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Classic Kubernetes/OpenShift offer a feature called NetworkPolicy that allows users to control the traffic to and from their assigned Namespace. NetworkPolicies are designed to give project owners or tenants the ability to protect their own namespace. Sometimes, however, I worked with customers where the cluster administrators or a dedicated (network) team need to enforce these policies.

Since the NetworkPolicy API is namespace-scoped, it is not possible to enforce policies across namespaces. The only solution was to create custom (project) admin and edit roles, and remove the ability of creating, modifying or deleting NetworkPolicy objects. Technically, this is possible and easily done. But shifts the whole network security to cluster administrators.

Luckily, this is where AdminNetworkPolicy (ANP) and BaselineAdminNetworkPolicy (BANP) comes into play.

Lately I came across several issues where a given Helm Chart must be modified after it has been rendered by Argo CD. Argo CD does a helm template to render a Chart. Sometimes, especially when you work with Subcharts or when a specific setting is not yet supported by the Chart, you need to modify it later …​ you need to post-render the Chart.

In this very short article, I would like to demonstrate this on a real-live example I had to do. I would like to inject annotations to a Route objects, so that the certificate can be injected. This is done by the cert-utils operator. For the post-rendering the Argo CD repo pod will be extended with a sidecar container, that is watching for the repos and patches them if required.

The article SSL Certificate Management for OpenShift on AWS explains how to use the Cert-Manager Operator to request and install a new SSL Certificate. This time, I would like to leverage the GitOps approach using the Helm Chart cert-manager I have prepared to deploy the Operator and order new Certificates.

I will use an ACME Letsencrypt issuer with a DNS challenge. My domain is hosted at AWS Route 53.

However, any other integration can be easily used.

During a GitOps journey at one point, the question arises, how to update a cluster? Nowadays it is very easy to update a cluster using CLI or WebUI, so why bother with GitOps in that case? The reason is simple: Using GitOps you can be sure that all clusters are updated to the correct, required version and the version of each cluster is also managed in Git.

All you need is the channel you want to use and the desired cluster version. Optionally, you can define the exact image SHA. This might be required when you are operating in a restricted environment.

Argo CD or OpenShift GitOps uses Applications or ApplicationSets to define the relationship between a source (Git) and a cluster. Typically, this is a 1:1 link, which means one Application is using one source to compare the cluster status. This can be a limitation. For example, if you are working with Helm Charts and a Helm repository, you do not want to re-build (or re-release) the whole chart just because you made a small change in the values file that is packaged into the repository. You want to separate the configuration of the chart with the Helm package.

The most common scenarios for multiple sources are (see: Argo CD documentation):

This small article describes three different ways with a working example and tries to cover the advantages and disadvantages of each of them. They might be opinionated but some of them proved to be easier to use and manage.

OpenShift Logging is one of the more complex things to install and configure on an OpenShift cluster. Not because the service or Operators are so complex to understand, but because of the dependencies logging has. Besides the logging operator itself, the Loki operator is required, the Loki operator requires access to an object storage, that might be configured or is already available.

In this article, I would like to demonstrate the configuration of the full stack using an object storage from OpenShift Data Foundation. This means:

All steps will be done automatically. In case you have S3 storage available, or you are not using OpenShift Data Foundation, the setup will be a bit different. For example, you do not need to create a BackingStore or the Loki authentication Secret.

MinIO is a simple, S3-compatible object storage, built for high-performance and large-scale environments. It can be installed as an Operator to Openshift. In addition, to a command line tool, it provides a WebUI where all settings can be done, especially creating and configuring new buckets. Currently, this is not possible in a declarative GitOps-friendly way. Therefore, I created the Helm chart minio configurator, that will start a Kubernetes Job, which will take care of the configuration.

Honestly, when I say I have created it, the truth is, that it is based on an existing MinIO Chart by Bitnami, that does much more than just set up a bucket. I took out the bucket configuration part, streamlined it a bit and added some new features, which I required.

This article shall explain how to achieve this.

Today I want to demonstrate the deployment and configuration of Advanced Cluster Security (ACS) using a GitOps approach. The required operator shall be installed, verified if it is running and then ACS shall be initialized. This initialization contains the deployment of several components:

Let’s start …​