System requirements

All the Cloud Pak containers are based on Red Hat Universal Base Images (UBI), and are Red Hat and IBM certified. To use the Cloud Pak images, it is important that you understand what you must do before you install the Cloud Pak operator.

For each stage in your operations (a minimum of three stages is expected development, preproduction, and production), you must allocate a cluster of nodes before you install the Cloud Pak. Development, preproduction, and production are stages that are best run on different compute nodes.

Note: Use the shared_configuration.sc_deployment_license parameter to define the purpose of the "enterprise" deployment type (shared_configuration.sc_deployment_type). Valid values are production and non-production.

The Detailed system requirements page provides a cluster requirements guideline for IBM Cloud Pak® for Business Automation.

The minimum cluster configuration and physical resources that are needed to run the Cloud Pak includes (but is not limited to):

  • Hardware architecture: Intel (amd64 or x86_64 the 64-bit edition for Linux® x86) on all platforms.
  • Node counts: Dual compute nodes for non-production and production clusters. A minimum of three nodes is needed for medium and large production environments and larger test environments. Any cluster configuration needs to adapt to the size of the projects and the work load that is expected.
A cluster where you want to install all of the capabilities needs as a minimum:
  • Master (3 nodes): 4 vCPU and 8 Gi memory on each node.
  • Worker (8 nodes): 16 vCPU and 32 Gi memory on each node.
Note: Business Automation Insights can coexist with another Cloud Pak in different namespaces on a cluster, provided the cluster has sufficient capacity and that both Cloud Paks use the same version of foundation services.

The following tables provide the default resources for each capability. For more information about the minimum requirements of foundational services, see Hardware requirements and recommendations for foundational services.

  • Table 1 Cloud Pak for Business Automation operator default requirements
  • Table 2 Automation Decision Services default requirements
  • Table 3 Automation Document Processing default requirements
  • Table 4 Automation Workstream Services default requirements
  • Table 5 Business Automation Application default requirements
  • Table 6 Business Automation Insights default requirements
  • Table 7 Business Automation Navigator default requirements
  • Table 8 Business Automation Studio default requirements
  • Table 9 Business Automation Workflow default requirements with or without Automation Workstream Services
  • Table 10 FileNet® Content Manager default requirements
  • Table 11 Operational Decision Manager default requirements
  • Table 12 User Management Service default requirements
Table 1. Cloud Pak for Business Automation operator default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
ibm-cp4a-operator 500 1000 256 1024 1 No
Table 2. Automation Decision Services default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
ads-runtime 1000 2000 2048

For 21.0.1 512

 3072

For 21.0.1

2048		 2 - 5 with horizontal pod autoscaling enabled Yes
For 21.0.1 ads-embedded-runtime 1000 2000 512 2048 2 Yes
ads-credentials

250

For 21.0.1 500

500

For 21.0.1 2000

800

For 21.0.1 512

1536

For 21.0.1 2048

 2 No
ads-embedded-build 500 2000 1024 2048 2 No
ads-download 100 300

For 21.0.1 500

 200 200 2 No
ads-front 250

For 21.0.1 500

 500

For 21.0.1 2000

 256

For 21.0.1 512

 512

For 21.0.1 2048

 2 No
ads-gitservice 500 1000

For 21.0.1 2000

 800

For 21.0.1 512

 1536

For 21.0.1 2048

 2 No
ads-parsing 250

For 21.0.1 500

 1000

For 21.0.1 2000

 800

For 21.0.1 512

 1536

For 21.0.1 2048

 2 No
ads-restapi 500 1000

For 21.0.1 2000

 800

For 21.0.1 512

 1536

For 21.0.1 2048

 2 No
ads-run 500 1000

For 21.0.1 2000

 800

For 21.0.1 512

 1536

For 21.0.1 2048

 2 No
mongo 500 1000 256 1024 2 No
Note: Automation Decision Services also creates some jobs that request 200m CPU and 256Mi Memory. The following jobs are created once at the beginning of the installation and do not last long:
  • ads-ltpa-creation
  • ads-runtime-bai-registration
  • ads-runtime-ums-registration
  • ads-ums-registration

The ads-rr-integration job is started every 15 minutes, and is also short-lived.

