors. It integrates better with Hadoop and makes time a core part of its API. This document provides instructions for setting up Spark Streaming projects using sbt or Maven and includes a demo reading from Kafka and processing a Twitter stream.
Cloud Foundry Meetup Stuttgart 2017 - Spring Cloud DevelopmentAndreas Falk
1) The document discusses Spring Boot and Spring Cloud frameworks for building cloud-native Java applications. It covers concepts like externalizing configurations, distributed tracing, logging as event streams, and integrating with Cloud Foundry.
2) The document recommends treating backing services as attached resources and binding services to applications. It also discusses storing encrypted configuration data and refreshing app configurations without restarts.
3) The document promotes principles of 12-factor apps like declaring explicit dependencies, maximizing robustness with fast startup/shutdown, and treating logs as event streams. It suggests pushing apps to Cloud Foundry with "cf push" and not worrying about infrastructure details.
Kafka Connect & Streams - the ecosystem around KafkaGuido Schmutz
After a quick overview and introduction of Apache Kafka, this session cover two components which extend the core of Apache Kafka: Kafka Connect and Kafka Streams/KSQL.
Kafka Connects role is to access data from the out-side-world and make it available inside Kafka by publishing it into a Kafka topic. On the other hand, Kafka Connect is also responsible to transport information from inside Kafka to the outside world, which could be a database or a file system. There are many existing connectors for different source and target systems available out-of-the-box, either provided by the community or by Confluent or other vendors. You simply configure these connectors and off you go.
Kafka Streams is a light-weight component which extends Kafka with stream processing functionality. By that, Kafka can now not only reliably and scalable transport events and messages through the Kafka broker but also analyse and process these event in real-time. Interestingly Kafka Streams does not provide its own cluster infrastructure and it is also not meant to run on a Kafka cluster. The idea is to run Kafka Streams where it makes sense, which can be inside a “normal” Java application, inside a Web container or on a more modern containerized (cloud) infrastructure, such as Mesos, Kubernetes or Docker. Kafka Streams has a lot of interesting features, such as reliable state handling, queryable state and much more. KSQL is a streaming engine for Apache Kafka, providing a simple and completely interactive SQL interface for processing data in Kafka.
How can you accelerate the delivery of new, high-quality services? How can you be able to experiment and get feedback quickly from your customers? To get the most out of the agility afforded by serverless and containers, it is essential to build CI/CD pipelines that help teams iterate on code and quickly release features. In this talk, we demonstrate how developers can build effective CI/CD release workflows to manage their serverless or containerized deployments on AWS. We cover infrastructure-as-code (IaC) application models, such as AWS Serverless Application Model (AWS SAM) and new imperative IaC tools. We also demonstrate how to set up CI/CD release pipelines with AWS CodePipeline and AWS CodeBuild, and we show you how to automate safer deployments with AWS CodeDeploy.
Why write two add-ons when you can write one and deploy it to both Server and Cloud? Charles Gutjahr from ThinkTilt shares how they brought their Connect add-on to different clouds. Learn how he packaged the add-on in a Docker container to offer it behind the firewall. Hear about the implications for installation, data storage, security, and functionality. By the end of the talk, you'll be able to decide whether Dockerization is the right choice for your add-on.
Charles Gutjahr, Co-Founder and Technology Architect, ThinkTilt
Apache Kafka - Scalable Message Processing and more!Guido Schmutz
After a quick overview and introduction of Apache Kafka, this session cover two components which extend the core of Apache Kafka: Kafka Connect and Kafka Streams/KSQL.
Kafka Connects role is to access data from the out-side-world and make it available inside Kafka by publishing it into a Kafka topic. On the other hand, Kafka Connect is also responsible to transport information from inside Kafka to the outside world, which could be a database or a file system. There are many existing connectors for different source and target systems available out-of-the-box, either provided by the community or by Confluent or other vendors. You simply configure these connectors and off you go.
Kafka Streams is a light-weight component which extends Kafka with stream processing functionality. By that, Kafka can now not only reliably and scalable transport events and messages through the Kafka broker but also analyse and process these event in real-time. Interestingly Kafka Streams does not provide its own cluster infrastructure and it is also not meant to run on a Kafka cluster. The idea is to run Kafka Streams where it makes sense, which can be inside a “normal” Java application, inside a Web container or on a more modern containerized (cloud) infrastructure, such as Mesos, Kubernetes or Docker. Kafka Streams has a lot of interesting features, such as reliable state handling, queryable state and much more. KSQL is a streaming engine for Apache Kafka, providing a simple and completely interactive SQL interface for processing data in Kafka.
Kafka Connect & Kafka Streams/KSQL - the ecosystem around KafkaGuido Schmutz
After a quick overview and introduction of Apache Kafka, this session cover two components which extend the core of Apache Kafka: Kafka Connect and Kafka Streams/KSQL.
