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.
Components | Related links |
---|---|
Cloud Pak for Data platform hardware requirements | Review the minimum requirements for a stable installation:
Work with your IBM Sales representative to determine whether you need more resources based on:
In addition, review the following resources:
|
Shared cluster-wide components | Review the hardware requirements for the shared cluster components that you need to install. |
Instance-level prerequisites | Review the hardware requirements for the instance-level prerequisites. |
Services | Review the hardware requirements for the services that you plan to install.
Not all services are supported on all hardware. |
Automatically installed dependencies | Review the hardware requirements for the automatically installed dependencies, such as the common core services. (These components are installed only if you install a service with a dependency on the component.) |
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. If you plan to install Cloud Pak for Data on a highly available cluster, review Highly available deployments.
If high availability is not a requirement for your deployment, you can deploy Cloud Pak for Data on a single node OpenShift (SNO) cluster. If you plan to install Cloud Pak for Data on SNO, review Single node OpenShift deployments.
Highly available deployments
The following requirements are the minimum recommendations for a small, stable deployment of Cloud Pak for Data.
- Sizing your cluster
-
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.
Important: Work with your IBM® Sales representative to size your cluster.The size of your cluster depends on multiple factors.
- The shared components that you need to install.
- The services that you plan to
install.
The sizing requirements for services are available in Services. 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.
- 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 several factors, use measurements from running real workloads with realistic data to size your cluster.
For additional information on sizing your cluster, download the component scaling guidance PDF.
- Choosing a configuration
-
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.
Node role | Hardware | Number of servers | Minimum available vCPU | Minimum memory | Minimum storage |
---|---|---|---|---|---|
Control plane |
|
3 (for high availability) |
4 vCPU per node (This configuration supports up to 24 worker nodes.) |
16 GB RAM per node (This configuration supports up to 24 worker nodes.) |
No additional storage is needed for Cloud Pak for Data. See the Red Hat OpenShift Container Platform documentation for sizing guidance. |
Infra |
|
3 (recommended) | 4 vCPU per node (This configuration supports up to 27 worker nodes.) |
24 GB RAM per node (This configuration supports up to 27 worker nodes.) |
See the Red Hat OpenShift Container Platform documentation for sizing guidance. |
Worker (compute) |
|
3 or more worker (compute) nodes | 16 vCPU per node |
|
300 GB of storage space per node for storing container images locally. If you plan to install the watsonx.ai service, increase the storage to 500 GB per node. See Cloud Pak for Data platform storage requirements for details. |
Load balancer |
|
2 load balancer nodes (For development, test, or proof-of-concept clusters, you can use 1 load balancer node.) |
2 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. A load balancer is required when using three control plane nodes. The load balancer can either be in the cluster or external to the cluster. However, in a production-level cluster, an enterprise-grade external load balancer is recommended. |
- Additional guidance for IBM Power hardware
-
The Cloud Pak for Data control plane supports Power9 and Power10.
To improve performance, it is recommended that you configure Power9 logical partitions to run Power9 compatibility mode, and that you configure Power10 logical partitions to run Power10 compatibility mode.
Not all services support Power. For more information, see Services.
On Power hardware, the maximum supported configuration for each worker node is shown as follows.
- 220 vCPU
- 824 GB RAM
- Additional guidance for s390x hardware
-
Not all services support s390x. For more information, see Services.
Single node OpenShift deployments
You can use single node OpenShift (SNO) if redundancy and scalability are not a concern.
- You are planning a small deployment with a limited number of services
- You want to set up satellite or disconnected deployments that are connected to a larger deployment of Cloud Pak for Data
- You plan to run workloads on remote physical locations
- You want to set up ephemeral instances of Cloud Pak for Data for test pipelines
- You need a cluster for demonstrations, training, or proof-of-concept installations.
- Considerations
- Before you choose an SNO deployment,
ensure that you understand the following limitations of a single node deployment:
- Limited scalability
- SNO is not as scalable as a multi-node deployment. You might experience performance issues if you try to run too many applications on a single node.
- Limited capacity
- SNO has a limited capacity for storage and memory. You might need to upgrade your hardware to accommodate larger workloads.
- Single point of failure
- Because SNO runs on a single node, it is more susceptible to downtime in the event of a hardware failure.
- Limited storage support
- If you want to use SNO, you must use one
of the following types of persistent storage:
- NFS
- Amazon Elastic storage, specifically Amazon Elastic File System and Amazon Elastic Block Store
- Dedicated nodes are not supported
- You cannot use dedicated nodes on an SNO cluster.
