Camel K allows building and deploying Apache Camel integration applications on Kubernetes in about 1 second. It provides a lightweight runtime for Camel on Kubernetes that enables low-code/no-code integration using Camel's Java DSL. Camel K applications can take advantage of serverless capabilities provided by Knative like autoscaling and scaling to zero. Quarkus is a Kubernetes-native Java stack that provides a minimal footprint and container-first experience for building microservices. It works well with Camel/Camel K by enabling native compilation of Camel routes for very fast startup times and low memory usage.
SouJava May 2020: Apache Camel 3 - the next generation of enterprise integrationClaus Ibsen
In this session, we'll discuss:
- What’s Apache Camel: An overview of Camel and what you use it for and why you should care.
- Camel 3: Demos of how Camel 3, Camel K and Camel Quarkus all work together, and will provide insights into Camel’s role in the next major release of Red Hat Integration products.
- Camel K: This serverless integration platform provides low-code/no-code capabilities, where integrations can be snapped together quickly using the powers from integration patterns and Camel’s extensive set of connectors.
- Camel Quarkus: Using Knative (the fast runtime of Quarkus) and Camel K brings awesome serverless features, such as auto-scaling, scaling to zero, and event-based communication, with great integration capabilities from Apache Camel.
You will also hear about the latest Camel sub-project Camel Kafka Connectors which makes it possible to use all the Camel components as Kafka Connect connectors.
Finally we bring details of the roadmap for what is coming up in the Camel projects.
And after the presentation we have about 30 minutes of QA answering all the questions from the audience.
Best Practices for Middleware and Integration Architecture Modernization with...Claus Ibsen
This document discusses best practices for middleware and integration architecture modernization using Apache Camel. It provides an overview of Apache Camel, including what it is, how it works through routes, and the different Camel projects. It then covers trends in integration architecture like microservices, cloud native, and serverless. Key aspects of Camel K and Camel Quarkus are summarized. The document concludes with a brief discussion of the Camel Kafka Connector and pointers to additional resources.
Cloud-Native Integration with Apache Camel on Kubernetes (Copenhagen October ...Claus Ibsen
Camel K is a lightweight integration platform based on Apache Camel that is optimized to run on Kubernetes and Knative. It allows developers to write integration logic using the Apache Camel Domain Specific Language and deploy it to Kubernetes with a single command. Camel K runs the integration as microservices on Kubernetes and handles scaling and management of the integration runtime. It aims to provide a serverless experience for building and running integrations in cloud-native environments.
Apache Camel is a leading open source integration framework that has been around for more than a decade. With the release of Apache Camel 3, the Camel family has been extended to include a full range of projects that are tailored to popular platforms including Spring Boot, Quarkus, Kafka, Kubernetes, and others - creating an ecosystem. Join this webinar to learn what’s new in Camel 3 and about Camel projects: - Latest features in Camel 3 - Quick demos of Camel 3, Camel Quarkus, Camel K, and Camel Kafka Connector - Present insights into what's coming next
Speakers: Andrea Cosentino, Claus Ibsen
Serverless integration with Knative and Apache Camel on KubernetesClaus Ibsen
This presentation will introduce Knative, an open source project that adds serverless capabilities on top of Kubernetes, and present Camel K, a lightweight platform that brings Apache Camel integrations in the serverless world. Camel K allows running Camel routes on top of any Kubernetes cluster, leveraging Knative serverless capabilities such as “scaling to zero”.
We will demo how Camel K can connect cloud services or enterprise applications using its 250+ components and how it can intelligently route events within the Knative environment via enterprise integration patterns (EIP).
Target Group: Developers, architects and other technical people - a basic understanding of Kubernetes is an advantage
ApacheCon EU 2016 - Apache Camel the integration libraryClaus Ibsen
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.
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.
Apache Camel Introduction & What's in the boxClaus Ibsen
Slides from JavaBin talk in Grimstad Norway, presented by Claus Ibsen in February 2016.
This slide deck is full up to date with latest Apache Camel 2.16.2 release and includes additional slides to present many of the features that Apache Camel provides out of the box.
This is a classic example of older technology not being used to its fullest, which Justin proves by walking through little-known configuration and optimization tricks that get data flowing reliably and efficiently – even for today’s complexity and scale. This session covers:
A – Camel basics, understanding Exchanges, Routes, and how to implement EIPs with them
B – Examples of real implementations of common EIPs like Content Based Routers and Recipient Lists
C – Integration of Camel with common endpoints, like JMS, FTP, and HTTP
Sun Web Server 7 is a high-performance, scalable web server with built-in clustering, security, and management features. It has seen widespread adoption serving sites with high traffic like MLB.com. The presentation discusses Sun Web Server 7's architecture, performance benchmarks, new features like regular expressions and URL rewriting, security enhancements, and its role in the Sun GlassFish application server portfolio.
