Hardware requirements
Before you install IBM® Cloud Pak for Data, review the hardware requirements for the control plane, the shared cluster components, and the services that you plan to install.
Cloud Pak for Data platform hardware requirements
You must install Cloud Pak for Data on a Red Hat® OpenShift® Container Platform cluster. For information about the supported versions of Red Hat OpenShift Container Platform, see Software requirements.
It is strongly recommended that you deploy Cloud Pak for Data on a highly available cluster.
The following requirements are the minimum recommendations for a small, stable deployment of Cloud Pak for Data. Use the minimum recommended configuration as a starting point for your cluster configuration. If you use fewer resources, you are likely to encounter stability problems.
The following configuration has been tested and validated by IBM. However, Red Hat OpenShift Container Platform supports other configurations. If the configuration in the following table does not work in your environment, you can adapt the configuration based on the guidance in the Red Hat OpenShift documentation. (Links to the relevant Red Hat OpenShift documentation are available in Software requirements.) In general, Cloud Pak for Data is primarily concerned with the resources that are available on your worker nodes.
- The shared components that you need to install
- The services that you plan to
install
The sizing requirements for services are available in Service hardware requirements. If you install only a few services with small vCPU and memory requirements, you might not need additional resources. However, if you plan to install multiple services or services with large footprints, add the appropriate amount of vCPU and memory to the minimum recommendations below.
- The types of workloads that you plan to run
For example, if you plan to run complex analytics workloads in addition to other resource-intensive workloads, such as ETL jobs, you can expect reduced concurrency levels if you don't add additional computing power to your cluster.
Because workloads vary based on a number of factors, use measurements from running real workloads with realistic data to size your cluster.
Node role | Hardware | Number of servers | Minimum available vCPU | Minimum memory | Minimum storage |
---|---|---|---|---|---|
Master + infra |
|
3 master (for high availability) and 3 infrastructure on the same 3 nodes | 8 vCPU per node | 32 GB RAM per node | No additional storage is needed. For sizing guidance, refer to the Red Hat OpenShift Container Platform documentation. |
Worker/compute |
|
3+ worker/compute nodes | 16 vCPU per node |
|
300 GB of storage space per node for storing container images locally. See Cloud Pak for Data platform storage requirements for details. |
Load balancer |
|
2 load balancer nodes | 4 vCPU per node | 4 GB RAM per node Add another 4 GB of RAM for access restrictions and security control. |
Add 100 GB of root storage for access restrictions and security control. |
- Power® hardware
- Power is supported on the following
versions of Red Hat OpenShift Container Platform:
- Version 4.8
- Version 4.10
The platform supports Power 9 and Power 10, but does not take advantage of Power 10 optimizations.
Not all services support Power. For details, see Service hardware requirements.
On Power hardware the maximum supported configuration for each worker node is:
- 160 vCPU
- 512 GB RAM
- s390x hardware
- s390x is supported only on Red Hat OpenShift Container Platform
Version 4.8.
Not all services support s390x. For details, see Service hardware requirements.
- Load balancer
- A load balancer is required when using three master nodes. The load balancer distributes the traffic load of the master and proxy nodes, securely isolates the master and compute node IP addresses, and facilitates external communication, including accessing the management console and API or making other requests to the master and proxy nodes.
Cluster node settings
The time on all of the nodes must be synchronized within 500 ms.
Some services require additional node settings to run correctly. For information about the node settings and the services that require them, see Changing required node settings. You must change the node settings before you install Cloud Pak for Data.
Disk requirements
To prepare your storage disks, ensure that you have good I/O performance, and prepare the disks for encryption.
- I/O performance
- When I/O performance is not sufficient, services can experience poor performance or cluster
instability, such as functional failures with timeouts. This is especially true when you are running
a heavy workload.
The I/O performance requirements for Cloud Pak for Data are based extensive testing in various cloud environments. The tests validate the I/O performance in these environments. The requirements are based on the performance of writing data to representative storage classes using the following block size and thread count combinations:
- To evaluate disk latency, the I/O tests use a small block (4 KB) with 8 threads
- To evaluate disk throughput, the I/O tests us a large block (1 GB) with 2 threads
To evaluate the storage performance on the cluster where you plan to install Cloud Pak for Data, run the Cloud Pak for Data storage performance validation playbook. Ensure that the results are comparable to the following recommended minimum values:
- Disk latency (4 KB block with 8 threads)
- For disk latency tests, 18 MB/s has been found to provide sufficient performance.
