![]() ![]() Now add the Solr Operator Helm repository. Now that we have the prerequisites setup, let us install Solr Operator which will let us easily manage a large Solr cluster: You can follow along here, or follow the instructions in the Official Helm release. Once we have installed Solr to our k8s, this will allow us to address the nodes locally. # Edit your /etc/hosts file (`sudo vi /etc/hosts`) and replace the 127.0.0.1 line with:ġ27.0.0.1 localhost dinghy-ping.localhost Install Kubernetes Dashboard (optional) Delete the solrCloud cluster named ‘example’. The most common scalability options for AKS are the cluster autoscaler (automatically adding/removing nodes based on CPU and memory utilization) or the HPA (horizontal pod autoscaler) for your applications to scale in and out based on CPU and memory utilization as well as more advanced metrics. ![]() Create a collection and index some documents. Additionally, there is a KEDA agent that is responsible for managing / activating deployments and scale your workload between 0 and n. Install an Ingress Controller to reach the cluster on localhost. # Inspect that the ingress controller is running by visiting the Kubernetes dashboard # and selecting namespace `ingress-nginx`, or running this command: KEDA, under the hood, works like the many other projects in this area and first and foremost acts as a Custom Metrics API for exposing metrics to the Horizontal Pod Autoscaler. ![]()
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