The document provides an overview and summary of a presentation titled "Camel riders in the cloud" given at Red Hat DevNation Live in March 2018. The presenter is a senior principal software engineer at Red Hat and long-time committer to the Apache Camel project. The presentation discusses how Apache Camel can be used for distributed integration in microservices and containerized architectures running in the cloud. It outlines best practices for running Camel in containers, including keeping Camel components small, stateless, and using configuration management. Fault tolerance, health checks, Enterprise Integration Patterns, and distributed tracing are also covered.
Apache Camel in the belly of the Docker whaleHenryk Konsek
This document discusses Docker and how it can be used to deploy Apache Camel applications and microservices. It provides an overview of key Docker concepts like images and containers. It then discusses how to structure a Camel application and split it into Docker containers for the different components. Examples are given of Dockerizing Camel routes that connect to ActiveMQ and MongoDB. The document also recommends using Spring Boot to simplify building and running Camel applications in Docker containers.
Getting Started with Apache Camel at DevNation 2014Claus Ibsen
Get off to a good start with Apache Camel. This session will give you an introduction to Apache Camel and teach you:
- How Camel is related to enterprise integration patterns (EIPs).
- How to use EIPs in Camel routes written in Java code or XML files.
- How to get started developing with Camel, including how to set up new projects from scratch using Maven and Eclipse.
- With a live demo, how to build Camel applications in Java, Spring, and OSGi Blueprint.
- How ready-to-use features make integration much easier.
- About the web console tools that give you insight into your running Apache Camel applications, including visual route diagrams with tracing, debugging, and profiling capabilities.
- Useful resources to learn more about Camel.
This session will be taught with a 50/50 mix of slides and live demos, and it will conclude with Q&A time.
Using Apache Camel connectors for external connectivityClaus Ibsen
The document summarizes a public presentation by Claus Ibsen on using Apache Camel connectors for external connectivity. The presentation covers understanding Camel components, essential components like Direct, Bean, File, and JMS, and how to create new Camel components. It also provides information on where to find additional Camel resources.
Event Driven Architecture with Apache Camelprajods
This presentation describes Event Driven Architecture(EDA) support in Camel, and scalability features like SEDA and Akka support in Camel.It starts with an overview of Camel and introduces its simple syntax
Developing Java based microservices ready for the world of containersClaus Ibsen
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 Apache Camel, Spring Boot and WildFly Swarm.
You will see how we can build small discrete microservices with these Java technologies and build and deploy on the Kubernets container platform.
We will discuss practices how to build distributed and fault tolerant microservices using technologies such as Kubernetes Services, Camel EIPs, and Netflixx Hysterix.
And the self healing and fault tolerant aspects of the Kubernetes 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.
The talk was presented at JDKIO on September 13th 2016.
Developing Java based microservices ready for the world of containersClaus Ibsen
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.
Integration made easy with Apache CamelRosen Spasov
This document discusses Apache Camel, an open-source integration framework. It begins with an overview of Camel and enterprise integration patterns. A live demo then shows how to route messages using the Java DSL. The document outlines the key components of Camel, including over 120 connectors, data formats, expression languages and domain-specific languages. It also covers testing, deployment options, and management of Camel applications.
Apache Camel - FUSE community day London 2010 presentationClaus Ibsen
My Apache Camel presentation from the FUSE community day event, London June 2010.
A video/audio/transcript of the presentation is in the works and will later be published at the fusesource (http://fusesource.com) website.
This document provides an overview of Apache Camel K, which allows building and deploying Apache Camel integration applications on Kubernetes in under one second. Camel K uses operators and custom resources to deploy Camel routes defined in Groovy files to Kubernetes. It provides a lightweight runtime for developing cloud-native integration microservices on Kubernetes without needing to build Docker images or configure Kubernetes resources manually. The document outlines some limitations of Camel K as an early project but notes its potential for rapid prototyping of simple integration logic in cloud environments.
DevNation Live 2020 - What's new with Apache Camel 3Claus Ibsen
Join this webinar to learn what’s new in Camel 3 and about Camel projects:
- Latest features in Camel 3
- Quick demos of Camel 3, Camel #Quarkus, #CamelK, and Camel Kafka Connector
- Present insights into what's coming next
The document discusses the history of build tools and outlines a roadmap for sbt 1.0 focused on stability and modularization. It introduces sbt-server as a way to centralize build tasks and allow multiple clients to interact with the build. Key points of the sbt-server design include running tasks in a centralized queue, handling reconnects, using a versioned protocol for communication, and supporting background jobs and input. The document also discusses bringing existing sbt plugins onto sbt-server without breaking functionality.