- Best practices
- If you decide to proceed with an SNO
deployment, ensure that you adhere to the following best practices:
- Workload planning
- If you plan to run multiple applications on the cluster, ensure that you have sufficient capacity for the workloads that you plan to run. If you run a resource intensive workload, it might prevent other workloads from running on the cluster.
- Backup and recovery
- Implement a robust data protection strategy to help ensure that the system can be recovered quickly in the event of a disaster or system crash. See Backing up and restoring Cloud Pak for Data for information about supported backup methods.
- Sizing your cluster
-
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.
Important: Work with your IBM Sales representative to size your cluster.The size of your cluster depends on multiple factors.
- The services that you plan to
install.
The sizing requirements for services are available in Services. 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.
Best practice: Size your SNO cluster appropriately before deploying any software on the cluster. You will encounter performance issues if you have insufficient hardware. - 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 several factors, use measurements from running real workloads with realistic data to size your cluster.
Best practice: If you plan to run multiple applications on the cluster, ensure that you have sufficient capacity for the workloads that you plan to run. If you run a resource intensive workload, it might prevent other workloads from running on the cluster.
For additional information on sizing your cluster, download the component scaling guidance PDF.
- The services that you plan to
install.
- Choosing a configuration
-
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.
The recommended configuration uses two virtual machines (VMs) that act as:- A bastion node with NFS storage configured
- A worker (compute) node
VM role | Hardware | Minimum available vCPU | Minimum memory | Minimum storage |
---|---|---|---|---|
Bastion node |
|
4 vCPU | 8 GB RAM | Allocate a minimum of 500 GB of disk space. The disk can be:
|
Worker (compute) |
|
32 vCPU | 128 GB RAM | Allocate a minimum of 300 GB of disk space on the node for image storage. See Cloud Pak for Data platform storage requirements for details. |
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. To assess your I/O performance:
- Run the Cloud Pak for Data
storage
performance validation playbook on the cluster where you plan to install Cloud Pak for Data and compare your results with the
recommendations.
The I/O performance requirements for Cloud Pak for Data are based on 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 use a large block (1 GB) with 2 threads.
Ensure that the results of the storage performance validation playbook are comparable to the following recommended minimum values.
- Disk latency (4 KB block with 8 threads)
- For disk latency tests, 11 MB/s has been found to provide sufficient performance.
- Disk throughput (1 GB block with 2 thread)
- For disk throughput tests, 128 MB/s has been found to provide sufficient performance.
To ensure sufficient performance, both requirements should be satisfied; however, this might not be feasible in all environments.
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.
- Complete a proof of concept with representative workloads.If your proof of concept encounters functional issues or performance issues, determine the root cause of the problem to confirm whether the issue is related to I/O performance. You can use the following best practices to help identify potential problems.
Workloads can vary dramatically in terms of complexity and concurrency. As you assess your I/O performance, apply the following information:- If you are unable to satisfy the recommended I/O performance requirements, you run a high risk of encountering performance problems.
- As the gap between your measured I/O performance and the recommended I/O performance widens, you
run an increased risk of performance and functional issues. For example, if disk latency-based
measurement is around or under 2 MB/s, you are likely to have all kinds of performance and
functional issues. In this case, I/O performance should be improved before you proceed.
However, if disk latency-based measurement is approximately 5 MB/s or higher, you can proceed. In this case, continue to monitor workloads closely and consider improving I/O performance.
- As your workloads increase, you can work with your infrastructure or storage vendor to review and improve I/O performance to ensure that it remains sufficient and optimal.
- Run the Cloud Pak for Data
storage
performance validation playbook on the cluster where you plan to install Cloud Pak for Data and compare your results with the
recommendations.
- Encryption with Linux® Unified Key Setup (LUKS2)
- To ensure that your data within Cloud Pak for Data is stored securely, you can encrypt your disks when you install Red Hat OpenShift Container Platform. For more information, see Encrypting and mirroring disks during installation in the Red Hat OpenShift Container Platform documentation:
Instance-level prerequisites
Instance-level prerequisites provide underlying functionality for services. Use the following sections to understand the hardware requirements for:
- IBM Cloud Pak for Data control plane
- IBM Cloud Pak foundational services
For more information, see Instance-level components.
