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.
2 hour session where I cover what is Apache Camel, latest news on the upcoming Camel v3, and then the main topic of the talk is the new Camel K sub-project for running integrations natively on the cloud with kubernetes. The last part of the talk is about running Camel with GraalVM / Quarkus to archive native compiled binaries that has impressive startup and footprint.
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.
Camel Day Italy 2021 - What's new in Camel 3Claus Ibsen
Slides for the 50 min presentation at Camel Day Italy 2021, where Claus Ibsen and Andrea Cosentino had the opporunity to give a more deep dive talk about the journey towards Camel 3, and what we have done to re-architect camel core in v3 to make it awesome for microservices, cloud native, kubernetes, quarkus, graalvm, knative, apache kafka.
Camel Day Italy 2021: https://www.meetup.com/it-IT/red-hat-developers-italy/events/275332376/
2 hour session where I cover what is Apache Camel, latest news on the upcoming Camel v3, and then the main topic of the talk is the new Camel K sub-project for running integrations natively on the cloud with kubernetes. The last part of the talk is about running Camel with GraalVM / Quarkus to archive native compiled binaries that has impressive startup and footprint.
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
Integrating microservices with apache camel on kubernetesClaus Ibsen
Apache Camel has fundamentally changed the way Java developers build system-to-system integrations by using enterprise integration patterns (EIP) with modern microservice architectures. In this session, we’ll show you best practices with Camel and EIPs, in the world of Spring Boot microservices running on Kubernetes. We'll also discuss practices how to build truly cloud-native distributed and fault-tolerant microservices and we’ll introduce the upcoming Camel 3.0 release, which includes serverless capabilities via Camel K. This talk is a mix with slides and live demos.
Best Practices for ETL with Apache NiFi on Kubernetes - Albert Lewandowski, G...GetInData
Did you like it? Check out our E-book: Apache NiFi - A Complete Guide
https://ebook.getindata.com/apache-nifi-complete-guide
Apache NiFi is one of the most popular services for running ETL pipelines otherwise it’s not the youngest technology. During the talk, there are described all details about migrating pipelines from the old Hadoop platform to the Kubernetes, managing everything as the code, monitoring all corner cases of NiFi and making it a robust solution that is user-friendly even for non-programmers.
Author: Albert Lewandowski
Linkedin: https://www.linkedin.com/in/albert-lewandowski/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
2 hour session where I cover what is Apache Camel, latest news on the upcoming Camel v3, and then the main topic of the talk is the new Camel K sub-project for running integrations natively on the cloud with kubernetes. The last part of the talk is about running Camel with GraalVM / Quarkus to archive native compiled binaries that has impressive startup and footprint.
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.
Camel Day Italy 2021 - What's new in Camel 3Claus Ibsen
Slides for the 50 min presentation at Camel Day Italy 2021, where Claus Ibsen and Andrea Cosentino had the opporunity to give a more deep dive talk about the journey towards Camel 3, and what we have done to re-architect camel core in v3 to make it awesome for microservices, cloud native, kubernetes, quarkus, graalvm, knative, apache kafka.
Camel Day Italy 2021: https://www.meetup.com/it-IT/red-hat-developers-italy/events/275332376/
2 hour session where I cover what is Apache Camel, latest news on the upcoming Camel v3, and then the main topic of the talk is the new Camel K sub-project for running integrations natively on the cloud with kubernetes. The last part of the talk is about running Camel with GraalVM / Quarkus to archive native compiled binaries that has impressive startup and footprint.
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
Integrating microservices with apache camel on kubernetesClaus Ibsen
Apache Camel has fundamentally changed the way Java developers build system-to-system integrations by using enterprise integration patterns (EIP) with modern microservice architectures. In this session, we’ll show you best practices with Camel and EIPs, in the world of Spring Boot microservices running on Kubernetes. We'll also discuss practices how to build truly cloud-native distributed and fault-tolerant microservices and we’ll introduce the upcoming Camel 3.0 release, which includes serverless capabilities via Camel K. This talk is a mix with slides and live demos.
Best Practices for ETL with Apache NiFi on Kubernetes - Albert Lewandowski, G...GetInData
Did you like it? Check out our E-book: Apache NiFi - A Complete Guide
https://ebook.getindata.com/apache-nifi-complete-guide
Apache NiFi is one of the most popular services for running ETL pipelines otherwise it’s not the youngest technology. During the talk, there are described all details about migrating pipelines from the old Hadoop platform to the Kubernetes, managing everything as the code, monitoring all corner cases of NiFi and making it a robust solution that is user-friendly even for non-programmers.