- Disk throughput (1 GB block with 2 thread)
- For disk throughput tests, 226 MB/s has been found to provide sufficient performance.
To ensure sufficient performance, both requirements should be satisfied.
Some storage types might have more stringent I/O requirements. For details, see Storage considerations.
Important: It is recommended that you run the validation playbook several times to account for variations in workloads, access patterns, and network traffic.In addition, if your storage volumes are remote, network speed can be a key factor in your I/O performance. For good I/O performance, ensure that you have sufficient network speed, as described in Storage considerations.
- Encryption with Linux® Unified Key Setup
- To ensure that your data within Cloud Pak for Data is stored securely, you can encrypt your disks. If you use Linux Unified Key Setup-on-disk-format (LUKS), you must enable LUKS when you install Red Hat OpenShift Container Platform. For more information, see Encrypting disks during installation in the Red Hat OpenShift Container Platform documentation.
Service hardware requirements
Use the following information to determine whether you have the minimum required resources to install each service that you want to use.
Service vCPU Memory Storage Notes Anaconda Repository for IBM Cloud Pak for Data 4 vCPU
8 GB RAM 500 GB This service cannot be installed on your Red Hat OpenShift cluster. For details, see the Anaconda installation requirements. Analytics Engine Powered by Apache Spark Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
3 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
7 GB RAMLocal Disk storage (SSDs) on OpenShift nodes. Spark jobs use emptyDir
volumes for temporary storage and shuffling. If your Spark jobs use a lot of disk space for temporary storage or shuffling, make sure that you have sufficient space on the local disk whereemptyDir
volumes are created.On OpenShift 4.6, the recommended location is a partition in /var/lib. For details, see Understanding ephemeral storage.
If you don't have sufficient space on the local disk, Spark jobs might run slowly and some of the executors might evict jobs. A minimum of 50 GB of temporary storage for each vCPU request is recommended.
Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Cognos® Analytics Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
9.3 vCPUOperator pods:
1 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
40 GB RAM- 500 MB for the service
- 2 GB for the smallest instance
Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
When you provision the Cognos Analytics service, you specify the size of the instance.
The information here is for the smallest instance. For other sizes, see Provisioning the Cognos Analytics service.
Cognos Dashboards Operator pods:
0.1 vCPU
Catalog pods:
0.5 vCPU
Operand:
3.125 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.256 GB RAM
Operand:
6.8 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Data Privacy Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
1 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
3.77 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Data Refinery Operator pods:
0.1 vCPU
Catalog pods:
0.5 vCPU
Operand:
1 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
1 GB RAM
Operand:
4 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
This service is installed when you install Watson™ Knowledge Catalog or Watson StudioData Virtualization Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
12 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
38 GB RAM220 GB total (assuming defaults) Head pod:
50 GB (default)
One worker pod:
50 GB (default)
utils:
100 GB
Caching:
10 GB (default)
Scheduling pod:
10 GBMinimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
When you provision the service, you can specify:
- The size of the persistent volume for the head pod
- The size of the persistent volume for the cache
- The number of worker pods
- The size of the persistent volume for the worker pods
DataStage® Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
8 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
31 GB RAM300 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
- Local storage in /var/lib/containers
- Adjust the amount of local storage per node based on the volume of data you are analyzing. Local storage should be approximately 2 times larger than the amount of data you expect the system to process concurrently.
Db2® Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
1.5 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
5.5 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
A dedicated node is recommended for production deployments of Db2. For details, see Setting up dedicated nodes.
Db2 Big SQL Operator pods:
0.2 vCPU
Catalog pods:
0.1 vCPU
Operand:
10.2 vCPUOperator pods:
0.3 GB RAM
Catalog pods:
0.2 GB RAM
Operand:
66.7 GB RAM410 GB total (assuming defaults) Head pod:
200 GB (default)
One worker pod:
200 GB (default)
Scheduling pod:
10 GBMinimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
When you provision the service, you can specify:
- The resources (vCPU and RAM) for the head and worker pods
- The number of worker pods
- The size of the persistent volume for the head pod and worker pods
Db2 Data Gate Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
2 vCPU per instanceOperator pods:
0.1 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
13 GB RAM per instance50 GB per instance Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Db2 Data Management Console Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
5 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
19.31 GB RAM10 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
For information on sizing the provisioned instance, see Provisioning the service.
