System requirements

All the containers are based on Red Hat Universal Base Images (UBI), and are Red Hat and IBM certified. To use the FileNet Content Manager images, the administrator must make sure that the target cluster has the capacity for all of the components that you plan to install.

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 operator. Development, preproduction, and production are stages that are best run on different compute nodes. To achieve resource isolation, each namespace is a virtual cluster within the physical cluster and a FileNet Content Manager deployment is scoped to a single namespace. High-level resource objects are scoped within namespaces. Low-level resources, such as nodes and persistent volumes, are not in namespaces.

Note: Use the shared_configuration.sc_deployment_license parameter to define the purpose of the "custom" 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 deployment include the following elements:

  • Hardware architecture: Intel (amd64 or x86_64 the 64-bit edition for Linux® x86) on all platforms, Linux on IBM Z, or Linux on Power.
  • Node counts: Dual compute nodes for nonproduction and production clusters. A minimum of three nodes is needed for medium and large production environments and large test environments. Any cluster configuration needs to adapt to the size of the projects and the workload 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.

Based on your cluster requirement, you can pick a deployment profile (sc_deployment_profile_size) and enable it during installation. Cloud Pak for Business Automation provides small, medium, and large deployment profiles. You can set the profile during installation, in an update, and during an upgrade.

The default profile is small. Before you install, you can change the profile to medium or large. You can scale up or down a profile anytime after installation. However, if you install with a medium profile and another Cloud Pak specifies a medium or large profile then if you scale down to size small, the profile for the foundational services remains as it is. You can scale down the foundational services to small only if no other Cloud Pak specifies a medium or large size.

The following table describes each deployment profile.

Table 1. Deployment profiles and estimated workloads
Profile Description Scaling (per 8-hour day) Minimum number of worker nodes
Small (no HA) For environments that are used by 10 developers and 25 users. For environments that are used by a single department with a few users; useful for application development.
  • Processes 10,000 documents
  • Processes 5,000 workflows
  • Processes 5,000 transactions
  • Processes 500,000 decisions
  • Supports failover
  • StatefulSet provides high availability (HA)
8
Medium For environments that are used by 20 developers and 125 users. For environments that are used by a single department and by limited users.
  • Processes 100,000 documents
  • Processes 25,000 workflows
  • Processes 25,000 transactions
  • Processes 2,000,000 decisions
  • Supports HA and failover
  • Provides at least two replicas of most services, if configuring failover
16
Large For environments that are used by 50 developers and 625 users. For environments that are shared by multiple departments and users.
  • Processes 1,000,000 documents
  • Processes 125,000 workflows
  • Processes 125,000 transactions
  • Processes 5,000,000 decisions
  • Supports HA and failover
  • Provides at least two replicas of most services, if configuring failover
32

You can use custom resource templates to update the hardware requirements of the services that you want to install.

The following sections 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.

Attention: The values in the hardware requirements tables were derived under specific operating and environment conditions. The information is accurate under the given conditions, but results that are obtained in your operating environments might vary significantly. Therefore, IBM cannot provide any representations, assurances, guarantees, or warranties regarding the performance of the profiles in your environment.

Small profile hardware requirements

  • Table 2 Operator default requirements for a small profile
  • Table 3 Business Automation Insights default requirements for a small profile
  • Table 4 Navigator default requirements for a small profile
  • Table 5 FileNet® Content Manager default requirements for a small profile
Table 2. Operator default requirements for a small profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
ibm-cp4a-operator 500 1000 256 1024 1 No
Table 3. Business Automation Insights default requirements for a small profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
Business Performance Center 100 2000 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
Management REST API 100 1000 50 160 1 No
Management back end (second container of the same management pod as the previous one) 100 500 350 512 1 No
Note: Business Automation Insights relies on Kafka, and Elasticsearch from Foundational Services. Business Automation Insights also creates the bai-setup and iaf-insights-engine-application-setup Kubernetes jobs and requests 200m for CPU and 350Mi for memory. The CPU and memory limits are set equal to the requests. The pods of these Kubernetes jobs run for a short time at the beginning of the installation, then complete, thus freeing the resources.
Table 4. Navigator default requirements for a small profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
Navigator 1000 1000 3072 3072 1 No
Table 5. FileNet Content Manager default requirements for a small profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
CPE 1000 1000 3072 3072 1 Yes
CSS 1000 1000 4096 4096 1 Yes
Enterprise Records (ER) 500 1000 1536 1536 1 Yes
Content Collector for SAP (CC4SAP) 500 1000 1536 1536 1 Yes
CMIS 500 1000 1536 1536 1 No
GraphQL 500 1000 1536 1536 1 No
Task Manager 500 1000 1536 1536 1 No
Note: Not all containers are used in every workload. If a feature like the Content Services GraphQL API is not used, that container requires less resources or is optionally not deployed.

In high-volume indexing scenarios, where ingested docs are full-text indexed, the CSS utilization can exceed the CPE utilization. In some cases, this might be 3 - 5 times larger.

For optional processing such as thumbnail generation or text filtering, at least 1 GB of native memory is required by the CPE for each. If both types of processing are expected, add at least 2 GB to the memory requests/limits for the CPE.

