Welcome to Yet Another Useless Blog

The following article shall quickly, without huge background information, deploy an Identity Management Server (based on FreeIPA) and connect this IDM to an existing Automation Controller so authentication can be tested and verified based on LDAP.

Working with a GitOps approach is a good way to keep all configurations and settings versioned and in sync on Git. Sensitive data, such as passwords to a database connection, will quickly come around. Obviously, it is not a idea to store clear text strings in a, maybe even public, Git repository. Therefore, all sensitive information should be stored in a secret object. The problem with secrets in Kubernetes is that they are actually not encrypted. Instead, strings are base64 encoded which can be decoded as well. Thats not good …​ it should not be possible to decrypt secured data. Sealed Secret will help here…​

Descheduler is a new feature which is GA since OpenShift 4.7. It can be used to evict pods from nodes based on specific strategies. The evicted pod is then scheduled on another node (by the Scheduler) which is more suitable.

This feature can be used when:

Topology spread constraints is a new feature since Kubernetes 1.19 (OpenShift 4.6) and another way to control where pods shall be started. It allows to use failure-domains, like zones or regions or to define custom topology domains. It heavily relies on configured node labels, which are used to define topology domains. This feature is a more granular approach than affinity, allowing to achieve higher availability.

While Node Affinity is a property of pods that attracts them to a set of nodes, taints are the exact opposite. Nodes can be configured with one or more taints, which mark the node in a way to only accept pods that do tolerate the taints. The tolerations themselves are applied to pods, telling the scheduler to accept a taints and start the workload on a tainted node.

A common use case would be to mark certain nodes as infrastructure nodes, where only specific pods are allowed to be executed or to taint nodes with a special hardware (i.e. GPU).

While noteSelector provides a very easy way to control where a pod shall be scheduled, the affinity/anti-affinity feature, expands this configuration with more expressive rules like logical AND operators, constraints against labels on other pods or soft rules instead of hard requirements.

The feature comes with two types:

One of the easiest ways to tell your Kubernetes cluster where to put certain pods is to use a nodeSelector specification. A nodeSelector defines a key-value pair and are defined inside the specification of the pods and as a label on one or multiple nodes (or machine set or machine config). Only if selector matches the node label, the pod is allowed to be scheduled on that node.

Node Affinity allows to place a pod to a specific group of nodes. For example, it is possible to run a pod only on nodes with a specific CPU or disktype. The disktype was used as an example for the nodeSelector and yes …​ Node Affinity is conceptually similar to nodeSelector but allows a more granular configuration.

Pod scheduling is an internal process that determines placement of new pods onto nodes within the cluster. It is probably one of the most important tasks for a Day-2 scenario and should be considered at a very early stage for a new cluster. OpenShift/Kubernetes is already shipped with a default scheduler which schedules pods as they get created accross the cluster, without any manual steps.

However, there are scenarios where a more advanced approach is required, like for example using a specifc group of nodes for dedicated workload or make sure that certain applications do not run on the same nodes. Kubernetes provides different options:

This series will try to go into the detail of the different options and explains in simple examples how to work with pod placement rules. It is not a replacement for any official documentation, so always check out Kubernetes and or OpenShift documentations.

Every wondered why Ansible Tower does not start downloading required collections when you synchronize a project? Here are the stumbling blocks we discovered so far:

As described at Compliance Operator the Compliance Operator can be used to scan the OpenShift cluster environment against security benchmark, like CIS. Fetching the actual results might be a bit tricky tough.

With OpenShift 4.8 plugins to the oc command are allowed. One of these plugin os oc compliance, which allows you to easily fetch scan results, re-run scans and so on. Let’s install and try it out.

OpenShift comes out of the box with a highly secure operating system, called Red Hat CoreOS. This OS is immutable, which means that no direct changes are done inside the OS, instead any configuration is managed by OpenShift itself using MachineConfig objects. Nevertheless, hardening certain settings must still be considered. Red Hat released a hardening guide (CIS Benchmark) which can be downloaded at https://www.cisecurity.org/.

In this blog post we would like to explore OpenShift / Kubernetes block device handling. We try to answer the following questions:

This quick post shall explain, without any fancy details, how to write an Operator based on Ansible. It is assumed that you know what purpose an Operator has.

As a short summary: Operators are a way to create custom controllers in OpenShift or Kubernetes. It watches for custom resource objects and creates the application based on the parameters in such custom resource object. Often written in Go, the SDK supports Ansible, Helm and (new) Java as well.