Camel K and Serverless in Action

When to use them As organizations move workloads to containers and the cloud the need to utilize resources optimally is ever important. Serverless technology allows dynamic allocation of resources as needed ensuring no under or over provisioning. This is particularly useful for workloads that run periodically or see spikes. Apache Camel is a widely used Java integration framework that in the latest major version begins to utilize serverless technology. In this session, attendees will get an introduction to serverless technology and Apache Camel. They will learn how Camel K utilizes it to run natively on Kubernetes platforms as well as how to get started with the technologies. Attendees will also see a live demo of Camel K and serverless in action.

YouTube: https://youtu.be/6BlLPUP0eJE

Transcript

1. Mary Cochran
   Camel K and
   Serverless
   Senior App Dev Solutions Architect
   

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2. Camel
   OpenShift Commons
   

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3. 3
   PATTERN BASED INTEGRATION
   300
   COMPONENTS
   Batch, messaging,
   web services, cloud,
   APIs, and more ...
   BUILT-IN DATA
   TRANSFORMATION
   JSON, XML, HL7,
   YAML, SOAP, Java,
   CSV, and more ...
   INTUITIVE
   ROUTING
   Develop
   integrations quickly
   in Java or XML.
   ENTERPRISE
   INTEGRATION
   PATTERNS
   Build integrations
   using enterprise best
   practices.
   Create, connect,
   and compose APIs
   with ease.
   NATIVE REST
   SUPPORT
   Apache Camel, a powerful pattern-based integration engine with a comprehensive
   set of connectors and data formats to tackle any integration problem.
   

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5. Integration Patterns
   Split
   orders
   Send
   each order
   to it’s
   process service
   Electronics
   Others
   Aggregator
   Normalizer
   Content Enricher
   Resequencer
   

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6. Camel Routes
   from("file:data/inbox")
   .to("jms:queue:order");
   
   
   
   
   Java DSL
   XML DSL
   

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7. 7
   from("file:inbox")
   .split(body().tokenize("\n"))
   .marshal(customToXml)
   .to("activemq:queue:line");
   

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8. Quarkus
   OpenShift Commons
   

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9. Differentiators
   9
   Live coding
   Unified configuration
   Developer joy
   Over 90 extensions
   “Powered by Quarkus” applications
   Best of breed libraries and standards
   Tailors your app for HotSpot & GraalVM
   Fast boot time and low RSS memory
   Serverless fit
   Container first
   Combines blocking and non-blocking
   Built-in event bus
   Unifies imperative and reactive
   “Quarkus has introduced a new paradigm that puts things upside down on the way things are run under the covers - supporting native, all
   reflection done at compile time and not runtime is just amazing!” - Talkdesk
   Compared to traditional Java stack
   ● 1/10 RAM usage
   ● 300x faster startup time
   

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10. 10
    A cohesive platform for optimized developer joy:
    ● Based on standards and more
    ● Unified configuration
    ● Live coding
    ● Streamlined code for the 80% common usages,
    flexible for the 20%
    ● No hassle native executable generation
    Developer Joy
    “Our developers used to wait 2 to 3 mins to see their changes. Live coding does away with this.”
    

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11. 11
    Container First
    REST + CRUD
    Quarkus + GraalVM 0.055 Seconds
    Quarkus + OpenJDK 2.5 Seconds
    Traditional Cloud-Native Stack 9.5 Seconds
    Time to first response
    REST + CRUD
    Quarkus +
    GraalVM
    35 MB
    Quarkus +
    OpenJDK
    130 MB
    Traditional
    Cloud-Native Stack
    218 MB
    “We went from 1-min startup times to 400 milliseconds”
    

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12. Camel K
    OpenShift Commons
    

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13. 13
    What is Apache Camel K?
    A lightweight integration platform based on Apache Camel,
    born on Kubernetes, with serverless superpowers.
    Based on operator-sdk
    A community-driven project
    A subproject of Apache Camel started on August 31st, 2018
    https://github.com/apache/camel-k
    http://camel.apache.org
    

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14. 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.
    