This document discusses deployment strategies for Ruby on Rails applications. It covers common components of the "Rails stack" including databases, caching, application servers and load balancers. Popular options are mentioned like Nginx, Memcached, Mongrel and Capistrano. Performance optimization techniques are also summarized, such as caching, background processing and memory usage strategies. The document concludes with an overview of common deployment processes and challenges.
This document discusses deployment strategies for Rails applications. It describes using Nginx as a front-end HTTP server with Mongrel as the application server. Capistrano is recommended for deployment automation. Caching at the page, action and fragment level with Memcached is also covered as a strategy for improving performance. Challenges discussed include Ruby threading and memory management issues, as well as integrating C extensions and ensuring interoperability. Installation details are provided for deploying a Rails app with Passenger on Apache. Benchmarks are mentioned comparing Mongrel, Thin and Passenger.
The document discusses how a company called HBC evolved their architecture from a monolithic application to a microservices architecture with streams. It describes how they introduced Kafka and Kafka Streams to share data between microservices in real-time, avoid common antipatterns, simplify development, and improve resilience and performance. The talk outlines how HBC uses Kafka Streams within their microservices to process streaming data, perform aggregations and joins, enable interactive queries, and power their search functionality.
Intro to Apache Kafka I gave at the Big Data Meetup in Geneva in June 2016. Covers the basics and gets into some more advanced topics. Includes demo and source code to write clients and unit tests in Java (GitHub repo on the last slides).
Varnish is a modern, open source HTTP accelerator that provides fast, efficient web caching. It is state-of-the-art, scales well in high traffic environments, and is used by many top websites. Varnish avoids expensive operations and has efficient object purging and eviction. It provides comprehensive logging, management, and real-time statistics collection.
Flink at netflix paypal speaker seriesMonal Daxini
(1) Monal Daxini presented on Netflix's use of Apache Flink for stream processing.
(2) Netflix introduced Flink two years ago and has driven its adoption within the company.
(3) Key aspects of Netflix's Flink usage include around 2,000 routing jobs processing around 3 trillion events per day across around 10,000 containers.
KSQL is an open-source streaming SQL engine for Apache Kafka. It allows users to easily interact with and analyze streaming data in Kafka using SQL-like queries. KSQL builds upon Kafka Streams to provide stream processing capabilities with exactly-once processing semantics. It aims to expand access to stream processing beyond coding by providing an interactive SQL interface for tasks like streaming ETL, anomaly detection, real-time monitoring, and simple topic transformations. KSQL can be run in standalone, client-server, or application deployment modes.
This summary provides an overview of the lightning talks presented at the NetflixOSS Open House:
- Jordan Zimmerman from Netflix presented on several NetflixOSS projects he works on including Curator, a Java library that makes using ZooKeeper easier, and Blitz4j, an asynchronous logging library that improves performance over Log4j.
- Additional talks covered Eureka, a REST service for discovering middle-tier services; Ribbon for load balancing between middle-tier instances; Archaius for dynamic configuration; Astyanax for interacting with Cassandra; and various other NetflixOSS projects.
- The talks highlighted the motivation for these projects including addressing challenges of scaling for Netflix's large data
Cloud Native Night June 2019, Munich: Talk by Moritz Kammerer (Software Architect at QAware)
Join our Meetup: www.meetup.com/cloud-native-muc
Abstract: Startup-Zeiten von Containern werden bei elastischer Skalierung in der Cloud immer wichtiger – wer möchte schon 2 Minuten warten, bis eine neue Instanz des Services erscheint? Hier kann der Shooting Star von Java-basierten Microservices, Spring Boot, nicht glänzen. Systembedingt steigt die Startzeit des Containers mit der Menge der Klassen auf dem Classpath. Auch der Speicherverbrauch einer Spring Boot Anwendung ist nicht gerade gering.
Micronaut, erschaffen von den Machern des Grails-Frameworks, behauptet, diese Probleme in den Griff zu bekommen. In dem Talk sehen wir uns an, wie sich Microservices mit Micronaut entwickeln lassen und prüfen, ob es die Versprechen hält.
Bonus: Da Micronaut kaum Reflection verwendet, sollte es sich mit dem GraalVM AOT Compiler in ein natives Image kompilieren lassen. In dem Vortrag werden wir dies ausprobieren und die Performance dieses Native Images messen.
Porting a Streaming Pipeline from Scala to RustEvan Chan
How we at Conviva ported a streaming data pipeline in months from Scala to Rust. What are the important human and technical factors in our port, and what did we learn?
Camel Kafka Connectors: Tune Kafka to “Speak” with (Almost) Everything (Andre...HostedbyConfluent
Apache Kafka is getting used as an event backbone in new organizations every day. We would love to send every byte of data through the event bus. However, most of the time, connecting to simple third party applications and services becomes a headache that involves several lines of code and additional applications. As a result, connecting Kafka to services like Google Sheets, communication tools such as Slack or Telegram, or even the omnipresent Salesforce, is a challenge nobody wants to face. Wouldn’t you like to have hundreds of connectors readily available out-of-the-box to solve this problem?