Author: Albert Lewandowski
Linkedin: https://www.linkedin.com/in/albert-lewandowski/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
Integrating systems in the age of Quarkus and CamelClaus Ibsen
Apache Camel has been the Swiss knife of integrating heterogeneous systems for more than a decade. Claus Ibsen explains how Camel adapts to the newest changes with microservices and cloud computing! Apache Camel integrations written on top of Quarkus start in a matter of milliseconds and consume just a few tens of megabytes of RAM. We will explain the technology and show a demo including the famous Quarkus dev mode. Then you will learn how the outstanding integration capabilities of Apache Camel enrich the serverless architectures based on Knative and CamelK!
This is the presentation I made on JavaDay Kiev 2015 regarding the architecture of Apache Spark. It covers the memory model, the shuffle implementations, data frames and some other high-level staff and can be used as an introduction to Apache Spark
2022-06-23 Apache Arrow and DataFusion_ Changing the Game for implementing Da...Andrew Lamb
DataFusion is an extensible and embeddable query engine, written in Rust used to create modern, fast and efficient data pipelines, ETL processes, and database systems.
This presentation explains where it fits into the data eco system and how it helps implement your system in Rust
Building a Streaming Microservice Architecture: with Apache Spark Structured ...Databricks
As we continue to push the boundaries of what is possible with respect to pipeline throughput and data serving tiers, new methodologies and techniques continue to emerge to handle larger and larger workloads
Introduction to Apache Flink - Fast and reliable big data processingTill Rohrmann
This presentation introduces Apache Flink, a massively parallel data processing engine which currently undergoes the incubation process at the Apache Software Foundation. Flink's programming primitives are presented and it is shown how easily a distributed PageRank algorithm can be implemented with Flink. Intriguing features such as dedicated memory management, Hadoop compatibility, streaming and automatic optimisation make it an unique system in the world of Big Data processing.
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudNoritaka Sekiyama
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud (Hadoop / Spark Conference Japan 2019)
# English version #
http://hadoop.apache.jp/hcj2019-program/
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
Running Apache NiFi with Apache Spark : Integration OptionsTimothy Spann
A walk-through of various options in integration Apache Spark and Apache NiFi in one smooth dataflow. There are now several options in interfacing between Apache NiFi and Apache Spark with Apache Kafka and Apache Livy.
Building Reliable Lakehouses with Apache Flink and Delta LakeFlink Forward
Flink Forward San Francisco 2022.
Apache Flink and Delta Lake together allow you to build the foundation for your data lakehouses by ensuring the reliability of your concurrent streams from processing to the underlying cloud object-store. Together, the Flink/Delta Connector enables you to store data in Delta tables such that you harness Delta’s reliability by providing ACID transactions and scalability while maintaining Flink’s end-to-end exactly-once processing. This ensures that the data from Flink is written to Delta Tables in an idempotent manner such that even if the Flink pipeline is restarted from its checkpoint information, the pipeline will guarantee no data is lost or duplicated thus preserving the exactly-once semantics of Flink.
by
Scott Sandre & Denny Lee
ksqlDB is a stream processing SQL engine, which allows stream processing on top of Apache Kafka. ksqlDB is based on Kafka Stream and provides capabilities for consuming messages from Kafka, analysing these messages in near-realtime with a SQL like language and produce results again to a Kafka topic. By that, no single line of Java code has to be written and you can reuse your SQL knowhow. This lowers the bar for starting with stream processing significantly.
ksqlDB offers powerful capabilities of stream processing, such as joins, aggregations, time windows and support for event time. In this talk I will present how KSQL integrates with the Kafka ecosystem and demonstrate how easy it is to implement a solution using ksqlDB for most part. This will be done in a live demo on a fictitious IoT sample.
Dynamically Scaling Data Streams across Multiple Kafka Clusters with Zero Fli...Flink Forward
Flink Forward San Francisco 2022.
