Part 3 of tutorial series OpenShift 4 and Service Mesh will show you how to create a Gateway and a VirtualService, so external traffic actually reaches your Mesh. It also provides an example script to run some curl in a loop.
Configure Gateway and VirtualService Example
With the microservices deployed during Issue #2, it makes sense to test the access somehow. In order to bring traffic into the application a Gateway object and a VirtualService object must be created.
The Gateway will be the entry point which forward the traffic to the istio ingressgateway
Get all istio-io related objects of your project. These objects represent the network objects of Service Mesh, like Gateway, VirtualService and DestinationRule (explained later)
oc get istio-io -n tutorial
NAME HOST AGE
destinationrule.networking.istio.io/recommendation recommendation 3d21h
NAME AGE
gateway.networking.istio.io/ingress-gateway 4d15h
NAME GATEWAYS HOSTS AGE
virtualservice.networking.istio.io/ingress-gateway [ingress-gateway] [*] 4d15h
Create some example traffic
Before we start, lets fetch the default route of our Service Mesh:
export GATEWAY_URL=$(oc -n istio-system get route istio-ingressgateway -o jsonpath='{.spec.host}')
This should return: istio-ingressgateway-istio-system.apps.<clustername>
Now, let’s create a shell script to run some curl commands in a loop and can be easily reused for other scenarios:
#!/bin/bash
numberOfRequests=$1
host2check=$2
if [ $# -eq 0 ]; then
echo "better define: <script> #ofrequests hostname2check"
echo "Example: run.sh 100 hello.com"
let "numberOfRequests=100"
else
let "i = 0"
while [ $i -lt $numberOfRequests ]; do
echo -n "# $i: "; curl $2
let "i=$((i + 1))"
done
fi
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):
Your organization wants to use an external/public Helm chart
You want to override the Helm values with your own local values
You don’t want to clone the Helm chart locally as well because that would lead to duplication and you would need to monitor it manually for upstream changes.
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:
Installing the logging operator into the namespace openshift-logging
Installing the Loki operator into the namespace openshift-operators-redhat
Creating a new BackingStore and BucketClass
Generating the Secret for Loki to authenticate against the object storage
Configuring the LokiStack resource
Configuring the ClusterLogging resource
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.
Thomas Jungbauer
( Lastmod: 2024-05-05 )
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2 min read