Due to these challenges, communities like Apache Camel are working on how to speed up development of key areas of the modern application, like integration. The Camel Kafka Connect project, from the Apache foundation, has enabled their vastly set of connectors to interact with Kafka Connect natively. So, developers can start sending and receiving data from Kafka to and from their preferred services and applications in no time without a single line of code.
In summary, during this session we will:
- Introduce you to the Camel Kafka Connector sub-project from Apache Camel
- Go over the list of connectors available as part of the project
- Showcase a couple of examples of integrations using the connectors
- Share some guidelines on how to get started with the Camel Kafka Connectors
This document provides an overview of microservices and how to develop them using Spring. It discusses the challenges of distributed systems and how Spring Boot and Spring Cloud Netflix address areas like configuration, service registration, load balancing, fault tolerance, and monitoring. Examples are provided for building microservices with Spring Boot, integrating configuration with Spring Cloud Config, registering services with Eureka, load balancing with Ribbon and Feign, handling faults with Hystrix, and monitoring with Hystrix Dashboard. Reactive programming with RxJava is also introduced as an approach for concurrent API integration.
This document discusses end-to-end processing of 3.7 million telemetry events per second using a lambda architecture at Symantec. It provides an overview of Symantec's security data lake infrastructure, the telemetry data processing architecture using Kafka, Storm and HBase, tuning targets for the infrastructure components, and performance benchmarks for Kafka, Storm and Hive.
Apache Spark 2.0 includes improvements that provide considerable speedups for CPU-intensive queries through techniques like code generation. Profiling tools like flame graphs can help analyze where CPU cycles are spent by visualizing stack traces. Flame graphs are useful for performance troubleshooting but have limitations. Testing Spark applications locally and through unit tests allows faster iteration compared to running on clusters and saves resources. It is also important to test with local approximations of distributed components like HDFS and Hive.
How Opera Syncs Tens of Millions of Browsers and Sleeps Well at NightScyllaDB
Opera chose Scylla over Cassandra to sync the data of millions of browsers to a back-end data repository. The results of the migration and further optimizations they made in their stack helped Opera to gain better latency/throughput and lower resources usage beyond their expectations.
Attend this session to learn how to
Migrate your data in a sane way, without any downtime
Connect a Python+Django web app to Scylla, how to use intranode sharding to improve your application
This document summarizes a presentation about near real-time analytics platforms at Uber and LinkedIn. It discusses use cases for streaming analytics, challenges with scalability and operations, and new platforms developed using Apache Samza and SQL. Key points include how Samza is used to build streaming applications with SQL queries, operators, and support for multi-stage workflows. The platforms aim to simplify deployment and management of streaming jobs through interfaces like AthenaX.
Low Code Integration with Apache Camel.pdfClaus Ibsen
Design your integration flows using Camel and JBang for a better developer experience, and make it easily production grade using Quarkus.
Claus Ibsen, Apache Camel lead & Senior Principal Software Engineer, Red Hat
Camel CLI (Camel JBang) provides an easy way to try Apache Camel without extensive configuration. It allows installing Camel dependencies with jbang, developing and running Camel integrations locally, and exporting projects to runtimes like Quarkus. Current features include dependency management, running Camel DSLs, hot reloading, and exporting to Spring Boot. Future plans include managing multiple integrations, improved health checks, and running on additional runtimes. Camel JBang aims to lower the barrier to experimenting with Camel.
JEEConf 2018 - Camel microservices with Spring Boot and KubernetesClaus Ibsen
Apache Camel has fundamentally changed the way enterprise Java developers think about system-to-system integration by making enterprise integration patterns (EIP) a simple declaration in a lightweight application wrapped and delivered as a single JAR.
In this session, we’ll show you how to bring the best practices from the EIP world together with containers, running on top of Kubernetes, and deployed as Spring Boot microservices, which are both cloud-native and cloud-portable.
Building and designing cloud-native microservices impacts how we develop. We’ll discuss practices how to build distributed and fault-tolerant microservices with technologies such as Kubernetes Services, Netflix Hystrix, Camel EIP patterns, and Istio. You will see live demos of us killing containers to test fault tolerance, and more.
Meetup Melbourne August 2017 - Agile Integration with Apache Camel microservi...Claus Ibsen
How to get started developing Camel microservices (or any Java technology for that matter) on a local Kubernetes cluster from zero to deployment.
As a Java developer it may be daunting to know how to get started how to develop container applications that runs on Kubernetes cluster.