Flink consumers read from Kafka as a scalable, high throughput, and low latency data source. However, there are challenges in scaling out data streams where migration and multiple Kafka clusters are required. Thus, we introduced a new Kafka source to read sharded data across multiple Kafka clusters in a way that conforms well with elastic, dynamic, and reliable infrastructure. In this presentation, we will present the source design and how the solution increases application availability while reducing maintenance toil. Furthermore, we will describe how we extended the existing KafkaSource to provide mechanisms to read logical streams located on multiple clusters, to dynamically adapt to infrastructure changes, and to perform transparent cluster migrations and failover.
by
Mason Chen
Designing a complete ci cd pipeline using argo events, workflow and cd productsJulian Mazzitelli
https://www.youtube.com/watch?v=YmIAatr3Who
Presented at Cloud and AI DevFest GDG Montreal on September 27, 2019.
Are you looking to get more flexibility out of your CICD platform? Interested how GitOps fits into the mix? Learn how Argo CD, Workflows, and Events can be combined to craft custom CICD flows. All while staying Kubernetes native, enabling you to leverage existing observability tooling.
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Spark
DevNexus 2022 Atlanta
https://devnexus.com/presentations/7150/
This talk is a quick overview of the How, What and WHY of Apache Pulsar, Apache Flink and Apache NiFi. I will show you how to design event-driven applications that scale the cloud native way.
This talk was done live in person at DevNexus across from the booth in room 311
Tim Spann
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
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
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
Integrating systems in the age of Quarkus and CamelClaus Ibsen
Apache Camel has been the Swiss knife of integrating heterogeneous systems for more than a decade. Claus Ibsen explains how Camel adapts to the newest changes with microservices and cloud computing! Apache Camel integrations written on top of Quarkus start in a matter of milliseconds and consume just a few tens of megabytes of RAM. We will explain the technology and show a demo including the famous Quarkus dev mode. Then you will learn how the outstanding integration capabilities of Apache Camel enrich the serverless architectures based on Knative and CamelK!
This is the presentation I made on JavaDay Kiev 2015 regarding the architecture of Apache Spark. It covers the memory model, the shuffle implementations, data frames and some other high-level staff and can be used as an introduction to Apache Spark
2022-06-23 Apache Arrow and DataFusion_ Changing the Game for implementing Da...Andrew Lamb
DataFusion is an extensible and embeddable query engine, written in Rust used to create modern, fast and efficient data pipelines, ETL processes, and database systems.
This presentation explains where it fits into the data eco system and how it helps implement your system in Rust
Building a Streaming Microservice Architecture: with Apache Spark Structured ...Databricks
As we continue to push the boundaries of what is possible with respect to pipeline throughput and data serving tiers, new methodologies and techniques continue to emerge to handle larger and larger workloads
Introduction to Apache Flink - Fast and reliable big data processingTill Rohrmann
This presentation introduces Apache Flink, a massively parallel data processing engine which currently undergoes the incubation process at the Apache Software Foundation. Flink's programming primitives are presented and it is shown how easily a distributed PageRank algorithm can be implemented with Flink. Intriguing features such as dedicated memory management, Hadoop compatibility, streaming and automatic optimisation make it an unique system in the world of Big Data processing.
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudNoritaka Sekiyama
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud (Hadoop / Spark Conference Japan 2019)
# English version #
http://hadoop.apache.jp/hcj2019-program/
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
Running Apache NiFi with Apache Spark : Integration OptionsTimothy Spann
A walk-through of various options in integration Apache Spark and Apache NiFi in one smooth dataflow. There are now several options in interfacing between Apache NiFi and Apache Spark with Apache Kafka and Apache Livy.
Building Reliable Lakehouses with Apache Flink and Delta LakeFlink Forward
Flink Forward San Francisco 2022.
Apache Flink and Delta Lake together allow you to build the foundation for your data lakehouses by ensuring the reliability of your concurrent streams from processing to the underlying cloud object-store. Together, the Flink/Delta Connector enables you to store data in Delta tables such that you harness Delta’s reliability by providing ACID transactions and scalability while maintaining Flink’s end-to-end exactly-once processing. This ensures that the data from Flink is written to Delta Tables in an idempotent manner such that even if the Flink pipeline is restarted from its checkpoint information, the pipeline will guarantee no data is lost or duplicated thus preserving the exactly-once semantics of Flink.
by
Scott Sandre & Denny Lee
ksqlDB is a stream processing SQL engine, which allows stream processing on top of Apache Kafka. ksqlDB is based on Kafka Stream and provides capabilities for consuming messages from Kafka, analysing these messages in near-realtime with a SQL like language and produce results again to a Kafka topic. By that, no single line of Java code has to be written and you can reuse your SQL knowhow. This lowers the bar for starting with stream processing significantly.
ksqlDB offers powerful capabilities of stream processing, such as joins, aggregations, time windows and support for event time. In this talk I will present how KSQL integrates with the Kafka ecosystem and demonstrate how easy it is to implement a solution using ksqlDB for most part. This will be done in a live demo on a fictitious IoT sample.