Use the following information to determine whether you have the minimum required resources to install each component on your cluster.
x86-64 hardware
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
IBM Cloud Pak for Data control plane | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements |
Required. The control plane is installed once for each instance of Cloud Pak for Data on the cluster. |
IBM Cloud Pak foundational services | 4 vCPU | 5 GB RAM |
See the Hardware requirements and recommendations for foundational
services in the
IBM Cloud Pak foundational services documentation:
|
Required. The IBM Cloud Pak foundational services are installed once for each instance of Cloud Pak for Data on the cluster. |
IBM Power (ppc64le) hardware
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
IBM Cloud Pak for Data control plane | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements |
Required. The control plane is installed once for each instance of Cloud Pak for Data on the cluster. |
IBM Cloud Pak foundational services | 3 vCPU | 5 GB RAM |
See the Hardware requirements and recommendations for foundational
services in the
IBM Cloud Pak foundational services documentation:
|
Required. The IBM Cloud Pak foundational services are installed once for each instance of Cloud Pak for Data on the cluster. |
Z (s390x) hardware
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
IBM Cloud Pak for Data control plane | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements | The requirements for the control plane are included in the Cloud Pak for Data platform hardware requirements |
Required. The control plane is installed once for each instance of Cloud Pak for Data on the cluster. |
IBM Cloud Pak foundational services | 3 vCPU | 5 GB RAM |
See the Hardware requirements and recommendations for foundational
services in the
IBM Cloud Pak foundational services documentation:
|
Required. The IBM Cloud Pak foundational services are installed once for each instance of Cloud Pak for Data on the cluster. |
Services
Use the following information to determine whether you have the minimum required resources to install each service that you want to use.
x86-64 hardware
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
AI Factsheets |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 1.2 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 300 GB Image storage: Up to 2.42 GB |
Minimum resources for an installation with a single replica per service. |
Anaconda Repository for IBM Cloud Pak for Data |
4 vCPU |
8 GB RAM | 1 TB | 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: 2.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 9 GB RAM |
Persistent storage:This information is not currently available.
Ephemeral storage: 50 GB per vCPU request (SSDs are recommended) Image storage: Up to 31.90 GB |
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 where
emptyDir volumes are created.The recommended location is a partition in
/var/lib. For more information, see Understanding ephemeral storagein the Red Hat
OpenShift documentation:
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. All of the Analytics Engine powered by Apache Spark service instances associated with an instance of Cloud Pak for Data use the same pool of resources. |
Cognos Analytics |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: 9.4 vCPU |
Operator pods:
1 GB RAM Catalog pods: 0.05 GB RAM Operand: 38.5 GB RAM |
Persistent storage:
Ephemeral storage:
Image storage: Up to 26.20 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. 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: 11 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.256 GB RAM Operand: 36 GB RAM |
Persistent storage:
30 GB Ephemeral storage: 37.4 GB Image storage: Up to 13.77 GB |
Minimum resources for an installation with a single replica per service. |
Data Gate |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 2 vCPU per instance |
Operator pods:
0.1 GB RAM Catalog pods: 0.05 GB RAM Operand: 13 GB RAM per instance |
Persistent storage:
50 GB per instance Ephemeral storage: 0.6 - 3.25 GB Image storage: Up to 17.45 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. |
Data Privacy | Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 1 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 3.77 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by IBM Knowledge Catalog. Ephemeral storage: 4.5 GB Image storage: Up to 3.15 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. |
Data Product Hub |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.13 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 0.45 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 4.5 GB Image storage: Up to 2.47 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. |
Data Refinery |
Operator pods:
0.1 vCPU Catalog pods: 0.5 vCPU Operand: 1 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 1 GB RAM Operand: 4 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 2 GB Image storage: Up to 3.78 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. This service is installed when you install IBM Knowledge Catalog or Watson Studio
|
Data Replication |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: 13 vCPU |
Operator pods:
0.512 GB RAM Catalog pods: 0.05 GB RAM Operand: 14 GB RAM |
Persistent storage:
10 GB - 512 GB Ephemeral storage: 22 GB Image storage: Up to 3.91 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. |
DataStage |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 8 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 31 GB RAM |
Persistent storage:
300 GB Ephemeral storage:This information is not currently available. Image storage: Up to 19.72 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.