Kafka Connects role is to access data from the out-side-world and make it available inside Kafka by publishing it into a Kafka topic. On the other hand, Kafka Connect is also responsible to transport information from inside Kafka to the outside world, which could be a database or a file system. There are many existing connectors for different source and target systems available out-of-the-box, either provided by the community or by Confluent or other vendors. You simply configure these connectors and off you go.
Kafka Streams is a light-weight component which extends Kafka with stream processing functionality. By that, Kafka can now not only reliably and scalable transport events and messages through the Kafka broker but also analyse and process these event in real-time. Interestingly Kafka Streams does not provide its own cluster infrastructure and it is also not meant to run on a Kafka cluster. The idea is to run Kafka Streams where it makes sense, which can be inside a “normal” Java application, inside a Web container or on a more modern containerized (cloud) infrastructure, such as Mesos, Kubernetes or Docker. Kafka Streams has a lot of interesting features, such as reliable state handling, queryable state and much more. KSQL is a streaming engine for Apache Kafka, providing a simple and completely interactive SQL interface for processing data in Kafka.
Norman Sutorius discusses using Swift on the server, including frameworks like Vapor and Kitura that allow building server-side applications in Swift. He demonstrates deploying a sample Todo backend app to Cloud Foundry using both Vapor and Kitura. While Swift has benefits like memory management and compatibility with iOS development, challenges include longer build times and a language still undergoing changes.
Cloud Native Programing with Docker and KubernetesBallerina
This document discusses cloud native programming with Docker and Kubernetes. It introduces Ballerina annotations that allow developers to build Docker images directly from Ballerina code. The annotations configure Docker image names, ports, and registries. Ballerina's build command then automatically generates Dockerfiles and builds images. Similarly, Kubernetes annotations are introduced to deploy Ballerina services to Kubernetes clusters for cloud native deployment.
Apache Kafka - Scalable Message Processing and more!Guido Schmutz
Apache Kafka is a distributed streaming platform for handling real-time data feeds and deriving value from them. It provides a unified, scalable infrastructure for ingesting, processing, and delivering real-time data feeds. Kafka supports high throughput, fault tolerance, and exactly-once delivery semantics.
Event Streaming with Kafka Streams and Spring Cloud Stream | Soby Chacko, VMwareHostedbyConfluent
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Oracle 23c New Features For DBAs and Developers.pptx
Spring Cloud Stream with Kafka
1. SPRING CLOUD STREAM
WITH KAFKA
by David Kiss
(
)
http://kaviddiss.com/2018/03/03/spring-cloud-
stream-kafka/
Navigate : Space / Arrow Keys | - Menu | - Fullscreen | - Overview | - Blackout | - Speaker | - HelpM F O B S ?
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2. OVERVIEW
This sample project demonstrates how to build
applications using
, , ,
and .
real-
time streaming event-driven
architecture Spring Boot Spring Cloud Stream Apache
Kafka Lombok
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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3. By end of this tutorial you'll have a simple Spring Boot
based Greetings microservice running that
1. takes a message from a REST api
2. writes it to a Kafka topic
3. reads it from the topic
4. outputs it to the console
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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5. WHAT IS SPRING CLOUD STREAMING?
Spring Cloud Stream is a framework built upon Spring
Boot for building message-driven microservices.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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6. WHAT IS KAFKA?
Kafka is a popular high performant and horizontally
scalable messaging platform originally developed by
LinkedIn.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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8. Download Kafka from and untar it:here
> tar -xzf kafka_2.11-1.0.0.tgz
> cd kafka_2.11-1.0.0
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9. Start Zookeeper and Kafka
On Windows:
On Linux or Mac:
> binwindowszookeeper-server-start.bat configzookeeper.propert
> binwindowskafka-server-start.bat configserver.properties
> bin/zookeeper-server-start.sh config/zookeeper.properties
> bin/kafka-server-start.sh config/server.properties
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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10. If Kafka is not running and fails to start after your
computer wakes up from hibernation, delete the
<TMP_DIR>/kafka-logs folder and then start Kafka
again.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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11. WHAT IS LOMBOK?
Lombok is a java framework that automatically
generates getters, setters, toString(), builders, loggers,
etc. in the code.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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13. Go to to create a maven project:https://start.spring.io
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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14. 1. Add necessary dependencies: Spring Cloud
Stream, Kafka, Devtools (for hot redeploys
during development, optional), Actuator (for
monitoring application, optional), Lombok (make
sure to also have the Lombok plugin installed in your
IDE)
2. Click the Generate Project button to download the
project as a zip le
3. Extract zip le and import the maven project to your
favourite IDE
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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15. Notice the maven dependencies in the pom.xml le:
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-stream</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-stream-kafka</artifactId>
</dependency>
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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16. <!-- Also install the Lombok plugin in your IDE -->
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<!-- hot reload - press Ctrl+F9 in IntelliJ after a code change
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-devtools</artifactId>
<optional>true</optional>
</dependency>
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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17. ... also the <dependencyManagement> section:
<dependencyManagement>
<dependencies>
<dependency>
<!-- Import dependency management from Spring Boo
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-dependencies</artifactId>
<version>$
{spring-boot.version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
...