Dynamically Scaling Data Streams across Multiple Kafka Clusters with Zero Fli...Flink Forward
Flink Forward San Francisco 2022.
Flink consumers read from Kafka as a scalable, high throughput, and low latency data source. However, there are challenges in scaling out data streams where migration and multiple Kafka clusters are required. Thus, we introduced a new Kafka source to read sharded data across multiple Kafka clusters in a way that conforms well with elastic, dynamic, and reliable infrastructure. In this presentation, we will present the source design and how the solution increases application availability while reducing maintenance toil. Furthermore, we will describe how we extended the existing KafkaSource to provide mechanisms to read logical streams located on multiple clusters, to dynamically adapt to infrastructure changes, and to perform transparent cluster migrations and failover.
by
Mason Chen
Designing a complete ci cd pipeline using argo events, workflow and cd productsJulian Mazzitelli
https://www.youtube.com/watch?v=YmIAatr3Who
Presented at Cloud and AI DevFest GDG Montreal on September 27, 2019.
Are you looking to get more flexibility out of your CICD platform? Interested how GitOps fits into the mix? Learn how Argo CD, Workflows, and Events can be combined to craft custom CICD flows. All while staying Kubernetes native, enabling you to leverage existing observability tooling.
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Spark
DevNexus 2022 Atlanta
https://devnexus.com/presentations/7150/
This talk is a quick overview of the How, What and WHY of Apache Pulsar, Apache Flink and Apache NiFi. I will show you how to design event-driven applications that scale the cloud native way.
This talk was done live in person at DevNexus across from the booth in room 311
Tim Spann
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
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
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
Cloud-Native Integration with Apache Camel on Kubernetes (Copenhagen October ...Claus Ibsen
Cloud-native applications of the future will consist of hybrid workloads: stateful applications, batch jobs, microservices, and functions, wrapped as Linux containers and deployed via Kubernetes on any cloud.
In this session, we will explore key challenges with function interactions and coordination, addressing these problems using Enterprise Integration Patterns (EIP) and modern approaches with the latest innovations from the Apache Camel community:
- Apache Camel 3
- Camel K
- Camel Quarkus
Apache Camel is the Swiss army knife of integration, and the most powerful integration framework. In this session you will hear about the latest features in the brand new 3rd generation.
Camel K, is a lightweight integration platform that enables Enterprise Integration Patterns to be used natively on any Kubernetes cluster. When used in combination with Knative, a framework that adds serverless building blocks to Kubernetes, and the subatomic execution environment of Quarkus, Camel K can mix serverless features such as auto-scaling, scaling to zero, and event-based communication with the outstanding integration capabilities of Apache Camel.
We will show how Camel K works. We'll also use examples to demonstrate how Camel K makes it easier to connect to cloud services or enterprise applications using some of the 300 components that Camel provides.
Apache Camel v3, Camel K and Camel QuarkusClaus Ibsen
In this session, we will explore key challenges with function interactions and coordination, addressing these problems using Enterprise Integration Patterns (EIP) and modern approaches with the latest innovations from the Apache Camel community:
Apache Camel is the Swiss army knife of integration, and the most powerful integration framework. In this session you will hear about the latest features in the brand new 3rd generation.
Camel K, is a lightweight integration platform that enables Enterprise Integration Patterns to be used natively on any Kubernetes cluster. When used in combination with Knative, a framework that adds serverless building blocks to Kubernetes, and the subatomic execution environment of Quarkus, Camel K can mix serverless features such as auto-scaling, scaling to zero, and event-based communication with the outstanding integration capabilities of Apache Camel.
- Apache Camel 3
- Camel K
- Camel Quarkus
We will show how Camel K works. We’ll also use examples to demonstrate how Camel K makes it easier to connect to cloud services or enterprise applications using some of the 300 components that Camel provides.