|
Data Virtualization |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 12 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 38 GB RAM |
Persistent storage:
280 GB total (assuming defaults)
Ephemeral storage: 2.428 - 13GB Image storage: Up to 2.23 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. When you provision the service, you can specify:
|
Db2 |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 8 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 24 GB RAM |
Persistent storage:
540 GB (assuming defaults) Ephemeral storage: 2.2 - 9.7 GB Image storage: Up to 0.64 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 vCPU |
Operator pods:
0.3 GB RAM Catalog pods: 0.2 GB RAM Operand: 66.7 GB RAM |
Persistent storage:
470 GB total (assuming defaults)
Ephemeral storage: 1.4 - 12.2 GB Image storage: Up to 0.40 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. When you provision the service, you can specify:
|
Db2 Data Management Console |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 5 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 19.31 GB RAM |
Persistent storage:
10 GB Ephemeral storage: 7.5 GB Image storage: Up to 5.89 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 Creating a service instance for Db2 Data Management Console from the web client. |
Db2 Warehouse |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: SMP: 7 vCPU MPP: 39 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: SMP: 98 GB RAM MPP: 610 GB RAM |
Persistent storage:
540 GB (assuming defaults) Ephemeral storage: 2.2 - 10.8 GB Image storage: Up to 2.15 GB |
Minimum resources for an installation with a single replica per service. Use dedicated nodes for:
For detail, see Setting up dedicated nodes.
|
Decision Optimization |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.9 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 1.5 GB RAM |
Persistent storage:
12 GB Ephemeral storage: 300 - 6500 MB Image storage: Up to 3.29 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-defined |
Operator pods:
IBM: 0.256 GB RAM Third-party: 0.2 GB RAM Catalog pods: 0.05 GB RAM Operand: User-defined |
Persistent storage:
100 GB Ephemeral storage:This information is not currently available. Image storage: Up to 2.71 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) |
Persistent storage:
2 GB per image pushed Ephemeral storage: 218 - 436 MB Image storage: Up to 2.46 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. 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 cluster. For details, see Installing the service on Apache Hadoop clusters. |
IBM Knowledge Catalog |
|
|
Persistent storage:
900 GB Ephemeral storage:
Image storage: Up to 46.95 GB with all optional components |
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 IBM Knowledge Catalog.
|
IBM Knowledge Catalog Premium |
Operator pods:
0.75 vCPU Catalog pods: 0.01 vCPU Operand: 30 vCPU |
Operator pods:
1.5 GB RAM Catalog pods: 0.05 GB RAM Operand: 78 GB RAM |
Persistent storage:
150 GB Ephemeral storage: 10 GB Image storage: Up to 28.66 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. The service requires one GPU. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
IBM Knowledge Catalog Standard |
Operator pods:
0.75 vCPU Catalog pods: 0.01 vCPU Operand: 25 vCPU |
Operator pods:
1.5 GB RAM Catalog pods: 0.05 GB RAM Operand: 61 GB RAM |
Persistent storage:
150 GB Ephemeral storage: 10 GB Image storage: Up to 28.66 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. The service requires one GPU. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
IBM Match 360 with Watson |
Operator pods:
2 vCPU Catalog pods: 1 vCPU Operand: 28 vCPU |
Operator pods:
2 GB RAM Catalog pods: 2 GB RAM Operand: 97 GB RAM |
Persistent storage:
190 GB Ephemeral storage: 16 GB Image storage: Up to 16.97 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 2 GB RAM |
Persistent storage:
20 GB Ephemeral storage: 900 MB (default) Image storage: Up to 5.47 GB |
Minimum resources for an installation with a single replica per service. |
MANTA Automated Data Lineage |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: 11 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.05 GB RAM Operand: 26 GB RAM |
Persistent storage:
37 GB Ephemeral storage: 5 GB Image storage: Up to 5.26 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. |
MongoDB |
Operator pods:
IBM: 0.1 vCPU Third-party: 0.5 vCPU Catalog pods: 0.01 vCPU Operand: User-defined |
Operator pods:
IBM: 0.256 GB RAM Third-party: 0.2 GB RAM Catalog pods: 0.05 GB RAM Operand: User-defined |
Persistent storage:
100 GB Ephemeral storage: 0.256 GB Image storage: Up to 7.91 GB |
Minimum resources for an installation with a single replica per service. Dedicated nodes are recommended. For details, see Setting up dedicated nodes.