Using minikube its very easy to run a local cluster and with the help of fabric8 tooling its even easier to install and run using familiar tools like Maven. In this talk we will build a set of Apache Camel and Java based Microservices that uses Spring Boot and WildFly Swarm. With the help of fabric8 maven tooling you will see how to build, deploy, and run your Java projects on a Kubernetes cluster (local or remote). And even live debugging is easy to do as well.
We will discuss practices how to build distributed and fault tolerant microservices using technologies such as Kubernetes Services, Netflix Hysterix, and Camel EIP patterns for fault tolerance. In the talk you will also hear about related open source projects where you can go explore more such as fabric8, openshift.io, istio, etc. This presentation is a 50/50 mix between slides and demo.
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.
Developing Microservices with Apache CamelClaus Ibsen
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.
Riga Dev Day 2016 - Microservices with Apache Camel & fabric8 on KubernetesClaus Ibsen
This document discusses microservices with Apache Camel and fabric8 on Kubernetes. It begins with a quick Apache Camel demo of a Twitter search application built with Camel. It then provides an overview of Kubernetes and fabric8, including key concepts like pods, replication controllers, services, and labels. The remainder discusses developing and deploying Java microservices to Kubernetes using Camel, CDI, fabric8, and the OpenShift CLI for tasks like deployment, scaling, and viewing logs.
Microservices with apache_camel_barcelonaClaus 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 micro services 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.
The second part of this talk is about running Camel in the cloud.We start by showing you how you can use the Maven Docker Plugin to create a docker image of your Camel application and run it using docker on a single host. Then kubernetes enters the stage and we take a look at how you can deploy your docker images on a kubernetes cloud platform, and how the fabric8 tooling can make this much easier for the Java developers.
At the end of this talk you will have learned about and seen in practice how to take a Java Camel project from scratch, turn that into a docker image, and how you can deploy those docker images in a scalable cloud platform based on Google's kubernetes.
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 micro services 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.
The second part of this talk is about running Camel in the cloud. We start by showing you how you can use the Maven Docker Plugin to create a docker image of your Camel application and run it using docker on a single host. Then kubernetes enters the stage and we take a look at how you can deploy your docker images on a kubernetes cloud platform, and how thenfabric8 tooling can make this much easier for the Java developers.
At the end of this talk you will have learned about and seen in practice how to take a Java Camel project from scratch, turn that into a docker image, and how you can deploy those docker images in a scalable cloud platform based on Google's kubernetes.
Integration using Apache Camel and GroovyClaus Ibsen
Apache Camel is versatile integration library that supports a huge number of components, enterprise integration patterns, and programming languages.
In this this talk I first introduce you to Apache Camel and its concepts. Then we move on to see how you can use the Groovy programming language with Camel as a first class Groovy DSL to build integration flows.
You will also learn how to build a new Camel and Groovy app from scratch from a live demo.
And we also touch how you can use Camel from grails using the grails-camel plugin.
I will also show the web console tools that give you insight into your running Apache Camel applications, including visual route diagrams with tracing, debugging, and profiling capabilities.
This session will be taught with a 50/50 mix of slides and live demos, and it will conclude with Q&A time.
WhatsApp Tracker - Tracking WhatsApp to Boost Online Safety.pdfonemonitarsoftware
WhatsApp Tracker Software is an effective tool for remotely tracking the target’s WhatsApp activities. It allows users to monitor their loved one’s online behavior to ensure appropriate interactions for responsive device use.
Download this PPTX file and share this information to others.
In this talk, we will explore strategies to optimize the success rate of storing and retaining new information. We will discuss scientifically proven ideal learning intervals and content structures. Additionally, we will examine how to create an environment that improves our focus while you remain in the “flow”. Lastly we will also address the influence of AI on learning capabilities.
In the dynamic field of software development, this knowledge will empower you to accelerate your learning curve and support others in their learning journeys.
NBFC Software: Optimize Your Non-Banking Financial CompanyNBFC Softwares
NBFC Software: Optimize Your Non-Banking Financial Company
Enhance Your Financial Services with Comprehensive NBFC Software
NBFC software provides a complete solution for non-banking financial companies, streamlining banking and accounting functions to reduce operational costs. Our software is designed to meet the diverse needs of NBFCs, including investment banks, insurance companies, and hedge funds.
Key Features of NBFC Software:
Centralized Database: Facilitates inter-branch collaboration and smooth operations with a unified platform.
Automation: Simplifies loan lifecycle management and account maintenance, ensuring efficient delivery of financial services.
Customization: Highly customizable to fit specific business needs, offering flexibility in managing various loan types such as home loans, mortgage loans, personal loans, and more.
Security: Ensures safe and secure handling of financial transactions and sensitive data.
User-Friendly Interface: Designed to be intuitive and easy to use, reducing the learning curve for employees.
Cost-Effective: Reduces the need for additional manpower by automating tasks, making it a budget-friendly solution. Benefits of NBFC Software:
Go Paperless: Transition to a fully digital operation, eliminating offline work.