Table 3. Automation Document Processing default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of Replicas (Demo/Small Enterprise) Pods are licensed for production/non-production
OCR Extraction 200 1000 2048 4096

For 21.0.1 (8Gi for demo)

 2/4 Yes
Classify Process 200 500

For 21.0.1 1000

 100 960 1/2 Yes
Processing Extraction 500 1000 1024 2048 1/2 Yes
Natural Language Extractor 200 500

For 21.0.1 1000

 100 1440 1/2 Yes
Callerapi 200 600 1024 3072 1/2 No
PostProcessing 200 600 100 480 1/2 No
For 21.0.1 PDFProcess 200 600 100 960 1/2 No
For 21.0.1 Utf8Process 200 1000 100 960 1/2 No
Setup 200 600 100 700 1/2 No
Deep Learning 1000 2000 3072 10240 1/2 No
UpdateFileDetail 200 600 100 480 1/2 No
Backend 200 600 100 1024 1/2 No
Redis 100 250 100 640 2/3 No
RabbitMQ 100 500 100 1024 2/3 No
Common Git Gateway Service (git-service) 500 1000 512 3072 2 No
Content Designer Repo API (CDRA) 500 1000 512 1024 2 No
Content Designer UI and REST (CDS) 500 1000 512 1024 2 No
Content Project Deployment Service (CPDS) 500 1000 512 1024 2 No
Mongo database (mongodb) 100 500 256 512 1 No
Viewer service (viewone) 500 1000 1024 4096 2 No
Important: Document Processing - For Deep Learning, it is highly recommended to use worker nodes with NVIDIA GPU for better and faster results. NVIDIA is the only supported GPU for Deep Learning in the Document Processing pattern. Use these installation instructions to install the NVIDIA GPU Operator.

The GPU worker nodes must have a unique label, like ibm-cloud.kubernetes.io/gpu-enabled:true. You add this label value to the deployment script or your CR YAML when you configure the YAML for deployment. To achieve HA, you need a minimum of 2 GPU so that 2 replicas of Deep Learning pods can be started. You can change the replica to 1 if you only have 1 GPU on the node.

Important: For Document Processing, the CPU of the worker nodes must meet TensorFlow AVX requirements. For more information, see Hardware requirements for TensorFlow with pip.
Note: Each Processing Extraction pod uses an additional 50Mi of RAM for the tmpfs volume mount with the type of Memory.
Note: Document Processing requires databases for project configuration and processing. These databases must be Db2. The hardware and storage requirements for the databases depend on the system load for each document processing project.
Table 4. Automation Workstream Services default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
Workflow Server 500 4000 2048 3072 2 Yes
Java™ Message Service 200 1000 512 2048 1 No
Process Federation Service 500 2000 512 4096 1 No
Process Federation Service-dbareg 200 500 512 512 1 No
Elasticsearch Service 200 2000 2148 3072 1 No
Notes:

Elasticsearch is installed if the deployment platform is set to "other" and the pfs_configuration.elasticsearch parameter is empty. For 21.0.1, Elasticsearch is always installed.

Automation Workstream Services also creates some jobs that request 200m CPU and 128Mi Memory:
  • basimport-job is created only with Business Automation Studio.
  • content-init-job
  • db-init-job-pfs
  • ltpa-job
  • oidc-registry-job
  • workplace-init-job
The db-init-job requests 500m CPU and 512Mi Memory.
Table 5. Business Automation Application default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
App Engine 300 2000 512 2048 2 Yes/No
Resource Registry 100 500 128 512 3 No
Table 6. Business Automation Insights default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
Business Performance Center 100 4000 512 2000 1 Yes/No
Flink task managers 1000 1000 1728 1728 Default parallelism

2

 Yes/No
Flink job manager 1000 1000 1728 1728 1 No
Administration REST API
  • (Optional) 100
  • For 21.0.1 3
  • (Optional) 500
  • For 21.0.1 -
50 120 2 No
Management REST API
  • 100
  • For 21.0.1 3
  • 1000
  • For 21.0.1 -
50 120 2 No
Management back end (second container of the same management pod as the previous one)

For 21.0.1 This container does not exist.