|
OpenPages |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: 6 vCPU |
Operator pods:
2 GB RAM Catalog pods: 0.05 GB RAM Operand: 20 GB RAM |
Persistent storage:
252 GB Ephemeral storage: 10.9 GB Image storage: Up to 6.27 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.
|
Orchestration Pipelines |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 1.4 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 2.625 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 1.3 GB Image storage: Up to 4.31 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. |
Planning Analytics |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 16 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 28 GB RAM |
Persistent storage:
20 GB Ephemeral storage: 50 GB (maximum) Image storage: Up to 30.97 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:
0.3 vCPU Catalog pods: 0.2 vCPU Operand: 16 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.05 GB RAM Operand: 34 GB RAM |
Persistent storage:
200 GB Ephemeral storage: 22 GB Image storage: Up to 16.86 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 Runtimes |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 1 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage:This information is not currently available. Image storage: Up to 51.30 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. |
SPSS Modeler |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.25 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 1 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 3 GB (maximum) Image storage: Up to 9.15 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. |
Synthetic Data Generator |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 10.15 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 42.5 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 100 GB Image storage: Up to 5.76 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. |
Voice Gateway |
Operator pods:
0.2 vCPU Catalog pods: 0.01 vCPU Operand: 2 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8 GB RAM |
Persistent storage:
Not applicable Ephemeral storage: 4 GB Image storage: 3.54 GB |
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 Discovery |
Operator pods:
0.05 vCPU Catalog pods: 0.01 vCPU Operand: 15 vCPU |
Operator pods:
0.1 GB RAM Catalog pods: 0.05 GB RAM Operand: 88 GB RAM |
Persistent storage:
Ephemeral storage: 147 GB Image storage: Up to 76.95 GB |
Starter deployments are sized for demonstration purposes only. Production deployments are
sized for robust use. Be sure to choose the right size for your needs. You cannot change the
deployment type after you install the service. If you need to change it later, you must reinstall.
These values represent the minimum requirements for a Starter deployment. CPUs must support the AVX2 instruction set. Work with IBM Sales to get a more accurate sizing based on your expected workload. All of the Watson Discovery service instances associated with an instance of Cloud Pak for Data use the same pool of resources. Watson Discovery supports only single-zone OpenShift deployments. You cannot install Watson Discovery on a multi-zone deployment. |
Watson Machine Learning |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 6 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.5 GB RAM Operand: 27 GB RAM |
Persistent storage:
150 GB Ephemeral storage:This information is not currently available. Image storage: Up to 139.65 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:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 5 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 13 GB RAM |
Persistent storage:
73 GB Ephemeral storage: 2 GB Image storage: Up to 26.55 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. The service requires at least one GPU. GPU support is limited to
|
Watson OpenScale |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 13.25 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 68 GB RAM |
Persistent storage:
100 GB Ephemeral storage: 13.5 GB Image storage: Up to 35.80 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:
0.3 vCPU Catalog pods: 0.01 vCPU Operand: Speech to Text: 9 vCPU Text to Speech: 6.5 vCPU |
Operator pods:
0.3 GB RAM Catalog pods: 0.05 GB RAM Operand: Speech to Text: 47.7 GB RAM Text to Speech: 16.4 GB RAM |
Persistent storage:
Ephemeral storage: 27 GB Image storage: Up to 90.39 GB |
Minimum resources for an instance with a single replica per service using the default models and voices (US-English). The amount of vCPU, memory, and ephemeral storage that is required increases when you install additional models. Work with IBM Sales to get a more accurate sizing based on your expected workload. CPUs must support the AVX2 instruction set. All of the Watson Speech services service instances associated with an instance of Cloud Pak for Data use the same pool of resources. |
Watson Studio |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 2 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Additional storage is required if you enable Visual Studio Code support. Ephemeral storage: 5 - 10 GB Image storage: Up to 6.91 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. If Data Refinery is not installed, add the vCPU and memory required for Data Refinery to the information listed for Watson Studio. If you enable the Visual Studio Code extension for Watson Studio, you must allocate a minimum of 500-600 MB of storage per user for installed extensions. For details, see To enable Visual Studio Code in Post-installation tasks for the Watson Studio service. |