Transparency: Enables managers and executives to monitor various points of the banking process easily.
Defaulter Tracking: Helps track loan defaulters, maintaining a healthy loan management system.
Increased Accessibility: Cutting-edge technology increases the accessibility and usability of NBFC operations. Request a Demo Now!
CViewSurvey Digitech Pvt Ltd that works on a proven C.A.A.G. model.bhatinidhi2001
CViewSurvey is a SaaS-based Web & Mobile application that provides digital transformation to traditional paper surveys and feedback for customer & employee experience, field & market research that helps you evaluate your customer's as well as employee's loyalty.
With our unique C.A.A.G. Collect, Analysis, Act & Grow approach; business & industry’s can create customized surveys on web, publish on app to collect unlimited response & review AI backed real-time data analytics on mobile & tablets anytime, anywhere. Data collected when offline is securely stored in the device, which syncs to the cloud server when connected to any network.
An MVP (Minimum Viable Product) mobile application is a streamlined version of a mobile app that includes only the core features necessary to address the primary needs of its users. The purpose of an MVP is to validate the app concept with minimal resources, gather user feedback, and identify any areas for improvement before investing in a full-scale development. This approach allows businesses to quickly launch their app, test its market viability, and make data-driven decisions for future enhancements, ensuring a higher likelihood of success and user satisfaction.
Explore the rapid development journey of TryBoxLang, completed in just 48 hours. This session delves into the innovative process behind creating TryBoxLang, a platform designed to showcase the capabilities of BoxLang by Ortus Solutions. Discover the challenges, strategies, and outcomes of this accelerated development effort, highlighting how TryBoxLang provides a practical introduction to BoxLang's features and benefits.
Efficient hot work permit software for safe, streamlined work permit management and compliance. Enhance safety today. Contact us on +353 214536034.
https://sheqnetwork.com/work-permit/
Are you wondering how to migrate to the Cloud? At the ITB session, we addressed the challenge of managing multiple ColdFusion licenses and AWS EC2 instances. Discover how you can consolidate with just one EC2 instance capable of running over 50 apps using CommandBox ColdFusion. This solution supports both ColdFusion flavors and includes cb-websites, a GoLang binary for managing CommandBox websites.
React and Next.js are complementary tools in web development. React, a JavaScript library, specializes in building user interfaces with its component-based architecture and efficient state management. Next.js extends React by providing server-side rendering, routing, and other utilities, making it ideal for building SEO-friendly, high-performance web applications.
introduction of Ansys software and basic and advance knowledge of modelling s...sachin chaurasia
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1. ~1 sec build and deploy on Kubernetes
Claus Ibsen
@davsclaus
2. About me
● Senior Principal Software Engineer at Red Hat
● Java Champion
● 11 years as Apache Camel committer
● Author of Camel in Action books
● https://medium.com/@davsclaus
27. Camel Community in Numbers
● Created in 2007
● 137 Releases
● 471 Contributors on github
● ~ 2500 stars ⭐️ on github (a star is appreciated)
● ~ 36000 commits on master branch (~ 3000/year - 8/day)
● ~ 8600 Q&A on stackoverflow
● ~ 500 users on gitter chat
● 538 follows on twitter (https://twitter.com/apachecamel)
29. The good, bad & ugly
● Huge and active community
● Continued and stable release cadence
● Open and welcoming community (we love contributions)
● Burden on core developers
● Well established and "old project" may not appear to hipsters
● Balance of "keep as-is" vs "modernize architecture"
● The outdated website and documentation
( new site under development: https://camel.apache.org/staging )
31. Camel 3 Timeline
● 3.0 Milestone 1 - February 2019
● 3.0 Milestone 2 - March 2019
● 3.0 Milestone 3 - May 2019
● 3.0 Milestone 3 - July 2019
● 3.0 GA - September 2019
● v3.0 Basic Features
● v3.1 Postponed Features
● v3.2 Postponed Features
● Quicker Releases
Timeboxed
Schedule
32. Camel 3 Major Goals
● Backwards compatible (minimal migration for normal use-cases)
● Light-weight & modular camel-core
● Reactive routing engine (non blocking & back-pressure)
● Tidy up APIs & cleanup of technical debt
● Fluent Builder Endpoint configuration (Java & XML)
● Java 8 DSL improvements
● New Cloud EIP Patterns
33. Camel 3 Major Goals
● Apache Camel K
● GraalVM/Quarkus Support
● Timeboxed Release
● New website & documentation
● More presence on social/workshop/blog posts
● There is still a lot of unexpressed potential
34. Camel 3 Milestone 1
● Released on February 22th 2019
● Migration Guide (work in progress)
https://github.com/apache/camel/blob/master/MIGRATION.md