100 500 350 512 2 No
Note: Business Automation Insights relies on Kafka, Apicurio, and Elasticsearch from IBM Automation foundation. For information about their system requirements, see the System requirements page of the IBM Automation foundation documentation. Business Automation Insights also creates a Kubernetes job, which is named bai-setup and requests 200m for CPU and 350Mi for memory. Its CPU and memory limits are set equal to the requests. The pod of this Kubernetes job runs for a short time at the beginning of the installation, then completes, thus freeing the resources.
Table 7. Business Automation Navigator default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
Navigator 500 1000 512 1536 2 No
Table 8. Business Automation Studio default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
App Engine playback 300 2000 512 2048 2 No
BAStudio 1000 4000 1024 3072 1 No
BAStudio JMS 200 1000 256 1024 1 No
Resource Registry 100 500 128 512 3 No
Table 9. Business Automation Workflow default requirements with or without Automation Workstream Services
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
Workflow Server 500 4000 2048 3072 2 Yes
Workflow Authoring 500 4000 1024 3072 1 No
Java Message Service 200 1000 512 2048 1 No
Process Federation Service 500 2000 512 4096 1 No
Process Federation Service-dbareg 500 500 512 512 1 No
Elasticsearch Service 200 2000 2148 3072 1 No
Intelligent Task Prioritization 500 2000 1024 2560 2 No
Workforce Insights 500 2000 1024 2560 2 No
Note:

Elasticsearch is installed if the deployment platform is set to "other" and the pfs_configuration.elasticsearch parameter is empty. For 21.0.1, Elasticsearch is always installed.

Business Automation Workflow also creates some jobs that request 200m CPU and 128Mi Memory:
  • basimport-job is created only with Business Automation Studio.
  • case-init-job
  • content-init-job
  • db-init-job-pfs
  • ltpa-job
  • oidc-registry-job
  • oidc-registry-job-for-webpd is created only with workflow center.
  • workplace-init-job
The db-init-job requests 500m CPU and 512Mi Memory.
Table 10. FileNet Content Manager default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
CPE 500 1000 512 3072 2 Yes
CSS 500 1000 512 4096 2 Yes
Enterprise Records (ER) 500 1000 512 1536 1 Yes
Content Collector for SAP (CC4SAP) 500 1000 512 1536 2 Yes
CMIS 500 1000 256 1536 2 No
GraphQL 500 1000 512 1536 2 No
External Share 500 1000 512 1536 2 No
Task Manager 500 1000 512 1536 2 No
Table 11. Operational Decision Manager default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
Decision Center 500 2000 1500 4096 2 Yes
Decision Runner 500 1000 512 4096 2 Yes
Decision Server Runtime 500 2000 512 4096 2 Yes
Decision Server Console 500 2000 512 1024 2 No
Note: Operational Decision Manager also creates an odm-oidc-job-registration job that requests 200m CPU and 256Mi Memory. The pod is created at the beginning of the installation and does not last long.
Table 12. User Management Service (UMS) default requirements
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/non-production
UMS 200 500 256 512 2 No
Note: With dedicated_pods configuration set to true, a pod is created for each of the UMS capabilities, therefore the overall requirement multiplies by a factor of the UMS capabilites.

To achieve high availability, you must adapt the cluster configuration and physical resources. You can set up a Db2® High Availability Disaster Recovery (HADR) database. For more information, see Preparing your environment for disaster recovery. For high availability and fault tolerance to be effective, set the number of replicas that you need for the respective configuration parameters in your custom resource file. The operator then manages the scaling.