Db2 Warehouse Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
SMP: 7 vCPU
MPP: 39 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
SMP: 98 GB RAM
MPP: 610 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Use dedicated nodes for:
- Production SMP deployments (recommended)
- MPP deployments (required)
For detail, see Setting up dedicated nodes.
- Development deployment
-
- 1 node for SMP
- 2 nodes for MPP
- Production deployment
-
- 1 node for SMP
- 2-999 nodes for MPP
- Recommended configuration
-
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Decision Optimization Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
0.9 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
1.5 GB RAM12 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
EDB Postgres Operator pods:
IBM: 0.1 vCPU
Third-party: 0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
User-definedOperator pods:
IBM: 0.256 GB RAM
Third-party: 0.2 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
User-defined100 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Execution Engine for Apache Hadoop Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
For each deployment:
0.5 vCPU + (0.5 vCPU * number of Hadoop registrations) + (0.6 vCPU * number of Hadoop jobs run)Operator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
For each deployment:
0.5 GB + (0.5 GB * number of Hadoop registrations) + (0.5 GB * number of Hadoop jobs run)2 GB per image pushed Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Each image that is pushed to the remote Hadoop cluster requires disk space where image tgz file can be stored.
Execution Engine for Apache Hadoop requires an Execution Engine for Hadoop RPM installation on the Apache Hadoop or IBM Spectrum® Conductor cluster. For details, see:Guardium® External S-TAP® Operator pods:
1 vCPU
Catalog pods:
0.01 vCPU
Operand:
0.5 vCPUOperator pods:
0.5 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
0.75 GB RAM1 GB of persistent storage. 1.025 GB of ephemeral storage.
Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
IBM Match 360 with Watson Operator pods:
2 vCPU
Catalog pods:
1 vCPU
Operand:
42 vCPUOperator pods:
2 GB RAM
Catalog pods:
2 GB RAM
Operand:
115 GB RAM190 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Informix® Operator pods:
0.1 vCPU
Catalog pods:
0.1 vCPU
Operand:
2 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
2 GB RAM20 GB Minimum resources for an installation with a single replica per service.
MongoDB Operator pods:
IBM: 0.1 vCPU
Third-party: 0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
User-definedOperator pods:
IBM: 0.256 GB RAM
Third-party: 0.2 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
User-defined100 GB Minimum resources for an installation with a single replica per service.
Dedicated nodes are recommended. For details, see Setting up dedicated nodes.
- Development deployment
- 3 nodes
- Production deployment
- 3 nodes
- Recommended configuration
- Refer to the Ops Manager System Requirements to determine the appropriate
specifications based on your expected workloads.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
OpenPages® Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
4.5 vCPUOperator pods:
2 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
14 GB RAM250 GB When you provision the OpenPages service, you specify the size of the instance and the storage class to use. You also specify whether to use the database that is provided with the OpenPages service or a database that is on an external server. These values represent the minimum resources for OpenPages with a Db2 database on Cloud Pak for Data.
- Using a Db2 database on Cloud Pak for Data
-
OpenPages uses Db2 as a service, which is different from the Db2 service in the services catalog.
You can optionally provision the Db2 database on dedicated nodes. For details, see Provisioning an instance of OpenPages.
- Using a Db2 database outside of Cloud Pak for Data
- If you use a database outside of Cloud Pak for Data, the minimum requirements for vCPUs and memory are lower.
Planning Analytics Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
10 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
22 GB RAM20 GB Work with IBM Sales to get a more accurate sizing based on your expected workload.
Select the size of your instance when you provision Planning Analytics. For details, see Provisioning the Planning Analytics service.
