HPE GreenLake for Private Cloud Enterprise includes powerful DevOps tools
that help streamline the software delivery process,
reducing risk, and improving resource utilization and application performance.
Let’s configure automated, continuous deployment
of a container-based application onto our private cloud
and enable developer teams to quickly view the automatically deployed
application via cloud shell.
From the HPE GreenLake Dashboard, signed in as a DevOps Admin,
begin by clicking on the HPE GreenLake for Private Cloud Enterprise tile.
From the HPE GreenLake for Private Cloud Enterprise dashboard,
Let’s configure automated, continuous deployment
From the HPE GreenLake for Private Cloud Enterprise dashboard,
let’s select DevOps.
Now that we’ve created the project, the next step is to define the source artifacts.
HPE GreenLake for Private Cloud Enterprise has support for GitHub
as the CI source so we’ll connect the GitHub code repo to this project.
Click on the Pipeline tab and then Create pipeline.
We will give the pipeline a name and select conditions for the pipeline
to be automatically triggered
based on a change the contributor makes in their code.
We’ll select Detect update to Helm Chart as the trigger type.
Drop down the helm chart location, in this demo,
GitHub, the GitHub account, the GitHub repository.
From here we can set the Trigger source to be a branch or release.
If we were to choose the branch trigger,
as a new change is committed to the "main” branch,
the change is detected automatically,
and the deployment pipeline is deployed onto the selected
HPE GreenLake for Private Cloud Enterprise cluster.
In this demo, we will choose release.
An automated continuous deployment pipeline will be created
where we can either select any release version or select the "latest" tag.
When the "latest" tag is selected,
then whenever a new release cut happens in the repository,
the latest versioned resources will be deployed in the target cluster.
Lastly input the helm chart path and select next.
Select which cluster from our HPE GreenLake for Private Cloud Enterprise
environment we’ll deploy to.
We can select the deployment target to be a development cluster
or we can choose a different active environment, like a production cluster.
Once that's set up, it creates the pipeline
and will initially run the pipeline to setup the helm chart so it's defined
and able to run that particular artifact.
The administrator or contributor can easily drill down into the pipeline
and view the logs and how the pipelines are running through the DevOps UI
or through the cloud shell.
Cloud shell is an interactive shell environment for private cloud
that lets developers manage their projects
and resources from their web browser.
Once the cloud shell session is ready, execute echo $KUBECONFIG.
The KUBECONFIG environment variable gives the path to the kubeconfig
for the deployment target cluster,
copy the file contents in the path
to another file and set the current context to the target cluster context.
Run kubectl command to view current deployment pods,
here we see one running.
Within GitHub we update the replicate count in the deployment helm chart to two
and create a new release.
We complete this by creating a new tag,
giving it a release title,
generating release notes...
and publishing the release.
This will trigger the pipeline to run
and the number of pod instances will increase to two.
As a new change is committed to the release,
the change is detected automatically,
and the deployment pipeline is deployed onto the selected
HPE GreenLake for Private Cloud Enterprise cluster.
Let’s run the kubectl command again in cloud shell
to view the new application pod.
We can now see two application pods running for the configured helm chart.
Help developer teams develop with velocity.
The HPE GreenLake for Private Cloud Enterprise developer experience
increases agility for faster, more consistent code collaboration
with the automation of repetitive tasks
and easy configuration of repeatable workflows.