Scaling¶

Before the deployment of the Denodo Lakehouse Accelerator, you must define in the values.yaml how many Lakehouse Accelerator Workers, presto.numWorkers, will run. But you can scale the Denodo Lakehouse Accelerator later, by increasing or decreasing the number of Lakehouse Accelerator Workers, pod replicas, depending on the workload.

It is strongly recommended to use pod-based scaling together with node-based scaling to coordinate scalability of the pods with the behavior of the nodes in the cluster, since our recommendation is to use one single node for each Lakehouse Accelerator worker. This way, when you need to scale up, the cluster autoscaler can add new nodes, and when scaling down, it can shut down unneeded nodes.

• For node-based scaling in Amazon EKS see Configuring an Autoscaling Denodo Embedded MPP Cluster in EKS.

• For node-based scaling in Azure Kubernetes Service see Configuring an Autoscaling Denodo Embedded MPP Cluster in AKS