Apache Camel workshop at BarcelonaJUG in January 2014

This document discusses Enterprise Integration Patterns (EIPs) using Apache Camel, a Java framework for integration and mediation. It provides an overview of common EIPs like content-based routing, normalization, and the transactional client pattern. It also demonstrates how to implement EIPs like these using the Java and Spring DSLs in Camel. Key features of Camel like components, exchanges, processors and error handling are explained. Tools for working with Camel like Fuse IDE and Hawt.io are also introduced.

We start with an introduction to what Apache Camel is, and how you can use Camel to make integration much easier. Allowing you to focus on your business logic, rather than low level messaging protocols, and transports. You will hear how Apache Camel is related Enterprise Integration Patterns which you can use in your architectural designs and as well in Java or XML code, running on the JVM with Camel. You will also hear what other features Camel provides out of the box, which can make integration much easier for you. We also take a moment to look at web console tooling that allows you to get insight into your running Apache Camel applications, which has among others visual route diagrams with tracing/debugging and profiling capabilities. In addition to the web tooling we will also show you other tools in the making. This talk was presented at JDKIO on September 13th 2016.

Red Hat Microservices Architecture Day - New York, November 2015. Presented by Claus Ibsen. Apache Camel is a very popular integration library that works very well with microservice architecture. This talk introduces you to Apache Camel and how you can easily get started with Camel on your computer. Then we cover how to create new Camel projects from scratch as microservices, which you can boot using Camel or Spring Boot, or other micro containers such as Jetty or fat JARs. We then take a look at what options you have for monitoring and managing your Camel microservices using tooling such as Jolokia, and hawtio web console.

Developing Java based microservices ready for the world of containers The so-called experts are saying microservices and containers will change the way we build, maintain, operate, and integrate applications. This talk is intended for Java developers who wants to hear and see how you can develop Java microservices that are ready to run in containers. In this talk we will build a set of Java based Microservices that uses a mix of technologies with: - Spring Boot with Apache Camel - Apache Tomcat with Apache Camel You will see how we can build small discrete microservices with these Java technologies and build and deploy on the Kubernets/OpenShift3 container platform. We will discuss practices how to build distributed and fault tolerant microservices using technologies such as Kubernetes Services, Camel EIPs, Netflixx Hysterix, and Ribbon. We will use Zipkin service tracing across all four Java based microservices to provide a visualization of timings and help highlight latency problems in our mesh of microservices. And the self healing and fault tolerant aspects of the Kubernetes/OpenShift3 platform is also discussed and demoed when we let the chaos monkeys loose killing containers. This talk is a 50/50 mix between slides and demo.

This document summarizes a reflection on GraphQL subscriptions and four GraphQL server implementations on the JVM. It provides an overview of GraphQL and how subscriptions work over websockets. It then evaluates lacinia-pedestal, graphql-spring-boot-starter, graphql-kotlin, and micronaut-graphql in terms of their source, engine used, support for only subscriptions over websockets, and whether they are code or schema first. Performance tests showed average end-to-end latency and throughput of up to 300 new subscriptions/second. The document concludes with questions and future directions for GraphQL subscriptions.

Google App Engine (GAE) is a popular PaaS offering. Where its scalable and reliable environment is hidden behind a custom API. This makes GAE apps hard to port over to other non-GAE environments. But what if one could implement such similar environment? And you could simply move your GAE application’s .war file to this new environment and it would just work? After all, at the end it’s all about the API, plus scalable and reliable services. JBoss CapeDwarf project aims at making this a reality. This presentation will provide a glimpse into what it takes to implement something as GAE, ranging from runtime integration with JBoss Application Server, actual services implementation to last but not least, automated heavy testing.

Subscriptions offer a stream of data to be send to clients. How are they implemented on the api, and how do several GraphQL servers compare?

A talk given to JCConf 2015 on 2015/12/05. 在程式設計領域，“immutable objects” 是相當重要的設計模式。同樣��，在虛擬化及雲端時代，“immutable infrastructure” 也成為新一代的顯學。在資源及流程的充分配合下，這將會大大簡化系統的複雜度，穩定性也會大大提升。 本演講將會從觀念出發，並佐以部份實作建議，讓大家有足夠資訊來評估此架構的好處。 Video: https://youtu.be/9j008nd6-A4

Upload your first module to the Comprehensive Perl Archive Network, interact with it in Github, and send and merge pull requests from co-maintainers.

This document discusses best practices for designing, scaling, and maintaining large-scale web applications. Some of the key points made include: having a consistent and flexible data model, loosely coupling components for easier testing and replacement, using caching strategies like page fragments and memcached, and emphasizing development practices like version control, testing, and monitoring performance. The document advocates for a modular architecture with components like load balancers, reverse proxies, caching layers, and asynchronous job queues.