Product Master Operator pods:
0.2 vCPU
Catalog pods:
0.2 vCPU
Operand:
14 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
48 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
RStudio® Server with R 3.6 Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
1 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
8.8 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
SPSS® Modeler Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
0.25 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
1 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Voice Gateway Operator pods:
0.2 vCPU
Catalog pods:
0.01 vCPU
Operand:
2 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
8 GB RAMNot applicable Minimum resources for a system that can provide voice-only support for up to 11 concurrent calls.
Dedicated nodes are recommended for production environments.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Watson Assistant Operator pods:
0.25 vCPU
Catalog pods:
0.01 vCPU
Operand:
20 vCPUOperator pods:
0.6 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
150 GB RAM425 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Your hardware must meet the following additional requirements:- CPUs must have a clock speed of 2.4 GHz or higher
- CPUs must support Linux SSE 4.2
- CPUs must support the AVX2 instruction set
Watson Discovery Operator pods:
0.1 vCPU
Catalog pods:
0.05 vCPU
Operand:
15 vCPUOperator pods:
0.05 GB RAM
Catalog pods:
0.01 GB RAM
Operand:
93 GB RAM508 GB Starter deployments have a single replica per service. Production deployments have multiple replicas per service. CPUs must support the AVX2 instruction set.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Watson Discovery supports only single-zone OpenShift deployments. You cannot install Watson Discovery on a multi-zone deployment.
Watson Knowledge Catalog - Base
-
Operator pods:
0.75 vCPU
Catalog pods:
0.05 vCPU
Operand:
32 vCPU - Data quality
-
Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
11 vCPU - AI Factsheets
-
Operator pods:
Not applicable.
Catalog pods:
Not applicable
Operand:
1 vCPU - Semantic search and lineage
-
Operator pods:
1.5 vCPU
Catalog pods:
0.05 vCPU
Operand:
5 vCPU - Advanced metadata import
-
Operator pods:
0.3 vCPU
Catalog pods:
0.05 vCPU
Operand:
6 vCPU
- Base
-
Operator pods:
4 GB RAM
Catalog pods:
0.2 GB RAM
Operand:
128 GB RAM - Data Quality
-
Operator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
44 GB RAM - AI Factsheets
-
Operator pods:
Not applicable.
Catalog pods:
Not applicable.
Operand:
4 GB RAM - Semantic search and lineage
-
Operator pods:
0.7 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
20 GB RAM - Advanced metadata import
-
Operator pods:
0.6 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
24 GB RAM
900 GB The minimum required resources depend on the features that you install.
If Data Refinery is not installed, add the vCPU and memory required for Data Refinery to the information listed for Watson Knowledge Catalog.
- Local storage in /var/lib/containers
- Adjust the amount of local storage per node based on the volume of data you are analyzing. Local storage should be approximately 2 times larger than the amount of data you expect the system to process concurrently.
- Persistent storage
- The raw size of shared storage depends on the storage class you use. For example, if you use
portworx-shared-gp3
, which has 3 replicas, multiply the storage by the number of replicas.
Watson Knowledge Studio Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
7 vCPUOperator pods:
0.1 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
31 GB RAM360 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Watson Machine Learning Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
6 vCPUOperator pods:
0.5 GB RAM
Catalog pods:
0.5 GB RAM
Operand:
27 GB RAM150 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
AVX2 is recommended but not required for AutoAI experiments.
Watson Machine Learning Accelerator Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
6.5 vCPUOperator pods:
1GB RAM
Catalog pods:
0.05 GB RAM
Operand:
18 GB RAM120 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
GPU support is limited to NVIDIA V100, A100 and T4 GPUs.
Watson OpenScale Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
14 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
72 GB RAM100 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Watson Speech services Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
Speech to Text: 8 vCPU
Text to Speech: 7 vCPUOperator pods:
0.5 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
Speech to Text: 22 GB RAM
Text to Speech: 15 GB RAM900 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
CPUs must support the AVX2 instruction set.
Watson Studio Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
2 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
8.8 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
If Data Refinery is not installed, add the vCPU and memory required for Data Refinery to the information listed for Watson Studio.
Watson Studio Runtimes Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
Dictated by the runtimesOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
Dictated by the runtimesNot applicable Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:- Jupyter Notebooks with Python 3.9
- Jupyter Notebooks with Python 3.9 for GPU
- Jupyter Notebooks with R 3.6
- Jupyter Notebooks with Python 3.9 for GPU
- At least 1 GPU core is required to use this runtime.
The following services support only Power 9:
Service vCPU Memory Storage Notes Watson Machine Learning Accelerator Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
6.5 vCPUOperator pods:
1GB RAM
Catalog pods:
0.05 GB RAM
Operand:
18 GB RAM120 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
GPU support is limited to NVIDIA V100, A100 and T4 GPUs.
The following services support Power 9 and Power 10. However, the services do not take advantage of Power 10 optimizations.