● Example of migrating Camel in Action 2nd source code
https://github.com/camelinaction/camelinaction2/compare/camel3m1
35. Camel 3 Milestone 1
● Modularization of camel-core
○ camel-api API for end users
○ camel-base Internal
○ camel-core Just like Camel 2.x
○ camel-management-api API for JMX management
○ camel-management-impl JMX is optional
○ camel-support API and support classes for end
users / components
○ camel-util General small utilities
○ camel-util-json Internal (Camel tooling and such)
○ camel-core-xml XML DSL support
○ camel-core-osgi OSGi support (no longer in camel-
core)
● camel-core-engine (M3)
Mock
Component still
in camel-core
We will attempt to
move it out in M3
38. Camel 3 Milestone 1
● Reactive Core
○ All EIPs now fully reactive
○ Blocking vs Non-Blocking code-paths merged into one (Non-Blocking)
● Reactive Core (todo)
○ Backpressure (M3)
○ Client API (M3)
○ Java 9+ Flowable API (M3)
■ M1/M2 currently Java 8
○ Component metadata
■ To know if a component is fully reactive
● Vert.X (todo 3.1/3.2)
○ Better camel-vertx integration
■ To use its fully reactive components
Not all Camel
components are
100% reactive
compliant
39. Camel 3 Milestone 1
● Tidy up API and clean technical debt
○ All deprecated code and components removed
○ Some APIs tidied up
...More internal cleanup on the way (M2/M3)
● camel-core-osgi
○ Upgraded to OSGi R6
● camel-activemq
○ Apache ActiveMQ 5.x (do not use activemq-camel)
40. Camel 3 Milestone 1
● Improve project build
○ Faster build and re-build of project
○ More source generation of metadata and other files
○ … more to come in M2
● Apache Camel K
○ Camel K 0.3.0 supports
■ Camel 2.x
■ Camel 3 milestone 1
41. Camel 3 Milestone 2
● Released soon (in VOTE)
● Migration Guide (work in progress)
https://github.com/apache/camel/blob/master/MIGRATION.md
● Example of migrating Camel in Action 2nd source code
https://github.com/camelinaction/camelinaction2/compare/camel3m2
42. Camel 3 Milestone 2
● Tidy up API and clean technical debt
○ All deprecated code and components removed
○ Some APIs tidied up
...More internal cleanup on the way (M3)
● Optimized type converters
○ Invoke type converter directly (no reflection method call)
○ Optimized type converter discovery and loading on startup
○ Allows pre-load with GraalVM/Quarkus
43. Camel 3 Milestone 2
● Properties component
○ Fallback to lookup property as OS ENV variable
○ To work better with Kubernetes / Camel K
● Camel Main
○ More functionality out of the box
■ dependency injection (IoC) with camel-core Java (RouteBuilder classes)
■ dependency injection (IoC) with camel-spring Java
○ Convention over configuration out of the box
■ application.properties
○ To work better with Camel K
44. Camel 3 Milestone 2
● Writeable registry
○ bind beans to registry
camelContext().getRegistry().bind("myName", myBean);
bindToRegistry("myName", myBean); (in RouteBuilder)
@BindToRegistry
○ Easier unit testing
○ Easier Camel standalone
● Step EIP
○ Group together EIPs (logic name)
○ Grouped performance statistics
45. Camel 3 Milestone 2
● Quarkus/GraalVM Support
○ Works better with quarkus-camel
○ More minimal/optimized camel-core
○ Works better with Camel K
46. Camel 3 Milestone 3 - TODO
● Quarkus/GraalVM Support
○ Generate additional metadata in JARs
○ Better integration with Quarkus
○ More minimal/optimized camel-core
○ Works better with Camel K
47. Camel 3 Milestone 3 - TODO
● camel-core-engine
○ Minimal set of dependency
● camel-mock
○ Move Mock out of camel-core (potentially not possible)
● camel-bean
○ Move Bean component / Language out of camel-core (likely not possible)
48. Camel 3 Milestone 3 - TODO
● Auto generated Endpoint DSL
○ Fluent Builders for endpoint in Java / XML
49. Camel 3 Milestone 4
● Reactive Core
○ Backpressure
○ Client API
○ Flowable API (Java9+)
● Data Shape
○ IN vs OUT contract
■ Route
■ Component
○ Improved Data Mapping support
■ camel-atmasmap
50. Camel 3 Milestone 4
● Java 11
○ Builds on Java 11
○ Java 8 to be dropped
● Stabilization and polish
○ Tidy up for GA release
● New website
○ Staging for preview
51. Camel 3 - GA September 2019
Camel 3 is our
“Duke Nukem
Forever”
project 😁
53. Why Camel K
● Building and deploying Camel on Kubernetes
○ fabric8-maven-plugin to build the image
○ s2i on OpenShift to build the image
○ ci/cd pipeline (such as Jenkins) to build the image
● Minute(s) to build and deploy "Hello Camel"
We want to go faster
54. Why Camel K
● Low-code / No-code integration
○ Engine in Red Hat Fuse Online
● Cloud Native Camel on Kubernetes
● Camel Serverless
Cloud Native Camel
on Kubernetes
55. Why Camel K
● Quick Prototyping
● Simple or little business logic
● Tiny microservices
● Opinionated runtime
Not intended for traditional
bigger projects
-
Instead use regular Camel
56. Limitations of Camel K
● Opinionated runtime
● Not a replacement for Apache Camel
● Must run on Kubernetes
● Testing framework currently limited
● Early project
... but Camel K has a lot of
potential
57. Overview of Camel K
A lightweight platform for running Camel integration DSL in the cloud.