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
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.
State of integration with Apache Camel (ApacheCon 2019)Claus Ibsen
Apache Camel is the leading open source integration framework, which has been around for over a decade. In this talk we will look back in history, to understand how the integration landscape has evolved from EAI, SOA, and ESB architectures up to microservices, and now with modern serverless and cloud native platforms. Apache Camel has been along for the ride. And we will look to the future and see how the latest release v3 of Apache Camel, is aimed for running modern cloud native workloads with Camel K. In this talk you will: Learn from history software integration, and why you should rely on existing, proven fully featured integration frameworks instead of rolling out your own DIY solutions. See how software integration is (still) important in today’s modern architectures and what role does Camel have in the new cloud native world. What is new and noteworthy in Apache Camel version 3
Red Hat Nordics 2020 - Apache Camel 3 the next generation of enterprise integ...Claus Ibsen
In this session, we'll focus on:
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.
Introduction to Containers - AWS Startup Day Johannesburg.pdfAmazon Web Services
In this session, we cover all the options for running containers on AWS. This will include an intro of container concepts, and an overview to different services like ECS, EKS, ECR and Fargate. We cover topics like: how to choose the right orchestration platform for your workload, some different tools that are out there to make the process easier, and how to find more information and support as you work.
"Shipping logs to Splunk from a container in AWS howto.
Advantages of running containers in AWS Fargate" by Oleksii Makieiev, Senior systems engineer EPAM Ukraine
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.
Event-driven Applications with Kafka, Micronaut, and AWS Lambda | Dave Klein,...HostedbyConfluent
One of the great things about running applications in the cloud is that you only pay for the resources that you use. But that also makes it more important than ever for our applications to be resource-efficient. This becomes even more critical when we use serverless functions.
Micronaut is an application framework that provides dependency injection, developer productivity features, and excellent support for Apache Kafka. By performing dependency injection, AOP, and other productivity-enhancing magic at compile time, Micronaut allows us to build smaller, more efficient microservices and serverless functions.
In this session, we'll explore the ways that Apache Kafka and Micronaut work together to enable us to build fast, efficient, event-driven applications. Then we'll see it in action, using the AWS Lambda Sink Connector for Confluent Cloud.
OSGi for real in the enterprise: Apache Karaf - NLJUG J-FALL 2010Adrian Trenaman
Want to know how to design, implement and deploy modular enterprise integration solutions using OSGi? The Apache Karaf OSGi shell, used by Apache Felix and Apache ServiceMix, enhances core OSGi implementations like Felix or Equinox with an easy to use, extendible command shell, providing logging, hot deployment, configuration, container administration, clustering, high availability and easy 'feature-based' dependency management In this session, you'll learn how Karaf works, and how you can leverage Karaf either on its own or embedded within ServiceMix to deploy business logic, RESTful services, EIP-based integration flows and web services. You'll learn how to extend the command shell with your own commands, and, use Spring-DM *or* OSGi BluePrint Services to make using OSGi a walk in the park.
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Il talk introduce Confluent, la Confluent Platform, ed in particolare il ruolo della Kafka Connect APIs ed l'Elasticsearch Connector di Confluent. Si spiegherà perché Kafka ed il connector di Confluent per Elastic sono un'ottima e semplice soluzione per aggregare dati da svariate sorgenti e gestire l'input e l'idicizzazione di documenti o dati in Elasticsearch.
Similar to Best Practices for Middleware and Integration Architecture Modernization with Apache Camel (20)
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.
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 enterprise integration world together with Linux containers, running on top of Kubernetes/OpenShift, and deployed as microservices, which are both cloud-native and cloud-portable.
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.
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.
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.
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 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.
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.
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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 runs in containers.
This talk uses Apache Camel as the Java library to build microservice architectured applications. At first we introduce you to Apache Camel and show how you can easily get started with Camel on your computer, and build a microservice application that runs on CDI and Spring-Boot.
The second part of this talk is about running Camel (or any Java project) on Docker and Kubernetes.
We start covering the basic concepts you as a Java developer must understand about Kubernetes. Then we show how to migrate Java projects to build as Docker images and deployable on Kubernetes, with help from fabric8 Maven tooling.
You will also hear about how to make your microservices scalable and distributed by leveraging the facilities that Kubernetes provides for truly distributed services with load balancing and location independence.
