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.
x86-64 hardware
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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 7 GB RAM |
Local 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 where
emptyDir 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 vCPU |
Operator pods:
1 GB RAM Catalog pods: 0.05 GB RAM Operand: 40 GB RAM |
|
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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.256 GB RAM Operand: 6.8 GB RAM |
Not 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 3.77 GB RAM |
Not 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 1 GB RAM Operand: 4 GB RAM |
Not 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 Studio
|
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 |
220 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 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:
|
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 |
300 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: 1.5 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 5.5 GB RAM |
200 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 |
410 GB total (assuming defaults)
Head pod:
200 GB (default) One worker pod: 200 GB (default) Scheduling pod: 10 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 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 |
50 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 19.31 GB RAM |
10 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: SMP: 98 GB RAM MPP: 610 GB RAM |
200 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 |
12 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 |
100 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 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.05 GB RAM Operand: 0.75 GB RAM |
1 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 vCPU |
Operator pods:
2 GB RAM Catalog pods: 2 GB RAM Operand: 115 GB RAM |
190 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 |
20 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-defined |
Operator pods:
IBM: 0.256 GB RAM Third-party: 0.2 GB RAM Catalog pods: 0.05 GB RAM Operand: User-defined |
100 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: 4.5 vCPU |
Operator pods:
2 GB RAM Catalog pods: 0.05 GB RAM Operand: 14 GB RAM |
250 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.
|
Planning Analytics |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 10 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 22 GB RAM |
20 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 48 GB RAM |
200 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Not 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 1 GB RAM |
Not 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8 GB RAM |
Not 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 vCPU |
Operator pods:
0.6 GB RAM Catalog pods: 0.05 GB RAM Operand: 150 GB RAM |
425 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:
|
Watson Discovery |
Operator pods:
0.1 vCPU Catalog pods: 0.05 vCPU Operand: 15 vCPU |
Operator pods:
0.05 GB RAM Catalog pods: 0.01 GB RAM Operand: 93 GB RAM |
508 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 |
|
|
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.
|
Watson Knowledge Studio |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 7 vCPU |
Operator pods:
0.1 GB RAM Catalog pods: 0.05 GB RAM Operand: 31 GB RAM |
360 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 |
150 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 vCPU |
Operator pods:
1GB RAM Catalog pods: 0.05 GB RAM Operand: 18 GB RAM |
120 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 72 GB RAM |
100 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 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.05 GB RAM Operand: Speech to Text: 22 GB RAM Text to Speech: 15 GB RAM |
900 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 8.8 GB RAM |
Not 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 runtimes |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: Dictated by the runtimes |
Not applicable | Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:
|
Power (ppc64le) hardware
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 vCPU |
Operator pods:
1GB RAM Catalog pods: 0.05 GB RAM Operand: 18 GB RAM |
120 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 5.5 GB RAM |
200 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 |
10 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: SMP: 98 GB RAM MPP: 610 GB RAM |
200 GB |
Minimum resources for an installation with a single replica per service. Use dedicated nodes for:
For detail, see Setting up dedicated nodes.
|
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®
Service | vCPU | Memory | Storage | Notes |
---|---|---|---|---|
Analytics Engine Powered by Apache Spark |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 3 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 7 GB RAM |
Local 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 where
emptyDir 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 1 GB RAM Operand: 4 GB RAM |
Not 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 Studio
|
Db2 |
Operator pods:
0.1 vCPU Catalog pods: 0.01 vCPU Operand: 1.5 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 5.5 GB RAM |
200 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 instance |
Operator pods:
0.1 GB RAM Catalog pods: 0.05 GB RAM Operand: 13 GB RAM per instance |
50 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 19.31 GB RAM |
10 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: SMP: 98 GB RAM MPP: 610 GB RAM |
200 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) |
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 vCPU |
Operator pods:
0.5 GB RAM Catalog pods: 0.5 GB RAM Operand: 27 GB RAM |
150 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 vCPU |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: 72 GB RAM |
100 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 |
Not 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 runtimes |
Operator pods:
0.256 GB RAM Catalog pods: 0.05 GB RAM Operand: Dictated by the runtimes |
Not applicable | Runtimes use on-demand vCPU and memory. Watson Studio Runtimes includes the following runtimes:
|