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Installation Options

This article outlines the various installation methods and modes that are available for customer selection.


ItemEmbedded ClusterExisting Cluster
DescriptionEstablishes a functional Kubernetes cluster on Linux servers. Subsequently, iceDQ is integrated into the Kubernetes cluster, hence the name “embedded cluster”.iceDQ is installed on a customer-managed dedicated Kubernetes cluster, such as AWS EKS, AKS, or GKE, hence the name “existing cluster”.
When to chooseYour organization either doesn't have Kubernetes services or, if it does have them, the team managing them cannot provide a dedicated cluster for installation.You organization has Kubernetes services, an expert team for managing Kubernetes and can readily provide a dedicated cluster for installation.
Online InstallThe servers have internet access so the customer can use one-line command that downloads packages in real-time and does the installation.The servers have internet access so the customer can use one-line command that downloads packages in real-time and does the installation.
Offline InstallThe servers lack internet access available so the customer must manually download the installation package and transfer it to the servers where the installation will take place.The servers lack internet access available so the customer must manually download the installation package and transfer it to the servers where the installation will take place.

Proof Of Concept Sizing

Below are the different embedded and existing cluster sizing recommendations for running a proof of concept.

  • Functional: You are interested in only verifying the functionality.
  • Performance: You are interested in verifying the functionality as well as performance & scalability.

Embedded Cluster

Functional

  • One machine with 16 vCPUs
  • 32GB of RAM on the machine
  • 850GB+ of SSD space for the machine

Performance

  • One machine (a) with 64 vCPUs for handling engine workload
  • 64GB of RAM for machine (a)
  • Two machines (b & c) with 32 vCPUs for handling application workload
  • 32GB of RAM for machine (b & c)
  • 1TB of SSD space for every machine
info

Please check Embedded Cluster System Requirements for additional pre-requisites


Existing Cluster

Amazon Kubernetes Service (EKS)

If you want to deploy in a dedicated Amazon Kubernetes Service Cluster.

ItemFunctionalPerformance
Cluster SizeSingle Node = 1 Worker NodeMulti Node = 2 Worker Nodes
Instance Sizem5.4xlargem5.8xlarge (each node)
RWO Class Storage750GB EBS1TB EBS (each node)
Load BalancerNetwork Load BalancerNetwork Load Balancer
Database (Optional)RDS PostgresSQL v15+RDS/ Aurora PostgresSQL v15+
Backup Store (Optional)S3S3

Azure Kubernetes Service (AKS)

If you want to deploy in a dedicated Azure Kubernetes Service Cluster.

ItemFunctionalPerformance
Cluster SizeSingle Node = 1 Worker NodeMulti Node = 2 Worker Nodes
Instance SizeStandard_D16ds_v4Standard_D32ds_v4 (each node)
RWO Class Storage750GB CSI1TB CSI (each node)
Load BalancerAzure Load BalancerAzure Load Balancer
Database (Optional)Azure PostgreSQL v15+Azure PostgreSQL v15+
Backup Store (Optional)Azure BlobAzure Blob

Google Kubernetes Service (GKE)

If you want to deploy in a dedicated Azure Kubernetes Service Cluster.

ItemFunctionalPerformance
Cluster SizeSingle Node = 1 Worker NodeMulti Node = 2 Worker Nodes
Instance Sizec3d-standard-16c3d-standard-30 (each node)
RWO Class Storage750GB1TB (each node)
Load BalancerGoogle Load BalancerGoogle Load Balancer
Database (Optional)PostgreSQL v15+PostgreSQL v15+
Backup Store (Optional)Google Cloud StorageGoogle Cloud Storage
info

Please check Existing Cluster System Requirements for additional pre-requisites