Spring Framework provides a comprehensive infrastructure to develop Java applications. It handles dependency injection and inversion of control so developers can focus on domain logic rather than plumbing. Spring promotes best practices like clean code, test-driven development, and design patterns. It includes aspects for cross-cutting concerns and supports web development through frameworks like Spring MVC. The document introduces Spring's lightweight and modular IoC container and AOP capabilities for separating concerns.

Join us for this interactive event and get your hands dirty with some WildFly 9 hacking! Our host Kabir Khan will explain how you can contribute to the WildFly project at many different levels, from properly reporting bugs in the forums and issue tracker, to actually being able to submit a pull request. During this interactive event you will have a chance to play with WildFly 9 and try some of the following: • Find a JIRA you want to work on. • See how to check-out the code and setup your IDE. • Build WildFly • Code walkthrough - code organisation, jboss-modules etc. • Debug something from a stack trace in a JIRA issue to nail down the problem. • Try the testsuite • And more!

BackPAN is a historical archive of the Comprehensive Perl Archive Network (CPAN) containing 200k files and 10 GB of data. CPAN itself only contains distributions uploaded by authors and has 55k distributions totaling 4 GB. CPAN tools use an index to install files by putting them in the include path (@INC) without tracking file to distribution mappings or managing versions.

Docker is not just about deploying containers to hundreds of servers. Developers need tools that help with day-to-day tasks and to do their job more effectively. Docker is a great addition to most workflows, from starting projects to writing utilities to make development less repetitive. Docker can help take care of many problems developers face during development such as “it works on my machine” as well as keeping tooling consistent between all of the people working on a project. See how easy it is to take an existing development setup and application and move it over to Docker, no matter your operating system.

This document discusses Git strategies for teams. It outlines several branching strategies including "wing and a prayer", long-running branches, Git flow, and branch-per-feature. Git flow uses long-running branches with specific rules for features, hotfixes, bugs, and only merging develop branches to master once stable. Branch-per-feature creates a new branch for each feature or change and nothing is merged until production deployment. The document also discusses automation, team composition, environments, and selection criteria to consider when choosing a branching strategy.

Ansible playbooks and roles are code and as any other code it should be tested automatically before it is applied in production environments. But unit tests are not as usefull for Ansible code. We need integrations tests with a fresh linux system everytime. We test with the triple-A concept: • Arrange: boot one or more fresh linux VMs (Vagrant, Virtualbox) • Act: apply Ansible code to test • Assert: test state of the VMs with another Ansible playbook More topics: • Why testing the Ansible code too? • How to test on every git commit? • Troubles to create a testing environment

- Perlbrew is a tool for managing multiple perl installations on a system. It allows installing different versions of perl and switching between them. - It isolates perl installations so that installing a new version does not affect existing site libraries or upgrade dependent modules. This avoids conflicts between applications. - Perlbrew provides benefits like not requiring sudo for cpan, easier cleanup of perl environments, and ability to set up isolated perl environments for different applications to avoid incompatible issues.

ActiveMQ is an open source message broker that implements the Java Message Service (JMS) API. It allows applications written in different languages to communicate asynchronously. Apache Camel is an open source integration framework that can be used to build messaging routes between different transports and APIs using a simple domain-specific language. It provides mediation capabilities and supports common integration patterns. Both ActiveMQ and Camel aim to simplify integration between disparate systems through message-based communication.

Building microservices requires more than just infrastructure, but infrastructure does have a role. In this talk we look at microservices from an enterprise perspective and talk about DDD, Docker, Kubernetes and how established open-source projects in the integration space fits a microservices architecture

Developing integration microservices using CI/CD with apache camel, open shift, fabric8.io, jenkins, et al.

We start with an introduction to what Apache Camel is, and how you can use Camel to make integration much easier. Allowing you to focus on your business logic, rather than low level messaging protocols, and transports. You will also hear what other features Camel provides out of the box, which can make integration much easier for you. We look into web console tooling that allows you to get insight into your running Apache Camel applications, which has among others visual route diagrams with tracing/debugging and profiling capabilities. In addition to the web tooling we will also show you other tools in the making.

The document discusses microservices and APIs. It covers how microservices optimize for speed by shedding dependencies and having dependencies on demand through services and APIs. It discusses consumer contracts for APIs and service versioning. It also discusses using an API gateway pattern for scalability, security, monitoring and more. It promotes API management for benefits like access control, analytics, and monetization of microservices.

10 yrs ago, SOA promised a lot of the same things Microservices promise use today. So where did we go wrong? What makes microservices different? In this talk, we discussed from an architectural view how we went sideways with SOA, why we must embrace things like Domain Driven Design and scaled-out architectures, and how microservices can be built with enterprises in mind. We also cover a step-by-step, in-depth tutorial that covers these concepts.

Slides from QConSF Nov 19th, 2011 focusing this time on describing the globally distributed and scaled industrial strength Java Platform as a Service that Netflix has built and run on top of AWS and Cassandra. Parts of that platform are being released as open source - Curator, Priam and Astyanax.

