Deploy the Example to a Kubernetes Cluster
If you have not already installed Cloudflow on a Kubernetes Cluster, please install Cloudflow first.
Once the application is built you need to publish the docker images to a container registry that stores, manages and secures your application images. In this example we will use a Docker Hub registry.
Follow these steps to complete the process of publishing:
Set up the target environment of publishing in your local build process. Create a file named
target-env.sbtin the root of your project folder (the same level where you have
build.sbt). The file needs to have the following 2 lines:
ThisBuild / cloudflowDockerRegistry := Some("docker.io") ThisBuild / cloudflowDockerRepository := Some("<your docker hub username>")
<docker hub username> with your Docker Hub username.
Publish the docker image of your project to the above registry.
Make sure you are logged in with `
docker login --username <your docker hub username>`
and then build and publish the application with
Once the images are successfully published, you will see something like the following as output of
buildApp in your console:
[info] Successfully built and published the following image: [info] docker.io/your-user-name/sensor-data-scala:471-89ca008 [success] Cloudflow application CR generated in /.../sensor-data-scala/target/sensor-data-scala.json [success] Use the following command to deploy the Cloudflow application: [success] kubectl cloudflow deploy /path/to/sensor-data-scala/target/sensor-data-scala.json [success] Total time: 41 s, completed Jun 10, 2020 10:10:10 PM
At this point, the Docker image containing the streamlets has been published to the Docker repository.
sensor-data-scala.json file that the build produces contains the application descriptor.
We use the Cloudflow CLI to deploy that application description to a cluster.
This is quite straightforward and the output of
buildApp actually tells you what command to run for deployment.
If your Docker Hub repository is private, you need to supply the credentials along with the CLI
deploy command, so that Kubernetes can pull the images when the containers are created.
The following example reads a password from a file, and passes it to the
kubectl cloudflow deploy command using STDIN:
$ cat my-dockerhub-password.txt | kubectl cloudflow deploy /path/to/sensor-data-scala/target/sensor-data-scala.json -u <your docker hub username> --password-stdin
If your docker repository is public you can omit credentials with the
--no-registry-credentials flag, which is shown in the following example:
$ kubectl cloudflow deploy /path/to/sensor-data-scala/target/sensor-data-scala.json --no-registry-credentials
If the command goes through you will see the following output:
[Done] Deployment of application `sensor-data-scala` has started.
Once all streamlets are up in their pods, you can see them running using the following command:
$ kubectl cloudflow status sensor-data-scala Name: sensor-data-scala Namespace: sensor-data-scala Version: 484-199a3c1-dirty Created: 2020-06-10 22:28:32 +0200 CEST Status: Running STREAMLET POD READY STATUS RESTARTS http-ingress sensor-data-scala-http-ingress-6f4b677c84-8gtk7 1/1 Running 0 invalid-logger sensor-data-scala-invalid-logger-f76667866-lffmk 1/1 Running 0 metrics sensor-data-scala-metrics-859d9cf974-vrpzs 1/1 Running 0 valid-logger sensor-data-scala-valid-logger-6946746b4b-bpqdc 1/1 Running 0 validation sensor-data-scala-validation-b7f85669d-kkpx9 1/1 Running 0
Note that all streamlets run in a namespace that matches the name of the application.
Congratulations! You have deployed and started your first Cloudflow application.
Now, we are ready to Exercise the example.