How the IBM Cloud Private Demo Helped me Understand Microservices and Kubernetes in 15 Minutes

Jesse’s Big Data Adventures
5 min readNov 1, 2017

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A few weeks ago, I took a look at the Lagom Reactive Platform for microservices. Although microservices is a hugely popular topic in DevOps and Big Data now, I was honestly a bit intimidated by the prospect of managing containers on a large scale. Technologies like Kubernetes claim to make container management easy, but I was a bit hesitant to try it out.

Fortunately, Paul Czarkowski wrote a great tutorial on Deploying a Lagom app to IBM Cloud Private. The deployment process was easy and drew me in.

$ git clone https://github.com/IBM/deploy-ibm-cloud-private.git

$ cd deploy-ibm-cloud-private

$ cd deploy/helm

$ helm repo add incubator https://kubernetes-charts-incubator.storage.googleapis.com

$ helm dependency update

$ helm install -n chirper . — values examples/ibm-cloud-private/values.yaml

NAME: chirper

From this short example, I understood that Kubernetes Helm really does handle the details of managing Kubernetes resources.

I’m just noticing the big IBM Cloud Private announcement coming out tonight. If you’re already working with IBM applications like WebSphere/DB2 apps and are looking for ways to containerize them, IBM provides good resources for doing so. Here are two immediate starting points:

Using the Transformation Advisor on IBM Cloud Private — The Transformation Advisor is a free developer tool to help you quickly evaluate on-premise Java EE apps for deployment to the cloud

Transform traditional WebSphere apps to WebSphere Liberty on IBM Cloud Private by using Kubernetes — Includes access a free trial of IBM Cloud Private

Flush with confidence that there’s an easy way to understand these difficult concepts, I took a look at the IBM Cloud Private demo to deploy a cloud-native application in Kubernetes using a nice web-based GUI. I’ll walk you through this 10 minute demo and explain what I learned.

URL:

https://www.ibm.com/cloud/garage/demo/try-private-cloud-install-an-app

The demo is hands-on and comes with an awesome sidebar on the right that explains all the steps.

As I work out of the glorious city of San Francisco, I selected the Dallas data center.

I logged in. It’s username admin and password admin

After logging in, I’m presented with a beautiful dashboard.

Using the drop-down menu in the upper left, I selected System.

Adding a new repository is just a simple click.

The new repository is set up from the URL of a pre-defined set of resources.

After adding the repository, it appeared in my list of repositories.

In the main left menu, I selected App Center.

I then selected bluecompute-ce.

There’s a minimal configuration. In my case, I just checked, global.persistence.enabled. That’s it!

I then verified that the new app was deployed in the App Center.

The Workloads/Application screen shows the workloads deployed on the cluster. Each application consists of several microservices. Wow, so easy!

Clicking on the default-bluecompute-ce-web application opens up more details.

Clicking on access http opens up a new browser window.

And there it is!

I’ve deployed a scalable microservices application. So easy, so fast.

The catalog is fun to use.

Summary

Playing around with the demo store was not only easy, it also made me reflect that technology tools like the IBM Cloud Private often help us to leapfrog past hurdles. Although I’m still intimidated by the word “cluster” and Kubernetes still makes me a bit anxious that I’ll need to dive into deep tech and look at log files, I now understand that I can dive into microservices quickly, get a proof of concept working, then learn more as I progress.

Learning by walking through hands-on demos is a great way to understand concepts and get a feel for how technology works. If you want to get a better understanding of microservices, I recommend you give the IBM Cloud Private “Store Catalog” demo a look.

https://www.ibm.com/cloud/garage/demo/try-private-cloud-install-an-app

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Jesse’s Big Data Adventures

Exploring the potential of blockchain and big data. Trying out blockchain technologies, big data infrastructure, visualization, and storage technology.