This presentation will demonstrate to developers involved with integration how the Apache Camel project can make your life much easier. We start with an introduction to what Apache Camel is, and how you can use Camel to make integration much easier. Allowing you to focus on your business logic, rather than low level messaging protocols, and transports. You will hear how Apache Camel is related Enterprise Integration Patterns which you can use in your architectural designs and as well in Java or XML code, running on the JVM with Camel. You will also hear what other features Camel provides out of the box, which can make integration much easier for you.

Christian Posta is a principal middleware specialist and architect who has worked with large microservices architectures. He discusses why companies are moving to microservices and cloud platforms like Kubernetes and OpenShift. He covers characteristics of microservices like small autonomous teams and decentralized decision making. Posta also discusses breaking applications into independent services, shedding dependencies between teams, and using contracts and APIs for communication between services.

Microservices architecture is a very powerful way to build scalable systems optimized for speed of change. To do this, we need to build independent, autonomous services which by definition tend to minimize dependencies on other systems. One of the tenants of microservices, and a way to minimize dependencies, is “a service should own its own database”. Unfortunately this is a lot easier said than done. Why? Because: your data. We’ve been dealing with data in information systems for 5 decades so isn’t this a solved problem? Yes and no. A lot of the lessons learned are still very relevant. Traditionally, we application developers have accepted the practice of using relational databases and relying on all of their safety guarantees without question. But as we build services architectures that span more than one database (by design, as with microservices), things get harder. If data about a customer changes in one database, how do we reconcile that with other databases (especially where the data storage may be heterogenous?). For developers focused on the traditional enterprise, not only do we have to try to build fast-changing systems that are surrounded by legacy systems, the domains (finance, insurance, retail, etc) are incredibly complicated. Just copying with Netflix does for microservices may or may not be useful. So how do we develop and reason about the boundaries in our system to reduce complexity in the domain? In this talk, we’ll explore these problems and see how Domain Driven Design helps grapple with the domain complexity. We’ll see how DDD concepts like Entities and Aggregates help reason about boundaries based on use cases and how transactions are affected. Once we can identify our transactional boundaries we can more carefully adjust our needs from the CAP theorem to scale out and achieve truly autonomous systems with strictly ordered eventual consistency. We’ll see how technologies like Apache Kafka, Apache Camel and Debezium.io can help build the backbone for these types of systems. We’ll even explore the details of a working example that brings all of this together.

The document discusses Christian Posta's journey with microservices architectures. It begins by explaining why organizations are moving to microservices and defines microservices. It then covers related topics like cloud platforms, container technologies like Kubernetes and OpenShift, benefits and drawbacks of microservices, and tools for developing microservices like Docker, Kubernetes, OpenShift, and Camel.

Fabric8 is a tool that aims to reduce the gap between development and operations by allowing developers to deploy and manage applications from development through production. It uses profiles and containers to deploy applications in a unified way across environments. Fabric8 supports various containers like Tomcat, Docker, and OpenShift. It includes integrated monitoring via Hawt.io and a shell to help with scripting and diagnostics. The goal is to make developers more self-sufficient by enabling them to take on more operations tasks in their own sandboxes.

Claus Ibsen's presentation during Red Hat's "Microservices Journey with Apache Camel" events that took place in Atlanta on Oct 4th and Minneapolis on Oct 6th.

Oracle Developers APAC Meetup #1 - Working with Wercker This is the hands-on work exercise example used for the Oracle APAC Developers Meetup #1 held in Singapore on 7th February 2018. The worksheets are intended to be used in conjunction with the slides. You can find the slides at : https://www.slideshare.net/DarrelChia1/oracle-apac-developers-meetup-1-working-with-wercker-slides Meetup Site: https://www.meetup.com/Oracle-Developers-APAC/events/247111220/

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. This training helps you understand key concepts within 3 hours.

Containers-and-Kubernetes

This document outlines an introduction to Docker for Java developers, including running Java microservices and applications in Docker containers. It discusses building Docker images with Maven, interacting with the Docker API in Java, continuous delivery with Jenkins and Docker, and deploying Java applications to production using Docker clusters like Kubernetes and Docker Swarm.

Frank van der Linden / elstar IT Since a few years the Domino server is a real Java server. Which give you plenty of new opportunities, such as real servlets. Get and post data to any database via a Java servlet. Develop once, run everywhere. In this session you will learn what are servlets, how to create a servlet as OSGi plugin. Make use of other plugins projects or third party projects and. Run the servlet on a Domino server and other Java servers, like Websphere Liberty Profile, Tomcat and Wildfly. Last but not least, how to deploy the servlet as OSGi plugin or as jar file or update site to the Domino server.

Kubernetes can schedule and manage containers across multiple clusters in different regions through cluster federation. The federation control plane manages deploying replicated applications and services across clusters. It creates a single API and DNS name to discover services running on pods in any federated cluster.