Watson Studio Runtimes |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: Dictated by the runtimes |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: Dictated by the runtimes |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: Dictated by the runtimes. Image storage: Up to 102.41 GB |
Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:
The following runtimes have additional hardware requirements:
|
watsonx.ai |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 27 vCPU |
Operator pods:
1 GB RAM Catalog pods: 0.05 GB RAM Operand: 665 GB RAM |
Persistent storage:
Varies based on the foundation models that you plan to install. For more information, see Adding foundation models. Ephemeral storage: Varies based on the foundation models that you plan to install. For more information, see Adding foundation models. Image storage: Up to 1.8 TB with all models |
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 requires GPUs. The number of GPUs depends on the models that you plan to run and whether you plan to run multiple models in parallel. For more information, see Adding foundation models. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
watsonx Assistant |
Operator pods:
0.25 vCPU Catalog pods: 0.01 vCPU Operand: 10 vCPU |
Operator pods:
6 GB RAM Catalog pods: 0.05 GB RAM Operand: 110 GB RAM |
Persistent storage:
Ephemeral storage: 30 - 135 GB Image storage: Up to 61.74 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. All of the watsonx Assistant service instances associated with an instance of Cloud Pak for Data use the same pool of resources. Your hardware must meet the following additional requirements:
If you plan to use conversational skills or conversational search features, the service requires a minimum of 2 GPUs for non-HA deployments. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
watsonx.data |
Operator pods:
1 vCPU Catalog pods: 0.01 vCPU Operand: 20 vCPU |
Operator pods:
0.75 GB RAM Catalog pods: 0.05 GB RAM Operand: 62 GB RAM |
Persistent storage:
542 GB Ephemeral storage: 25 GB Image storage: Up to 19.91 GB |
Minimum resources for an installation with a single replica of the Presto engine. If you increase the number of Presto replicas, you need additional vCPU, memory, and ephemeral storage. Work with IBM Sales to get a more accurate sizing based on your expected workload. If Analytics Engine powered by Apache Spark is not installed, add the vCPU and memory required for Analytics Engine powered by Apache Spark to the information listed for watsonx.data. |
watsonx Code Assistant for Red Hat Ansible® Lightspeed |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 5 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8 GB RAM |
Persistent storage:
25 GB Ephemeral storage: 0.266 GB Image storage: Up to 18.61 GB |
Minimum resources for an installation with a single replica per service. The service requires at least two GPUs. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
watsonx Code Assistant for Z |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 5 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8 GB RAM |
Persistent storage:
80 GB Ephemeral storage: 135 MB Image storage: Up to 86.93 GB |
Minimum resources for an installation with a single replica per service. The service requires one GPU. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
watsonx.governance |
Operator pods:
0.1 vCPU
Catalog pods:
0.01 vCPU
Operand:
|
Operator pods:
0.256 GB RAM
Catalog pods:
0.05 GB RAM
Operand:
|
Persistent storage:
Ephemeral storage: 250 MB
Image 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. |
watsonx Orchestrate |
Operator pods:
0.2 vCPU Catalog pods: 0.01 vCPU Operand: 53 vCPU |
Operator pods:
0.512 GB RAM Catalog pods: 0.05 GB RAM Operand: 293 GB RAM |
Persistent storage:
640 GB Ephemeral storage: 12 GB Image storage: Up to 26.36 GB |
Minimum resources for a highly available production deployment. Work with IBM Sales to get a more accurate sizing based on your expected workload. The service requires a minimum of 2 GPUs for non-HA deployments. GPU support is limited to
Restriction: Do not configure NVIDIA Multi-Instance GPU if you plan to install this service.
|
IBM Power (ppc64le) hardware
The following services support Power9 and Power10.
Service | Limitations |
---|---|
Analytics Engine powered by Apache Spark | You cannot use, run, or deploy assets based on R frameworks. |
Watson Machine Learning | You cannot use, run, or deploy:
Not all software specifications are supported on Power hardware. For more information, see Supported machine learning tools, libraries, frameworks, and software specifications |
Watson Studio | You cannot use, run, or deploy:
|
Watson Studio Runtimes |
|
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
Analytics Engine powered by Apache Spark |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 2.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 9 GB RAM |
Persistent storage:This information is not currently available.