Service vCPU Memory Storage Notes Db2 Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
1.5 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
5.5 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
A dedicated node is recommended for production deployments of Db2. For details, see Setting up dedicated nodes.
Db2 Data Management Console Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
5 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
19.31 GB RAM10 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
For information on sizing the provisioned instance, see Provisioning the service.
Db2 Warehouse Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
SMP: 7 vCPU
MPP: 39 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
SMP: 98 GB RAM
MPP: 610 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Use dedicated nodes for:
- Production SMP deployments (recommended)
- MPP deployments (required)
For detail, see Setting up dedicated nodes.
- Development deployment
-
- 1 node for SMP
- 2 nodes for MPP
- Production deployment
-
- 1 node for SMP
- 2-999 nodes for MPP
- Recommended configuration
-
Work with IBM Sales to get a more accurate sizing based on your expected workload.
- Restriction: The following services have a limited set of features on s390x hardware:
- Watson Machine Learning
- Watson Studio
- Watson Studio Runtimes
For a list of the features that are available on s390x hardware, see Capabilities on IBM Z®
Service vCPU Memory Storage Notes Analytics Engine Powered by Apache Spark Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
3 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
7 GB RAMLocal Disk storage (SSDs) on OpenShift nodes. Spark jobs use emptyDir
volumes for temporary storage and shuffling. If your Spark jobs use a lot of disk space for temporary storage or shuffling, make sure that you have sufficient space on the local disk whereemptyDir
volumes are created.On OpenShift 4.6, the recommended location is a partition in /var/lib. For details, see Understanding ephemeral storage.
If you don't have sufficient space on the local disk, Spark jobs might run slowly and some of the executors might evict jobs. A minimum of 50 GB of temporary storage for each vCPU request is recommended.
Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Data Refinery Operator pods:
0.1 vCPU
Catalog pods:
0.5 vCPU
Operand:
1 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
1 GB RAM
Operand:
4 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
This service is installed when you install Watson Knowledge Catalog or Watson StudioDb2 Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
1.5 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
5.5 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
A dedicated node is recommended for production deployments of Db2. For details, see Setting up dedicated nodes.
Db2 Data Gate Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
2 vCPU per instanceOperator pods:
0.1 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
13 GB RAM per instance50 GB per instance Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Db2 Data Management Console Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
5 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
19.31 GB RAM10 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
For information on sizing the provisioned instance, see Provisioning the service.
Db2 Warehouse Operator pods:
0.5 vCPU
Catalog pods:
0.01 vCPU
Operand:
SMP: 7 vCPU
MPP: 39 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
SMP: 98 GB RAM
MPP: 610 GB RAM200 GB Minimum resources for an installation with a single replica per service.
Use dedicated nodes for:
- Production SMP deployments (recommended)
- MPP deployments (required)
For detail, see Setting up dedicated nodes.
- Development deployment
-
- 1 node for SMP
- 2 nodes for MPP
- Production deployment
-
- 1 node for SMP
- 2-999 nodes for MPP
- Recommended configuration
-
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Execution Engine for Apache Hadoop Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
For each deployment:
0.5 vCPU + (0.5 vCPU * number of Hadoop registrations) + (0.6 vCPU * number of Hadoop jobs run)Operator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
For each deployment:
0.5 GB + (0.5 GB * number of Hadoop registrations) + (0.5 GB * number of Hadoop jobs run)2 GB per image pushed Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Each image that is pushed to the remote Hadoop cluster requires disk space where image tgz file can be stored.
Execution Engine for Apache Hadoop requires an Execution Engine for Hadoop RPM installation on the Apache Hadoop or IBM Spectrum Conductor cluster. For details, see:Watson Machine Learning Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
6 vCPUOperator pods:
0.5 GB RAM
Catalog pods:
0.5 GB RAM
Operand:
27 GB RAM150 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
AVX2 is recommended but not required for AutoAI experiments.
Watson OpenScale Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
14 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
72 GB RAM100 GB Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
Watson Studio Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
2 vCPUOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
8.8 GB RAMNot applicable Minimum resources for an installation with a single replica per service.
Work with IBM Sales to get a more accurate sizing based on your expected workload.
If Data Refinery is not installed, add the vCPU and memory required for Data Refinery to the information listed for Watson Studio.
Watson Studio Runtimes Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
Dictated by the runtimesOperator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
Dictated by the runtimesNot applicable Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:- Jupyter Notebooks with Python 3.9