Tips, Expertise, Articles and Advice from the Pro's for Your Website or Blog to Succeed
On the heels of the ActiveMQ v5.16.4 release, the Apache ActiveMQ team has released v5.17.0.
The v5.17.0 release will be most notable for what comes next. This release was more about aligning Java JDK and dependencies for moving forward than adding new features.
Meet Josh (a pseudonym). Josh is your typical developer. He’s good at writing code in his native language, hates documentation, and REALLY hates the “drag and drop” approach to developing software found in bloated API management platforms. Josh would rather write code, weave in some docs and avoid worrying about security, networking, deployment, and reliability. Josh avoids venturing into newer networking technologies like Istio, labeling them unnecessarily complicated to configure and maintain. He would rather write everything in Java, Groovy, or his go-to integration library: Apache Camel.
Recently Josh stumbled across an open-source API platform called Kong. After 30 minutes of playing around, Josh discovered how easy it was to:
Microservices are becoming a very popular architectural style for developing greenfield applications and also for brownfield solutions. People are moving away from the monolith solutions due to added advantages like faster development and go-to-market, increased adoption of containerization and small teams, and a lighter codebase.
You can use either Spring Boot, Quarkus, or Lagom frameworks to develop the REST services. I would like to show how we can use Apache Camel, a leading opensource integration framework, to write REST services easier and quicker using the REST domain-specific language (DSL).
When a client reaches its API usage limits, API rejects the request by returning theHTTP 429 Too Many Requests error to the client. The client may retry after the retry period that is usually returned in a custom HTTP response header. This is an API throttling strategy commonly employed.
There are situations where API may depend on an external service provider that may have a fixed capacity. As this external dependency has a fixed capacity and cannot handle bursts in requests, we have to control the throughput of requests to meet the service level agreements of the dependency. In this article, we will explore two alternate strategies to throttle API usage to deal with this condition:
In this article, I will demonstrate an example of Camel SQL Stored Procedure.
I tested this POC in Fedora 34 and used the following product/technologies.
Getting Started with Apache Camel? This post is for you. But I am not going to dive into how to write the Camel route, there are plenty of materials out there that do a better job than me. A good place to get started is the one and only Camel Blog, it gives you all the latest and greatest news from the community. If you want to start from the basics, I highly recommend Camel in Action II Book. It has everything you need to know about writing Camel. Or join the Camel community mailing list or Zulip to ask questions, it's very friendly and welcoming.
If you are a returning Camel rider, I would go through this post, where it will get you up to speed on what to expect. Another good resource is the FAQ page. I found the majority of the getting started enquiries can be found here.
Part 1 || Part 2 || Part 3
This blog is part two of my three blogs on how to build a hybrid multi-cloud event mesh with Camel. In this part, I am going over the more technical aspects. Going through how I set up the event mesh demo.
In this tutorial, we will be implementing a Spring Boot + Apache Camel Hello World Example to copy files from one location to another. In a previous tutorial, we had looked at enterprise application integration and how Apache Camel helps achieve it. In this tutorial, we will have a brief look at why we need to use Apache Camel in microservices architecture. What benefits it provides.
SAP is the world's leading enterprise business processing solution. There is always going to be a need to connect an organization's core to other SaaS offerings, partners, or even another SAP solution. Red Hat Integration (RHI) offers flexibility, adaptability, and the ability to move quickly with framework and software to build the event-driven integration architecture. Not just connect, but also maintain data consistency across platforms.
SAP offers interfaces such as OData v4, OData v2, RESTful API, and SOAP as the HTTP-based one, or you can also use the classic RFC(remote procedure call) and iDoc Messages. And there is a recent event enablement add-on that offers AMQP and MQTT protocol. Camel in RHI allows you to seamlessly connect to any of your preferred protocols. Developers can simply configure to connect to the endpoints with their address, credential, and/or SSL settings.
Each step of an Apache Camel Application triggers an event that allows us to read or edit data while the message travels on the "Route." The provided mechanism to access these events is the EventNotifierSupport class.
Apache Camel's route is a sequence of steps, executed in order by Camel, that consumes and processes a message. The initial point of this sequence is represented by the method from(). A route may have many processing components that modify a message or send it to an endpoint.
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In this article, we are going to discuss Camel Kafka Connectors. Apache Camel has more than 300 components used for the integration of different endpoints and protocols. Thus, this combination of Camel components and Kafka has made integrations with Kafka even more easy, stable, and versatile. Also, not a single line of code is required.
One of the most common issues that we usually tackle with customers when modernizing legacy integrations is when they have a collection of legacy SOAP web services that don't integrate well enough with the modern RESTful-based clients.
In this article, we are going to use Apache Camel to build a REST endpoint that will translate REST calls to a SOAP envelope, get the response, and send it back to the client.
The financial industry is going through a radical change; the new generation of customers expects more precise, immediate, and comprehensive services. The emerging fintech offerings completely reshape the industry. New regulations are constantly emerging and need to be applied timely. In 2020, the unexpected global pandemic is another accelerator for this revolution. Around the world branches and offices are closed, more services and operations have been moving online, on the cloud, and on devices. At the same time, in the world of technology, people are moving toward becoming cloud-native, more precisely Kubernetes- native. Which completely changes the mindset of deployment, packaging, software development, and even the structures of how the IT teams are formed.
Financial institutions have shifted their focuses, and invest more heavily on the IT infrastructure in order to:
Event-Driven Architecture (EDA) is a way of designing applications and services to respond to real-time information based on the sending and receiving of information about individual events. Serverless is all about providing service on a provision as-used basis. Combining both you get the best of both worlds.
Loose coupling of services - For better fault tolerance, and can add/remove functionality on the go without affecting others.
Apache Camel is an open-source framework for message-oriented middleware with a rule-based routing and mediation engine that provides a Java object-based implementation of the Enterprise Integration Patterns using an application programming interface to configure routing and mediation rules
Red Hat AMQ Streams is a massively-scalable, distributed, and high-performance data streaming platform based on the Apache ZooKeeper and Apache Kafka projects.
Recently, I've been having a look around at autoscaling options for applications deployed onto Kubernetes. There are quite a few emerging options. I decided to give KEDA a spin. KEDA stands for Kubernetes Event-Driven Autoscaling, and that's exactly what it does.
KEDA is a tool you can deploy into your Kubernetes cluster which will autoscale Pods based on an external event or trigger. Events are collected by a set of Scalers, which integrate with a range of applications like:
Apache Camel is an open-source software integration framework implementing the patterns described in the Enterprise Integration Patterns book.
The detailed description of the framework can be found on its official website.
To run a camel spring boot or camel main application in Kubernetes, it requires a developer to build the docker or s2i images, create Kubernetes resources and then apply the resources to a running cluster which is very time-consuming. Camel K solves this problem and saves development time with the dev mode. Simply adding a --dev flag while running code allows the developer to deploy instantly to Kubernetes and also make any changes to the running pod whenever the source file is updated.
We know that camel supports multiple DSL such as Java or Groovy and Camel K supports it as well. What is new in Camel K is that the automatic dependencies management feature. The developer need not worry about packaging a deployable artifact or the maven or Gradle dependencies of various components. It automatically resolves the necessary dependencies from a source file during deployment. And also only one source file is enough to run integration in a pod.