
Create an Azure Kubernetes Service cluster and configure node pools for up to 100 nodes. Enable system assigned managed identity for Azure Container Registry access and RBAC.
Hint: the helm command arguments changes depends the version of the mongodb installed. Make sure to run the command "helm show chart bitnami/mongodb" and check the version of the mongodb, and check the documentation for the updated args names "https://hub.helm.sh/charts/bitnami/mongodb".
For example, Authentication parameters are reorganized: mongodbUsername, mongodbPassword and mongodbDatabase are now auth.username, auth.password, auth.database
Clone the GitHub projects, install git, build images with Azure Container Registry, and push the rating web and rating API images to the registry.
Deploy and verify the rating api in a Kubernetes cluster with the rating app namespace, and resolve image pull issues by granting access to Azure Container Registry via role assignment.
This is a hand’s on workshop for implementing state of the art end-to-end microservice docker based architecture using k8s on top of Azure Kubernetes Service [AKS]. The workshop will takes you through the steps of creating a Kubernetes cluster, deploying a Mongo DB & microservices-based application, load balancing and securing inbound traffic, scaling option in aks and how can you monitor your cluster in production environment.
At the end of this workshop you will understand AKS inside out, and will be able to design and implement production ready Kubernetes clusters.
The K8s cluster will be hosted on AKS and integrated with azure container register for hosting the container images. AKS RBAC and Azure Active directory will be used to authenticate and authorize access to the AKS cluster and Azure monitor will be used to monitor the cluster.
Any application can be hosted on this cluster, but for the sake of this workshop, we will be using a ready-made sample application from github. A rating website.