● Based on operator-sdk
● Works on Openshift and “vanilla” Kubernetes
$ kamel run routes.groovy --dev
from(“telegram:bots/bot-id”)
.transform()...
.to(“kafka:topic”);
from(“kafka:topic”)
.to(“http:my-host/api/path”);
File routes.groovy
60. Knative
Kubernetes-based platform to build, deploy, and manage
modern serverless workloads
● Serving
● Build
● Events
Serving and Events
are most relevant
to Camel K
62. Camel K and Knative
Now part of Knative
Camel K is Serverless:
● Autoscaling and scaling to zero (Knative Serving)
● Event-based communication (Knative eventing)
● CamelSources in Knative: https://github.com/knative/eventing-
sources/tree/master/contrib/camel/samples
+
63. Camel K
Demo
Let’s build a Telegram Chat Bot in few minutes.
You’ll need shortly on
your phone:
- Telegram App
- A QR Code reader
65. Camel K - Links
● Apache Camel K
https://github.com/apache/camel-k
● Camel K Telegram Demo Code
https://github.com/nicolaferraro/camel-k-chuck-bot
● Camel K Introduction Blog
https://www.nicolaferraro.me/2018/10/15/introducing-camel-k
● Camel K and Knative Tutorial
https://redhat-developer-demos.github.io/knative-tutorial/knative-tutorial/1.0-
SNAPSHOT/camelk/intro.html
67. What is Quarkus
A Kubernetes Native Java stack tailored for
GraalVM & OpenJDK HotSpot, crafted from the
best of breed Java libraries and standards
68. Minimal Footprint - Quarkus
● Minimal footprint Java applications
○ Native vs Quarkus+OpenJDK JVM vs Traditional JVM
69. Container First - Quakrus
● First Class Support for Graal/SubstrateVM
○ Native compiled first-class supported
● Build Time Metadata Processing
○ Pre-Build and "warump" as much as possible during build time
● Reduction in Reflection Usage
○ Reduce startup and memory
● Native Image Pre Boot
○ Most of startup serialized into native image to startup even faster
https://quarkus.io/vision/container-first
73. Quarkus and Camel / Camel K
● Works with Camel K and regular Camel (3.x)
● Fast startup, low memory usage
● Compile Camel routes to native code (Camel K)
● Compile Camel projects to native code (Camel)
● Bring Camel to the serverless world
74. Quarkus and Camel / Camel K
● Work to do
○ Quarkus Dev mode
○ More native Camel components
○ More camel-core optimizations
○ Better Camel and Quakrus integration
○ Better Camel and CDI with Quarkus
○ Native Compilation with GraalVM is not rock solid
Camel is not house-hold name, aka not well known like Apache Tomcat, Kafka etc.
Camel is used for any kind of system integration
Camel inspired by this book.
Book published 13 years ago
Universal patterns that are reusable for developers to use
Very simple Camel route example
Another example with a bit more where we pickup files, split the files line by line, and convert each line from a custom format to XML and send the Apache ActiveMQ
Another example with a bit more where we pickup files, split the files line by line, and convert each line from a custom format to XML and send the Apache ActiveMQ
Another example with a bit more where we pickup files, split the files line by line, and convert each line from a custom format to XML and send the Apache ActiveMQ
Another example with a bit more where we pickup files, split the files line by line, and convert each line from a custom format to XML and send the Apache ActiveMQ
Another example with a bit more where we pickup files, split the files line by line, and convert each line from a custom format to XML and send the Apache ActiveMQ
Overall architecture of Apache Camel
Where can you run Camel?
Camel is a very lightweight integration framework / engine
You can run Camel everywhere (Java)
Camel was created 11 years ago (before cloud / linux containers)
Back then typical deployment was using application servers (still a choice today)
However cloud, docker and containers is the future direction
Slides with connectors for various things
Traditional / Legacy systems
Public Cloud (the 3 big vendors, AWS, Google and MS Azure)
SaaS (social media, salesforce and others)
IoT (gateways to embedded devices)