With the processing of content, resources required increase with the complexity and size of the content. Increase both memory and CPU for the CPE and CSS services to reflect the type and size of documents in your system. Resource requirements might also increase over time as the amount of data in the system grows.

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.

Medium profile hardware requirements

  • Table 6 Operator default requirements for a medium profile
  • Table 7 Business Automation Insights default requirements for a medium profile
  • Table 8 Business Automation Navigator default requirements for a medium profile
  • Table 9 FileNet Content Manager default requirements for a medium profile
Table 6. Operator default requirements for a medium profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
ibm-cp4a-operator 500 1000 256 1024 1 No
Table 7. Business Automation Insights default requirements for a medium profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
Business Performance Center 100 4000 512 2000 2 Yes/No
Flink task managers 1000 1000 1728 1728 Default parallelism

2

Yes/No
Flink job manager 1000 1000 1728 1728 1 No
Management REST API 100 1000 50 160 2 No
Management back end (second container of the same management pod as the previous one) 100 500 350 512 2 No
Note: Business Automation Insights relies on Kafka, and Elasticsearch from Foundational Services. Business Automation Insights also creates the bai-setup and iaf-insights-engine-application-setup Kubernetes jobs and requests 200m for CPU and 350Mi for memory. The CPU and memory limits are set equal to the requests. The pods of these Kubernetes jobs run for a short time at the beginning of the installation, then complete, thus freeing the resources.
Table 8. Business Automation Navigator default requirements for a medium profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
Navigator 2000 3000 4096 4096 2 No
Table 9. FileNet Content Manager default requirements for a medium profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
CPE 1500 2000 3072 3072 2 Yes
CSS 1000 2000 8192 8192 2 Yes
Enterprise Records (ER) 500 1000 1536 1536 2 Yes
Content Collector for SAP (CC4SAP) 500 1000 1536 1536 2 Yes
CMIS 500 1000 1536 1536 2 No
GraphQL 500 2000 3072 3072 3 No
Task Manager 500 1000 1536 1536 2 No
Note: Not all containers are used in every workload. If a feature like the Content Services GraphQL API is not used, that container requires less resources or is optionally not deployed.

In high-volume indexing scenarios, where ingested docs are full-text indexed, the CSS utilization can exceed the CPE utilization. In some cases, this might be 3 - 5 times larger.

For optional processing such as thumbnail generation or text filtering, at least 1 GB of native memory is required by the CPE for each. If both types of processing are expected, add at least 2 GB to the memory requests/limits for the Content Platform Engine (CPE).

With the processing of content, resource requirements increase with the complexity and size of the content. Increase both memory and CPU for the CPE and CSS services to reflect the type and size of documents in your system. Resource requirements might also increase over time as the amount of data in the system grows.

Large profile hardware requirements

  • Table 10 Operator default requirements for a large profile
  • Table 11 Business Automation Insights default requirements for a large profile
  • Table 12 Business Automation Navigator default requirements for a large profile
  • Table 13 FileNet Content Manager default requirements for a large profile
Table 10. Operator default requirements for a large profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
ibm-cp4a-operator 500 1000 256 1024 1 No
Table 11. Business Automation Insights default requirements for a large profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
Business Performance Center 100 4000 512 2000 2 Yes/No
Flink task managers 1000 1000 1728 1728 Default parallelism

2

Yes/No
Flink job manager 1000 1000 1728 1728 1 No
Management REST API 100 1000 50 160 2 No
Management back end (second container of the same management pod as the previous one) 100 500 350 512 2 No
Note: Business Automation Insights relies on Kafka, and Elasticsearch from Foundational Services. Business Automation Insights also creates the bai-setup and iaf-insights-engine-application-setup Kubernetes jobs and requests 200m for CPU and 350Mi for memory. The CPU and memory limits are set equal to the requests. The pods of these Kubernetes jobs run for a short time at the beginning of the installation, then complete, thus freeing the resources.
Table 12. Business Automation Navigator default requirements for a large profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
Navigator 2000 4000 6144 6144 6 No
Table 13. FileNet Content Manager default requirements for a large profile
Component CPU Request (m) CPU Limit (m) Memory Request (Mi) Memory Limit (Mi) Number of replicas Pods are licensed for production/nonproduction
CPE 3000 4000 8192 8192 2 Yes
CSS 2000 4000 8192 8192 2 Yes
Enterprise Records (ER) 500 1000 1536 1536 2 Yes
Content Collector for SAP (CC4SAP) 500 1000 1536 1536 2 Yes
CMIS 500 1000 1536 1536 2 No
GraphQL 1000 2000 3072 3072 6 No
Task Manager 500 1000 1536 1536 2 No
Note: Not all containers are used in every workload. If a feature like the Content Services GraphQL API is not used, that container requires less resources or is optionally not deployed.

In high-volume indexing scenarios, where ingested docs are full-text indexed, the CSS utilization can exceed the CPE utilization. In some cases, this might be 3 - 5 times larger.

For optional processing such as thumbnail generation or text filtering, at least 1 GB of native memory is required by the CPE for each. If both types of processing are expected, add at least 2 GB to the memory requests/limits for the CPE.

With the processing of content, resources required increase with the complexity and size of the content. Increase both memory and CPU for the CPE and CSS services to reflect the type and size of documents in your system. Resource requirements might also increase over time as the amount of data in the system grows.