Ephemeral storage: 50 GB per vCPU request (SSDs are recommended) Image storage: Up to 31.90 GB |
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 where
emptyDir volumes are created.The recommended location is a partition in
/var/lib. For more information, see Understanding ephemeral storagein the Red Hat
OpenShift documentation:
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. All of the Analytics Engine powered by Apache Spark service instances associated with an instance of Cloud Pak for Data use the same pool of resources. |
Data Refinery |
Operator pods:
0.1 vCPU Catalog pods: 0.5 vCPU Operand: 1 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 1 GB RAM Operand: 4 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 2 GB Image storage: Up to 3.78 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. This service is installed when you install IBM Knowledge Catalog or Watson Studio
|
Decision Optimization |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.9 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 1.5 GB RAM |
Persistent storage:
12 GB Ephemeral storage: 300 - 6500 MB Image storage: Up to 3.29 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. |
Db2 |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 8 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 24 GB RAM |
Persistent storage:
540 GB (assuming defaults) Ephemeral storage: 2.2 - 9.7 GB Image storage: Up to 0.64 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 19.31 GB RAM |
Persistent storage:
10 GB Ephemeral storage: 7.5 GB Image storage: Up to 5.89 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 Creating a service instance for Db2 Data Management Console from the web client. |
Db2 Warehouse |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: SMP: 7 vCPU MPP: 39 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: SMP: 98 GB RAM MPP: 610 GB RAM |
Persistent storage:
540 GB (assuming defaults) Ephemeral storage: 2.2 - 10.8 GB Image storage: Up to 2.15 GB |
Minimum resources for an installation with a single replica per service. Use dedicated nodes for:
For detail, see Setting up dedicated nodes.
|
RStudio Server Runtimes |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 1 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage:This information is not currently available. Image storage: Up to 51.30 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 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.5 GB RAM Operand: 27 GB RAM |
Persistent storage:
150 GB Ephemeral storage:This information is not currently available. Image storage: Up to 139.65 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 Studio |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 2 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Additional storage is required if you enable Visual Studio Code support. Ephemeral storage: 5 - 10 GB Image storage: Up to 6.91 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. If Data Refinery is not installed, add the vCPU and memory required for Data Refinery to the information listed for Watson Studio. If you enable the Visual Studio Code extension for Watson Studio, you must allocate a minimum of 500-600 MB of storage per user for installed extensions. For details, see To enable Visual Studio Code in Post-installation tasks for the Watson Studio service. |
Watson Studio Runtimes |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: Dictated by the runtimes |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: Dictated by the runtimes |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: Dictated by the runtimes. Image storage: Up to 102.41 GB |
Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:
|
Z (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
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
Analytics Engine powered by Apache Spark |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 2.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 9 GB RAM |
Persistent storage:This information is not currently available.
Ephemeral storage: 50 GB per vCPU request (SSDs are recommended) Image storage: Up to 31.90 GB |
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 where
emptyDir volumes are created.The recommended location is a partition in
/var/lib. For more information, see Understanding ephemeral storagein the Red Hat
OpenShift documentation:
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. All of the Analytics Engine powered by Apache Spark service instances associated with an instance of Cloud Pak for Data use the same pool of resources. |
Data Gate |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 2 vCPU per instance |
Operator pods:
0.1 GB RAM Catalog pods: 0.05 GB RAM Operand: 13 GB RAM per instance |
Persistent storage:
50 GB per instance Ephemeral storage: 0.6 - 3.25 GB Image storage: Up to 17.45 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. |
Data Refinery |
Operator pods:
0.1 vCPU Catalog pods: 0.5 vCPU Operand: 1 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 1 GB RAM Operand: 4 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 2 GB Image storage: Up to 3.78 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. This service is installed when you install IBM Knowledge Catalog or Watson Studio
|
Db2 |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 8 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 24 GB RAM |
Persistent storage:
540 GB (assuming defaults) Ephemeral storage: 2.2 - 9.7 GB Image storage: Up to 0.64 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 19.31 GB RAM |
Persistent storage:
10 GB Ephemeral storage: 7.5 GB Image storage: Up to 5.89 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 Creating a service instance for Db2 Data Management Console from the web client. |
Db2 Warehouse |
Operator pods:
0.5 vCPU Catalog pods: 0.01 vCPU Operand: SMP: 7 vCPU MPP: 39 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: SMP: 98 GB RAM MPP: 610 GB RAM |
Persistent storage:
540 GB (assuming defaults) Ephemeral storage: 2.2 - 10.8 GB Image storage: Up to 2.15 GB |
Minimum resources for an installation with a single replica per service. Use dedicated nodes for:
For detail, see Setting up dedicated nodes.
