Skip to main content
Redhat Developers  Logo
  • AI

    Get started with AI

    • Red Hat AI
      Accelerate the development and deployment of enterprise AI solutions.
    • AI learning hub
      Explore learning materials and tools, organized by task.
    • AI interactive demos
      Click through scenarios with Red Hat AI, including training LLMs and more.
    • AI/ML learning paths
      Expand your OpenShift AI knowledge using these learning resources.
    • AI quickstarts
      Focused AI use cases designed for fast deployment on Red Hat AI platforms.
    • No-cost AI training
      Foundational Red Hat AI training.

    Featured resources

    • OpenShift AI learning
    • Open source AI for developers
    • AI product application development
    • Open source-powered AI/ML for hybrid cloud
    • AI and Node.js cheat sheet

    Red Hat AI Factory with NVIDIA

    • Red Hat AI Factory with NVIDIA is a co-engineered, enterprise-grade AI solution for building, deploying, and managing AI at scale across hybrid cloud environments.
    • Explore the solution
  • Learn

    Self-guided

    • Documentation
      Find answers, get step-by-step guidance, and learn how to use Red Hat products.
    • Learning paths
      Explore curated walkthroughs for common development tasks.
    • Guided learning
      Receive custom learning paths powered by our AI assistant.
    • See all learning

    Hands-on

    • Developer Sandbox
      Spin up Red Hat's products and technologies without setup or configuration.
    • Interactive labs
      Learn by doing in these hands-on, browser-based experiences.
    • Interactive demos
      Click through product features in these guided tours.

    Browse by topic

    • AI/ML
    • Automation
    • Java
    • Kubernetes
    • Linux
    • See all topics

    Training & certifications

    • Courses and exams
    • Certifications
    • Skills assessments
    • Red Hat Academy
    • Learning subscription
    • Explore training
  • Build

    Get started

    • Red Hat build of Podman Desktop
      A downloadable, local development hub to experiment with our products and builds.
    • Developer Sandbox
      Spin up Red Hat's products and technologies without setup or configuration.

    Download products

    • Access product downloads to start building and testing right away.
    • Red Hat Enterprise Linux
    • Red Hat AI
    • Red Hat OpenShift
    • Red Hat Ansible Automation Platform
    • See all products

    Featured

    • Red Hat build of OpenJDK
    • Red Hat JBoss Enterprise Application Platform
    • Red Hat OpenShift Dev Spaces
    • Red Hat Developer Toolset

    References

    • E-books
    • Documentation
    • Cheat sheets
    • Architecture center
  • Community

    Get involved

    • Events
    • Live AI events
    • Red Hat Summit
    • Red Hat Accelerators
    • Community discussions

    Follow along

    • Articles & blogs
    • Developer newsletter
    • Videos
    • Github

    Get help

    • Customer service
    • Customer support
    • Regional contacts
    • Find a partner

    Join the Red Hat Developer program

    • Download Red Hat products and project builds, access support documentation, learning content, and more.
    • Explore the benefits

How Kamelets simplify Camel integrations on Kubernetes

November 1, 2022
Mohammadi Iram
Related topics:
Developer toolsEvent-drivenKubernetesMicroservices
Related products:
Red Hat OpenShift

    Modern applications, rarely coded from scratch, are formed by combining software components (known as subsystems) into a single system. This process is called integration. Typical subsystems include databases and web services. This article explains how Apache Camel and Kubernetes support easy integration of such services through Kamelets.

    How Kamelets make Camel integration easy

    Apache Camel is a popular open source integration framework based on known Enterprise Integration Patterns (EIPs). Camel is a complete, production-ready framework with a built-in set of patterns you can use in your integration flows. These patterns are based on design patterns and help connect different systems.

    Developers build many frameworks on Apache Camel. This article focuses on Camel K, but several other frameworks exist, such as Camel Kafka and Camel Quarkus.

    Camel K is a lightweight integration framework based on Apache Camel that runs natively on Kubernetes to create serverless and microservice architectures. Camel K allows you to write configuration instructions in the YAML format. The YAML file is known as a Kamelet. Any Kubernetes cluster can deploy a Kamelet as a resource.