You will also see how to manage your container using the Kubernetes CLI and the fabric8 web console.
At the end we have a bit of fun with scaling up and down your Camel application to see how resilient the application is, when we kill containers.
This talk is a 50/50 mix between slides and demo.
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Slides from JavaBin talk in Grimstad Norway, presented by Claus Ibsen in February 2016.
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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.
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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.
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- 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.
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By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
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Your Digital Assistant.
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Stress-free Sign-up
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Individual log-in – Every user has their own log-in id
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Visitor Management System is a secure and user friendly database manager that records, filters, tracks the visitors to your organization.
"Secure Your Premises with VizMan (VMS) – Get It Now"
Best Practices for Middleware and Integration Architecture Modernization with Apache Camel
1. Best Practices for
Middleware and Integration
Architecture Modernization
Claus Ibsen
Red Hat
March 2020
With Apache Camel
2. About
Claus Ibsen
● Senior Principal Software Engineer at Red Hat
● ASF Member & Java Champion
● Apache Camel Tech Lead
● Author of Camel in Action books
● Based in Denmark
● Blog: https://medium.com/@davsclaus
● Linkedin: https://www.linkedin.com/in/davsclaus
● Twitter: @davsclaus
3. Agenda
● What’s Camel
● Camel 3
● Integration Evolution
● Serverless
● Camel K
● Camel Quarkus
● Camel Kafka Connector
● More Material
9. What is Apache Camel
● Java based integration framework
● Runtime support: Spring Boot, Quarks, Java EE, Microprofile, OSGi, Standalone, etc.
● Based on Enterprise Integration Patterns
● Comes with 300+ components (connectors)
● DSL (Java or XML) to describe integration flow (routes)
● Can integrate everything ... almost everything
13. Apache Camel 3 - Projects
Camel
Swiss knife of integration
Camel Spring Boot
Camel on
Spring Boot
14. Apache Camel 3 - Projects
Camel
Swiss knife of integration
Camel Spring Boot
Camel on
Spring Boot
Camel Karaf
Camel on
Apache Karaf / OSGi
15. Apache Camel 3 - Projects
Camel K
Camel on
Kubernetes & Knative
Camel
Swiss knife of integration
Camel Spring Boot
Camel on
Spring Boot
Camel Karaf
Camel on
Apache Karaf / OSGi
16. Apache Camel 3 - Projects
Camel Quarkus
Optimized JVM & Native
compiled Java (GraalVM)
Camel K
Camel on
Kubernetes & Knative
Camel
Swiss knife of integration
Camel Spring Boot
Camel on
Spring Boot
Camel Karaf
Camel on
Apache Karaf / OSGi
17. Apache Camel 3 - Projects
Camel Quarkus
Optimized JVM & Native
compiled Java (GraalVM)
Camel K
Camel on
Kubernetes & Knative
Camel
Swiss knife of integration
Camel Spring Boot
Camel on
Spring Boot
Camel Karaf
Camel on
Apache Karaf / OSGi
Camel Kafka Connector
Kafka Connector with Camel
31. Serverless Requirements
For the platform
● Scaling to zero
● Rapid scaling up and down
● Eventing mechanism
● Routing and networking
For the application runtime
● Fast startup
● Fast first response
● Low on memory and CPU
● Small size on disk
32. Serverless Requirements
For the platform
● Scaling to zero
● Rapid scaling up and down
● Eventing mechanism
● Routing and networking
For the application runtime
● Fast startup
● Fast first response
● Low on memory and CPU
● Small size on disk
K
34. A lightweight integration platform, based on Apache Camel,
born on Kubernetes, with serverless superpowers.
What is Apache Camel K ?
35. A lightweight integration platform, based on Apache Camel,
born on Kubernetes, with serverless superpowers.
What is Apache Camel K ?
Runs on “vanilla” Kubernetes (1) ...
K
1.
36. A lightweight integration platform, based on Apache Camel,
born on Kubernetes, with serverless superpowers.
What is Apache Camel K ?
Runs on “vanilla” Kubernetes (1), Openshift (2) ...
K
1.
K
2.
37. A lightweight integration platform, based on Apache Camel,
born on Kubernetes, with serverless superpowers.
What is Apache Camel K ?
Runs on “vanilla” Kubernetes (1), Openshift (2) and gives its best on a Knative-powered cluster (3)!