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15. 15
    Source:https://camel.apache.org/projects/
    Apache Camel 3 Projects
    APACHE CAMEL KAFKA CONNECTORS
    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
    

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16. 16
    Performance
    Lower is better :)
    

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17. 17
    What?
    1. Create an integration file (Java, Groovy, Kotlin, JS, XML, …)
    $ kamel run integration.groovy
    2. Run it
    3. It runs on
    Kubernetes /
    OpenShift
    // Lookup every second the 'www.google.com' domain
    name and log the output
    from('timer:dns?period=1s')
    .routeId('dns')
    .setHeader('dns.domain')
    .constant('www.google.com')
    .to('dns:ip')
    .log('log:dns');
    Camel DSL, based on
    EIPs...
    Camel K CLI
    (optional)
    

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18. 18
    Architecture
    Dev Environment 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
    

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19. INTERNAL ONLY
    QUARKUS BOOTCAMP
    Service Microservice Serverless
    > Single Purpose
    > Stateless
    > Independently Scalable
    > Automated
    > Single Action
    > Ephemeral
    > Autonomous
    > Loosely-coupled
    Architectural Evolution to Serverless
    f( )
    19
    

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20. kind: Integration
    apiVersion: camel.apache.org/v1alpha1
    metadata:
    name: my-integration
    spec:
    sources:
    - name: source.groovy
    content: |-
    from("knative:channel/a")
    .to("http:my-host/api/path")
    from("knative:channel/a")
    .to("http:my-host/api/path");
    Camel K Operator
    Knative
    profile?
    kind: Service
    apiVersion: serving.knative.dev/v1alpha1
    ...
    yes
    kind: Deployment
    # regular one
    ...
    no
    Camel K Knative Profile
    20
    

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21. 21
    Use Cases For Camel K
    Integration on demand Reusable modules
    Stream processing Filter, converts and aggregates data
    Dynamic resizing capabilities
    Scale up for fluctuations, and 0 to none
    usage
    On Demand
    IoT sensor input
    Bots
    Batch Job
    

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22. Demo Camel K
    OpenShift Commons
    

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23. Serverless and Knative
    OpenShift Commons
    

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24. 24
    ● Serverless is an execution model where the code is
    executed by dynamically allocated resources.
    ● Serverless removes the need for a traditional always-on
    server component from the perspective of the
    developer.
    ● Knative is an open-source Kubernetes-based platform
    to deploy and manage serverless workloads.
    ● Knative is the primary component in Red Hat’s
    OpenShift Functions product (currently in tech preview).
    What is Serverless and
    Knative?
    https://knative.dev
    

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25. 25
    Knative
    Serving Eventing
    Knative defines building blocks for “Serverless” applications
    <>
    Service
    Scale-to-zero and request-driven
    compute
    <>
    Service
    <>
    Service
    Event binding and delivery for
    messaging style integration
    <>
    Channel
    <>
    Channel
    <>
    Channel
    A building block is a CRD with a controller (or “operator”) that manages its lifecycle
    

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26. Install the Operators and
    Deploy
    OpenShift Commons
    

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27. 27
    Kubernetes Namespace
    There’s no container if no one needs it!
    rest().post("/path")
    .to("xx:system1")
    .to("xx:system2")
    300+ components!
    System 1
    System 2
    Knative
    Service
    Knative Serving
    

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28. 28
    Kubernetes Namespace
    A container is created only when needed!
    rest().post("/path")
    .to("xx:system1")
    .to("xx:system2")
    300+ components!
    System 1
    System 2
    Knative
    Service
    Request
    Pod
    Knative Serving
    

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29. Kubernetes Namespace
    rest().post("/path")
    .to("xx:system1")
    .to("xx:system2")
    300+ components!
    System 1
    System 2
    Knative
    Service
    Multiple containers under high load!
    Request
    Pod
    Request
    Request
    Pod
    Pod
    Knative Serving
    29
    

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30. 30
    Serverless Benefits
    Avoid random,
    arbitrary
    prediction
    Lower operational
    cost
    Faster time to
    market
    Reduced
    packaging and
    deployment
    complexity
    Flexible Scalability
    on-demand
    Serverless Camel K
    

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31. 31
    Serverless Operational Benefits
    With Serverless
    Over provisioning
    Time in capacity planning
    IT cost of idle resources
    Under provisioning
    Lost business revenue
    Poor quality of service
    More applications
    Direct line between IT
    costs & business revenue
    NOT Serverless with Serverless
    

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32. Event Driven + Serverless
    Serverless
    f( )
    Microservice
    OpenShift
    KNative
    Streams, AMQ Broker
    Camel K
    Quarkus
    Event Driven
    

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33. Serverless in Action
    OpenShift Commons
    

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34. linkedin.com/company/red-hat
    youtube.com/user/RedHatVideos
    facebook.com/redhatinc
    twitter.com/RedHat
    34
    Red Hat is the world’s leading provider of enterprise
    open source software solutions. Award-winning
    support, training, and consulting services make Red
    Hat a trusted adviser to the Fortune 500.
    Thank you
    

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