|
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) |
Persistent storage:
2 GB per image pushed Ephemeral storage: 218 - 436 MB Image storage: Up to 2.46 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. 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 cluster. For details, see Installing the service on Apache Hadoop clusters. |
Watson Machine Learning |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 6 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.5 GB RAM Operand: 27 GB RAM |
Persistent storage:
150 GB Ephemeral storage:This information is not currently available. Image storage: Up to 139.65 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: 13.25 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 68 GB RAM |
Persistent storage:
100 GB Ephemeral storage: 13.5 GB Image storage: Up to 35.80 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Additional storage is required if you enable Visual Studio Code support. Ephemeral storage: 5 - 10 GB Image storage: Up to 6.91 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. If Data Refinery is not installed, add the vCPU and memory required for Data Refinery to the information listed for Watson Studio. If you enable the Visual Studio Code extension for Watson Studio, you must allocate a minimum of 500-600 MB of storage per user for installed extensions. For details, see To enable Visual Studio Code in Post-installation tasks for the Watson Studio service. |
Watson Studio Runtimes |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: Dictated by the runtimes |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: Dictated by the runtimes |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: Dictated by the runtimes. Image storage: Up to 102.41 GB |
Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:
|
Automatically installed dependencies
Automatically installed dependencies provide underlying functionality for services. Use the following sections to understand the hardware requirements for:
- Common core services
- Db2 as a service
- Db2U
Use the following information to determine whether you have the minimum required resources to install each component on your cluster.
x86_64 hardware
Service | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
Canvas |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.15 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: .0.6 GB RAM |
Persistent storage:
Uses the persistent storage provisioned by the common core services. Ephemeral storage: 0.02 GB Image storage: Up to 1.29 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Common core services |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 11 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 18.3 GB RAM |
Persistent storage:
500 GB Ephemeral storage: 100 GB Image storage: Up to 20.75 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Db2 as a service |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 0.8 GB RAM |
Persistent storage:
Not applicable Ephemeral storage: 0.5 GB Image storage: Up to 0.64 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Db2U |
Operator pods:
0.6 vCPU Catalog pods: 0.01 vCPU Operand: Not applicable. |
Operator pods:
0.7 GB RAM Catalog pods: 0.05 GB RAM Operand: Not applicable. |
Persistent storage:
Not applicable Ephemeral storage: 0.5 GB Image storage: Up to 40.32 GB |
Automatically installed by services that require it. Depending on the services that you install, the operands for this software might be installed multiple times in each Red Hat OpenShift project where Cloud Pak for Data is installed. The operator is installed once per instance of Cloud Pak for Data. The operands are generated by the services that have a dependency on Db2U. For a list of services that have a dependency on Db2U, see Service software requirements. |
Power (ppc64le) hardware
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
Common core services |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 11 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 18.3 GB RAM |
Persistent storage:
500 GB Ephemeral storage: 100 GB Image storage: Up to 20.75 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Db2 as a service |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 0.8 GB RAM |
Persistent storage:
Not applicable Ephemeral storage: 0.5 GB Image storage: Up to 0.64 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Db2U |
Operator pods:
0.6 vCPU Catalog pods: 0.01 vCPU Operand: Not applicable. |
Operator pods:
0.7 GB RAM Catalog pods: 0.05 GB RAM Operand: Not applicable. |
Persistent storage:
Not applicable Ephemeral storage: 0.5 GB Image storage: Up to 40.32 GB |
Automatically installed by services that require it. Depending on the services that you install, the operands for this software might be installed multiple times in each Red Hat OpenShift project where Cloud Pak for Data is installed. The operator is installed once per instance of Cloud Pak for Data. The operands are generated by the services that have a dependency on Db2U. For a list of services that have a dependency on Db2U, see Service software requirements. |
Z (s390x) hardware
Software | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
Common core services |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 11 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 18.3 GB RAM |
Persistent storage:
500 GB Ephemeral storage: 100 GB Image storage: Up to 20.75 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Db2 as a service |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 0.3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 0.8 GB RAM |
Persistent storage:
Not applicable Ephemeral storage: 0.5 GB Image storage: Up to 0.64 GB |
Automatically installed by services that require it. Depending on the services that you install, this software is installed once in each Red Hat OpenShift project where Cloud Pak for Data is installed. For details, see Service software requirements. |
Db2U |
Operator pods:
0.6 vCPU Catalog pods: 0.01 vCPU Operand: Not applicable. |
Operator pods:
0.7 GB RAM Catalog pods: 0.05 GB RAM Operand: Not applicable. |
Persistent storage:
Not applicable Ephemeral storage: 0.5 GB Image storage: Up to 40.32 GB |
Automatically installed by services that require it. Depending on the services that you install, the operands for this software might be installed multiple times in each Red Hat OpenShift project where Cloud Pak for Data is installed. The operator is installed once per instance of Cloud Pak for Data. The operands are generated by the services that have a dependency on Db2U. For a list of services that have a dependency on Db2U, see Service software requirements. |