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OpenShift Cluster Sizing for the Medical Diagnosis Pattern

Table of contents

  1. OpenShift Cluster Sizing for the Medical Diagnosis Pattern
    1. Table of contents
    2. Tested Platforms
    3. General OpenShift Minimum Requirements
      1. Medical Diagnosis Pattern Components
      2. Medical Diagnosis Pattern OpenShift Cluster Size
      3. AWS Instance Types
      4. Azure Instance Types
      5. Google Cloud (GCP) Instance Types

Tested Platforms

The Medical Diagnosis pattern has been tested in the following Certified Cloud Providers.

Certified Cloud Providers 4.8 4.9 4.10 4.11
Amazon Web Services Tested Tested Tested Tested
Google Compute        
Microsoft Azure        

General OpenShift Minimum Requirements

OpenShift 4 has the following minimum requirements for sizing of nodes:

  • Minimum 4 vCPU (additional are strongly recommended).
  • Minimum 16 GB RAM (additional memory is strongly recommended, especially if etcd is colocated on Control Planes).
  • Minimum 40 GB hard disk space for the file system containing /var/.
  • Minimum 1 GB hard disk space for the file system containing /usr/local/bin/.

Medical Diagnosis Pattern Components

Here’s an inventory of what gets deployed by the Medical Diagnosis pattern:

Name Kind Namespace Description
Medical Diagnosis Hub Application medical-diagnosis-hub Hub GitOps management
Red Hat OpenShift GitOps Operator openshift-operators OpenShift GitOps
Red Hat OpenShift Data Foundations Operator openshift-storage Cloud Native storage solution
Red Hat AMQStreams (Apache Kafka) Operator openshift-operators AMQ Streams provides Apache Kafka access
Red Hat OpenShift Serverless Operator - knative-eventing
- knative-serving
Provides access to knative eventing and serving functions

Medical Diagnosis Pattern OpenShift Cluster Size

The Medical Diagnosis pattern has been tested with a defined set of configurations that represent the most common combinations that Red Hat OpenShift Container Platform (OCP) customers are using or deploying for the x86_64 architecture.

The OpenShift cluster for the Medical Diagnosis pattern needs to be sized a bit larger to support the compute and storage demands of OpenShift Data Foundations and other operators that make up the pattern. The above cluster sizing is close to a minimum size for an OpenShift cluster supporting this pattern. In the next few sections we take some snapshots of the cluster utilization while the Medical Diagnosis pattern is running. Keep in mind that resources will have to be added as more developers are working building their applications.

The OpenShift cluster is a standard deployment of 3 control plane nodes and 3 or more worker nodes.

Node Type Number of nodes Cloud Provider Instance Type
Control Plane/Worker 3 Google Cloud n1-standard-8
Control Plane/Worker 3 Amazon Cloud Services m5.2xlarge
Control Plane/Worker 3 Microsoft Azure Standard_D8s_v3

AWS Instance Types

The Medical Diagnosis pattern was tested with the highlighted AWS instances in bold. The OpenShift installer will let you know if the instance type meets the minimum requirements for a cluster.

The message that the openshift installer will give you will be similar to this message

INFO Credentials loaded from default AWS environment variables
FATAL failed to fetch Metadata: failed to load asset "Install Config": [controlPlane.platform.aws.type: Invalid value: "m4.large": instance type does not meet minimum resource requirements of 4 vCPUs, controlPlane.platform.aws.type: Invalid value: "m4.large": instance type does not meet minimum resource requirements of 16384 MiB Memory]

Below you can find a list of the AWS instance types that can be used to deploy the Medical Diagnosis pattern.

Instance type Default vCPUs Memory (GiB) Hub Factory/Edge
      3x3 OCP Cluster 3 Node OCP Cluster
m4.xlarge 4 16 N N
m4.2xlarge 8 32 Y Y
m4.4xlarge 16 64 Y Y
m4.10xlarge 40 160 Y Y
m4.16xlarge 64 256 Y Y
m5.xlarge 4 16 Y N
m5.2xlarge 8 32 Y Y
m5.4xlarge 16 64 Y Y
m5.8xlarge 32 128 Y Y
m5.12xlarge 48 192 Y Y
m5.16xlarge 64 256 Y Y
m5.24xlarge 96 384 Y Y

The OpenShift cluster is made of 3 Control Plane nodes and 3 Workers. For the node sizes we used the m5.4xlarge on AWS and this instance type met the minimum requirements to deploy the Medical Diagnosis pattern successfully.

To understand better what types of nodes you can use on other Cloud Providers we provide some of the details below.

Azure Instance Types

The Medical Diagnosis pattern was also deployed on Azure using the Standard_D8s_v3 VM size. Below is a table of different VM sizes available for Azure. Keep in mind that due to limited access to Azure we only used the Standard_D8s_v3 VM size.

The OpenShift cluster is made of 3 Control Plane nodes and 3 Workers.

Type Sizes Description
General purpose B, Dsv3, Dv3, Dasv4, Dav4, DSv2, Dv2, Av2, DC, DCv2, Dv4, Dsv4, Ddv4, Ddsv4 Balanced CPU-to-memory ratio. Ideal for testing and development, small to medium databases, and low to medium traffic web servers.
Compute optimized F, Fs, Fsv2, FX High CPU-to-memory ratio. Good for medium traffic web servers, network appliances, batch processes, and application servers.
Memory optimized Esv3, Ev3, Easv4, Eav4, Ev4, Esv4, Edv4, Edsv4, Mv2, M, DSv2, Dv2 High memory-to-CPU ratio. Great for relational database servers, medium to large caches, and in-memory analytics.
Storage optimized Lsv2 High disk throughput and IO ideal for Big Data, SQL, NoSQL databases, data warehousing and large transactional databases.
GPU NC, NCv2, NCv3, NCasT4_v3, ND, NDv2, NV, NVv3, NVv4 Specialized virtual machines targeted for heavy graphic rendering and video editing, as well as model training and inferencing (ND) with deep learning. Available with single or multiple GPUs.
High performance compute HB, HBv2, HBv3, HC, H Our fastest and most powerful CPU virtual machines with optional high-throughput network interfaces (RDMA).

For more information please refer to the Azure VM Size Page.

Google Cloud (GCP) Instance Types

The Medical Diagnosis pattern was also deployed on GCP using the n1-standard-8 VM size. Below is a table of different VM sizes available for GCP. Keep in mind that due to limited access to GCP we only used the n1-standard-8 VM size.

The OpenShift cluster is made of 3 Control Plane and 3 Workers cluster.

The following table provides VM recommendations for different workloads.

General purpose Workload optimized        
Cost-optimized Balanced Scale-out optimized Memory-optimized Compute-optimized Accelerator-optimized
E2 N2, N2D, N1 T2D M2, M1 C2 A2
Day-to-day computing at a lower cost Balanced price/performance across a wide range of VM shapes Best performance/cost for scale-out workloads Ultra high-memory workloads Ultra high performance for compute-intensive workloads Optimized for high performance computing workloads

For more information please refer to the GCP VM Size Page.