    An example of a simple Kamelet follows:

    apiVersion: camel.apache.org/v1alpha1
    kind: KameletBinding
    metadata:
     name: integration
    spec:
     source:
      ref:
      apiVersion: camel.apache.org/v1alpha1
      name: aws-ddb-streams-source
      kind: Kamelet
    sink:
     ref:
      apiVersion: camel.apache.org/v1alpha1
      name: pulsar-sink
      kind: Kamelet

    Kamelets make it easy to exploit the power of Camel K without previous knowledge of that tool. Kamelets are integration snippets with connectors, in the form of sources and sinks, that allow you to connect to external systems using a simplified interface that hides the details of a connection.

    4 Advantages of Kamelets

    Developers are turning to Kamelets for several reasons:

    1. Kamelets simplify and streamline the integration of services into Kubernetes.
    2. You can employ Camel's powerful integration through a Kamelet without any prior knowledge of Camel.
    3. Kamelets offer connectors for event-driven applications. Events are becoming increasingly important, particularly with microservices. As event-driven applications spread, many organizations and developers have begun to use Apache Kafka and Knative as the backbone for connecting all of the systems' applications.
    4. Kamelets make it easy to reuse code for different use cases.

    3 Types of Kamelets

    Kamelets are classified into three types:

    1. Source: Consumes data from an external system into your platform.
    2. Sink: Sends data to an external system or performs an action on the data.
    3. Action: Performs an intermediate step: For example, an action can convert an event to a PDF file before it is saved to a sink.

    You can use a sink or a source to listen to or trigger several types of events, like a channel or a broker. For example, a Kafka channel can be directly connected to a JMS broker using Kamelets. In another example, the Aws-ddb-streams-source can take data from an Amazon DynamoDB database, and the pulsar-sink sink could then store this data elsewhere.

    Advanced features of Kamelets

    • KameletBindings provide a source and a sink as a pair.
    • You can store Kamelets in a catalog, similar to a GitHub repository. Kaoto is a catalog provided by my team. Kaoto is a free, open-source tool that provides a simple integration framework based on Apache Camel, making it easier to visualize your integrations and create Kamelets.

    Summary

    Kamelets advanced features make it easy to utilize Camel K. You can connect to external systems using a simplified interface that hides connection details. There are many advantages to using Kamelets for application integration. Learn more by reviewing the Kaoto catalog. Feel free to comment below. We welcome your feedback.

    Last updated: October 20, 2023

    Related Posts

    • Design event-driven integrations with Kamelets and Camel K

    • Tracking COVID-19 using Quarkus, AMQ Streams, and Camel K on OpenShift

    • Six reasons to love Camel K

    • Event-driven serverless applications with Camel K

    • Sending a telegram with Apache Camel K and Visual Studio Code

    Recent Posts

    • Preventing GPU waste: A guide to JIT checkpointing with Kubeflow Trainer on OpenShift AI

    • How to manage TLS certificates used by OpenShift GitOps operator

    • Configure a split disk on OpenShift Container Platform

    • Red Hat Enterprise Linux 10.2 and 9.8: Top features for developers

    • What GPU kernels mean for your distributed inference

    What’s up next?

    Learn Camel K basics with us! We will teach you how to use a lightweight framework for writing integrations.

    Learn by doing
    Red Hat Developers logo LinkedIn YouTube Twitter Facebook

    Platforms

    • Red Hat AI
    • Red Hat Enterprise Linux
    • Red Hat OpenShift
    • Red Hat Ansible Automation Platform
    • See all products

    Build

    • Developer Sandbox
    • Developer tools
    • Interactive tutorials
    • API catalog

    Quicklinks

    • Learning resources
    • E-books
    • Cheat sheets
    • Blog
    • Events
    • Newsletter

    Communicate

    • About us
    • Contact sales
    • Find a partner
    • Report a website issue
    • Site status dashboard
    • Report a security problem

    RED HAT DEVELOPER

    Build here. Go anywhere.

    We serve the builders. The problem solvers who create careers with code.

    Join us if you’re a developer, software engineer, web designer, front-end designer, UX designer, computer scientist, architect, tester, product manager, project manager or team lead.

    Sign me up

    Red Hat legal and privacy links

    • About Red Hat
    • Jobs
    • Events
    • Locations
    • Contact Red Hat
    • Red Hat Blog
    • Inclusion at Red Hat
    • Cool Stuff Store
    • Red Hat Summit
    © 2026 Red Hat

    Red Hat legal and privacy links

    • Privacy statement
    • Terms of use
    • All policies and guidelines
    • Digital accessibility

    Chat Support

    Please log in with your Red Hat account to access chat support.