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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22. In order for our application to be able to communicate
with Kafka, we'll need to de ne an outbound stream to
write messages to a Kafka topic, and an inbound stream
to read messages from a Kafka topic.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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23. Spring Cloud provides a convenient way to do this by
simply creating an interface that de nes a separate
method for each stream.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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24. The inboundGreetings() method de nes the
inbound stream to read from Kafka and
outboundGreetings() method de nes the
outbound stream to write to Kafka.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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25. During runtime Spring will create a java proxy based
implementation of the GreetingsStreams interface
that can be injected as a Spring Bean anywhere in the
code to access our two streams.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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26. CONFIGURE SPRING CLOUD STREAM
Our next step is to con gure Spring Cloud Stream to
bind to our streams in the GreetingsStreams
interface.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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27. This can be done by creating a @Configuration class
com.kaviddiss.streamkafka.config.StreamsConfig
with below code:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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29. Binding the streams is done using the
@EnableBinding annotation where the
GreatingsService interface is passed to.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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30. CONFIGURATION PROPERTIES FOR KAFKA
By default, the con guration properties are stored in
the
src/main/resources/application.properties
le.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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31. However I prefer to use the YAML format as it's less
verbose and allows to keep both common and
environment-speci c properties in the same le.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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32. For now, let's rename application.properties to
application.yaml and paste below con g snippet
into the le:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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34. The above con guration properties con gure the
address of the Kafka server to connect to, and the
Kafka topic we use for both the inbound and outbound
streams in our code. They both must use the same
Kafka topic!
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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35. The contentType properties tell Spring Cloud Stream
to send/receive our message objects as Strings in the
streams.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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36. CREATE THE MESSAGE OBJECT
Create a simple
com.kaviddiss.streamkafka.model.Greetings
class with below code that will represent the message
object we read from and write to the greetings
Kafka topic:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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37. package com.kaviddiss.streamkafka.model;
// lombok autogenerates getters, setters, toString() and a builde
import lombok.Builder;
import lombok.Getter;
import lombok.Setter;
import lombok.ToString;
@Getter @Setter @ToString @Builder
public class Greetings {
private long timestamp;
private String message;
}
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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38. Notice how the class doesn't have any getters and
setters thanks to the Lombok annotations. The
@ToString will generate a toString() method
using the class' elds and the @Builder annotation
will allow us creating Greetings objects using uent
builder (see below).
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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39. CREATE SERVICE LAYER TO WRITE TO KAFKA
Let's create the
com.kaviddiss.streamkafka.service.GreetingsSer
class with below code that will write a Greetings
object to the greetings Kafka topic:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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43. The @Service annotation will con gure this class as a
Spring Bean and inject the GreetingsService
dependency via the constructor.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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44. The @Slf4j annotation will generate an SLF4J logger
eld that we can use for logging.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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45. In the sendGreeting() method we use the injected
GreetingsStream object to send a message
represented by the Greetings object.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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46. CREATE REST API
Now we'll be creating a REST api endpoint that will
trigger sending a message to Kafka using the
GreetingsService Spring Bean:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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50. The @RestController annotation tells Spring that
this is a Controller bean (the C from MVC). The
greetings() method de nes an HTTP GET
/greetings endpoint that takes a message request
param and passes it to the sendGreeting() method
in GreetingsService.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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51. LISTENING ON THE GREETINGS KAFKA TOPIC
Let's create a
com.kaviddiss.streamkafka.service.GreetingsLis
class that will listen to messages on the greetings
Kafka topic and log them on the console:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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53. @Component
@Slf4j
public class GreetingsListener {
@StreamListener(GreetingsStreams.INPUT)
public void handleGreetings(@Payload Greetings greetings) {
log.info("Received greetings: {}", greetings);
}
}
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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54. The @Component annotation similarly to @Service
and @RestController de nes a Spring Bean.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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55. GreetingsListener has a single method,
handleGreetings() that will be invoked by Spring
Cloud Stream with every new Greetings message
object on the greetings Kafka topic. This is thanks to
the @StreamListener annotation con gured for the
handleGreetings() method.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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56. RUNNING THE APPLICATION
The last piece of the puzzle is the
com.kaviddiss.streamkafka.StreamKafkaApplicati
class that was auto-generated by the Spring Initializer:
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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58. No need to make any changes here. You can either run
this class as a Java application from your IDE, or run the
application from the command line using the Spring
Boot maven plugin:
> mvn spring-boot:run
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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59. Once the application is running, go to
in the
browser and check your console.
http://localhost:8080/greetings?message=hello
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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60. SUMMARY
I hope you enjoyed this tutorial. Feel free to ask any
questions and leave your feedback.
[ GitPitch @ github/davidkiss/spring-cloud-streams-kafka-demo ]
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