K
1.
K
2.
K
3.
42. Architecture of Camel K
Dev Environment Remote Cloud
kamel CLI
Camel K
Operator
“Integration”
Custom
Resource
Running Pod
Live updates!
Fast redeploy!
Less than 1 second!
Tailored for cloud-native development experience
43. Fast Deployment of Camel K
Time to run a integration using different strategies (in seconds)
Lower is better
😃
F-m-p is the “fabric8-maven-plugin”
(http://maven.fabric8.io/) deploying a
average spring-boot based
integration on Minishift vs. a remote
OpenShift cluster (accounting time to
upload the fat Jar). Source S2I build
has been measured in Red Hat Fuse
Online.
49. Java Density Problem
CONTAINER ORCHESTRATION
Node Node Node
Traditional Cloud-Native
Java Stack
Traditional Cloud-Native
Java Stack
Traditional Cloud-Native
Java Stack
Traditional Cloud-Native
Java Stack
NodeJS
NodeJS
NodeJS
NodeJS
NodeJS
NodeJS
NodeJS
Go Go Go
Go Go Go
Go Go Go
Go Go Go
Go Go Go
Go Go Go
Go Go Go
https://developers.redhat.com/blog/2017/03/14/java-inside-docker/
53. What is Quarkus ?
Supersonic Subatomic Java
A Kubernetes Native Java stack tailored for GraalVM &
OpenJDK HotSpot, crafted from the best of breed Java libraries
and standards
60. What is Apache Kafka?
● Kafka is known as
○ a distributed streaming platform
○ or a pub/sub messaging broker
● It’s an ecosystem
○ Multiple components part of Apache Kafka
○ A lot of 3rd party integrations
○ One of them is Kafka Connect
Streams
API
Producer
API
Consumer
API
3rd party
tools
Mirror
Maker
Connect
61. What is Kafka Connect?
● It is a framework that helps you to integrate Kafka with other systems
○ A user can define source and sink connectors to stream data in/out of Kafka brokers
○ Connectors are plugable - you can use one of the many connectors available or write your own
● Distributed and scalable by default
● Automatic offset management
● Simple transformations
● Streaming / batch integration
Kafka Connect:
Source
Connector
Kafka Connect:
Sink
Connector
External
System
External
System
62. What is Camel Kafka Connector?
● A Kafka Connector built on top of Apache Camel
● Started as an internal proof-of-concept
○ A sub-project of the Apache Camel
○ Donated by Red Hat to the ASF on December 2019
● Reuses in a simple way most of the Camel components as Kafka sink and sources
64. Demo S3 to JMS
● https://github.com/oscerd/camel-kafka-connector-demo
● S3 Source connector (camel-aws-s3)
● JMS Sink connector (camel-sjms2)
● A file loaded on a bucket -> file content in a JMS Queue
To run Kafka on
Kubernetes
68. More Camel Material
● Apache Camel K
https://github.com/apache/camel-k
● Apache Camel Quarkus
https://github.com/apache/camel-quarkus
● Apache Camel Kafka Connector
https://github.com/apache/camel-kafka-connector
● Quick Camel K demo
https://www.youtube.com/watch?v=I-g2xt-Qcb8
● Camel K Introduction Blog
https://www.nicolaferraro.me/2018/10/15/introducing-camel-k
● Kubernetes enterprise integration patterns with Camel K webinar
https://www.youtube.com/watch?v=51x9BewGCYA
● Camel K and Knative video
https://www.youtube.com/watch?v=lOqubmVSGdw
69. More Material
● Webinar - Apache Camel 3 is here what’s new
https://www.redhat.com/en/events/webinar/apache-camel-3-here-whats-new
● QCon 2020 Talk by Bilgin - Evolution of Distributed Systems on Kubernetes
https://www.infoq.com/presentations/kubernetes-primitives-design-patterns
https://k8spatterns.io/ https://www.manning.com/books/camel-in-action-second-edition
70. ● Red Hat Integration
https://www.redhat.com/en/products/integration
● Red Hat Middleware
https://developers.redhat.com/middleware
● Red Hat Event Driven Architecture
https://developers.redhat.com/topics/event-driven
More Material
71. Any Questions ?
Follow us on Twitter
@davsclaus
@ApacheCamel
https://github.com/apache/camel
A star on github is appreciated