With this release of the Infinispan Operator, you can configure explicit CPU and memory limits for individual containers. The defaults are 0.5 CPUs and 512Mi of memory.

The Operator also lets you pass extra JVM options, which is useful for tracking native memory consumption or extra GC logging parameters.

Starting with 0.3.0, credentials are automatically generated for data connector and management users when you instantiate the Infinispan Operator.

The default usernames are developer and admin for the data connector user and management user, respectively.

Generated passwords are stored in Kubernetes Secret instances. You can extract the passwords as follows:

For convenience, the default usernames are also stored in the secret. Using the jq command line tool, you can inspect both the username and password values with a single command:

If you want to set custom credentials for the data connector and management users, create Kubernetes Secret instances as follows:

When using a Credentials type authentication, the referenced secrets must contain username and password fields.

The easiest way to get started with the Infinispan Operator is via the simple tutorial. The Operator is compatible with vanilla Kubernetes environments, such as Minikube, as well as Red Hat OpenShift.

Install the Infinispan Operator directly from the Operator Hub, which is available out of the box on all OpenShift 4 versions. If you’re using a vanilla Kubernertes environment, you might need to install the Operator Lifecycle Manager before you can install via the Operator Hub.

The Infinispan Operator is also included in the community for Kubernetes Operators is available from operatorhub.io.

The Operator configuration does not yet provide all capabilities available for Infinispan servers. We’re working through a process of configuration specification that distills the server configuration into a simple, easy to use, set of configuration options. The current proposal is being discussed openly here.

Infinispan 10 brings a brand new server that’s no longer based on WildFly. The Operator 0.x series will remain focused on Infinispan 9.x server, with Operator 1.x series focusing on Infinispan 10 and onwards.

Cheers, Galder

We’d like to build Infinispan cluster based on Kubernetes hosted locally (using Minikube). We will expose a service and route it to our local machine. Finally, we will use it to put data into the grid.

There are many ways to spin up a local Kubernetes cluster. One of my favorites is Minikube. At first you will need the 'minikube' binary, which can be downloaded from Github releases page. I usually copy it into '/usr/bin' which makes it very convenient to use. The next step is to download 'kubectl' binary. I usually use Kubernetes Github releases page for this. The 'kubectl' binary is stored inside the release archive under 'kubernetes/platforms/<your_platform>/<your_architecture>/kubectl'. I’m using linux/amd64 since I’m running Fedora F23. I also copy the binary to '/usr/bin'.

We are ready to spin up Kubernetes:

This time we’ll focus on automation, so there will be no 'kubectl edit' commands. Below is the yaml file for creating all necessary components in Kubernetes cluster:

Save it somewhere on the disk and execute 'kubectl create' command:

One of the Minikube’s limitations is that it can’t use Ingress API and expose services to the outside world. Thankfully there’s other way - use Node Port service type. With this simple trick we will be able to access the service using '<minikube_ip>:<node_port_number>'. The port number was specified in the yaml file (we could leave it blank and let Kubernetes assign random one). The node port can easily be checked using the following command:

In order to obtain the Kubernetes node IP, use the following command:

Testing is quite simple and the only thing to remember is to use the proper address - <minikube_ip>:<node_port>:

Minikube has all-in-one command to do the clean up:

Kubernetes setup is almost identical to the OpenShift one but there are a couple of differences to keep in mind:

Happy scaling and don’t forget to check if Infinispan formed a cluster (hint - look into the previous post).

We’d like to build an Infinispan cluster on top of OpenShift and expose a Service for it (you may think about Services as Load Balancers). A Service can be exposed to the outside world using Routes. Finally, we will use REST interface to PUT and GET some data from the cluster.

Of course before playing with Infinispan, you will need an OpenShift cluster. There are number of options you can investigate. I will use the simplest path - OpenShift local cluster.

The first step is to download OpenShift Client Tools for your platform. You can find them on OpenShift releases Github page. Once you download and extract the 'oc' binary, make it accessible in your $PATH. I usually copy such things into my '/usr/bin' directory (I’m using Fedora F23). 

Once everything is set and done - spin up the cluster:

Note that you have been automatically logged in as 'developer' and your project has been automatically set to 'myproject'. 

The first step is to create an Infinispan app:

Now you need to modify the Deployment Configuration (use 'oc edit dc/infinispan-server' for this) and tell Infinispan to boot up with Kubernetes' discovery protocol stack by using the proper namespace to look up other nodes (unfortunately this step can not be automated, otherwise a newly created Infinispan node might try to join an existing cluster and this is something you might not want). Here’s my modified Deployment Configuration:

There is one final step - Kubernetes' PING protocol uses the API to look up other nodes in the Infinispan cluster. By default API access is disabled in OpenShift and needs to be enabled. This can be done by this simple command:

Now we can redeploy the application (to ensure that all changes were applied) and scale it out (to 3 nodes):

Now let’s check if everything looks good - you can do it either through the OpenShift web console or by using 'oc get pods' and 'oc logs' commands:

In order to access the Infinispan cluster from the outside world we need a Route:

The newly created Route needs small changes - we need to change the target port to 8080 (this is the REST service). The 'oc edit route/infinispan-server' command is perfect for it. Below is my updated configuration:

You can easily see how to access the cluster by describing the Route:

Now let’s try to play with the data:

Finally, when you are done with experimenting, you can remove everything using 'oc delete' command:

Running Infinispan cluster inside an OpenShift cloud is really simple. Just 3 steps to remember:

Happy scaling!

Openshift v3 has not been released yet, so I’m going to use the code from origin. There are many ways to install Openshift v3, but for simplicity, I’ll run a full multinode cluster locally on top of VirtualBoxes using the provided Vagrant scripts.

Let’s start by checking out and building the sources:

To boot Openshift, it’s a simple matter of starting up the desired number of nodes:

Grab a beer while the cluster is being provisioned, after a while you should be able to see 3 instances running:

The following template defines a 2 node Infinispan cluster communicating via TCP, and discovery done using the JGroups gossip router:

There are few different components declared in this template:

To apply the template via cmd line:

Grab another beer, it can take a while since in this case the docker images need to be fetched on each of the minions from the public registry. In the meantime, to inspect the pods, along with their containers and statuses:

Changing the number of pods (and thus the number of nodes in the Infinispan cluster) is a simple matter of manipulating the number of replicas in the Replication Controller. To increase the number of nodes to 4:

This should take only a few seconds, since the docker images are already present in all the minions.

And this concludes the post, be sure to check other cool features of Openshift in the project documentation and try out other samples.