App Connect Designer Authoring reference

Use this reference to create, update, or delete App Connect Designer instances by using the IBM® Cloud Pak Platform UI, or the Red Hat® OpenShift® web console or CLI.

Tip: A deployed IBM Cloud Pak for Integration Platform UI instance gives you access to the IBM Cloud Pak Platform UI, where you can create and manage instances of capabilities from a central location.

Introduction
Prerequisites
Red Hat OpenShift SecurityContextConstraints requirements
Resources required
Storage
Data encryption
Creating an instance
Updating the custom resource settings for an instance
Deleting an instance
Validation for custom resource values
Custom resource values
Supported platforms

Introduction

The App Connect Designer Authoring API enables you to create an App Connect Designer instance for developing, testing, and sharing integration flows. An App Connect Designer instance provides an authoring environment for hosting non-production workloads.

Usage guidelines:

Multiple instances of App Connect Designer can be created in a namespace (project) for individual or team use. Users in this namespace can then use their allocated instance to develop and manage flows.

Prerequisites

Red Hat OpenShift Container Platform 4.12 or 4.14 is required.
Note: For information about the custom resource (or operand) versions that are supported for each Red Hat OpenShift version, see spec.version values.
The IBM App Connect Operator must be installed in your cluster either through an independent deployment or an installation of IBM Cloud Pak for Integration. For further details, see the following information:
- Installing the IBM App Connect Operator on Red Hat OpenShift
- IBM Cloud Pak for Integration: Overview of installation
Ensure that you have cluster administrator authority or have been granted the appropriate role-based access control (RBAC).
If you want to use the command-line interface (CLI) to log in to your cluster and run commands to create and manage your IBM App Connect instances and other resources, ensure that the required CLI tools are installed on your computer. For more information, see Installing tools for managing the cluster, containers, and other resources (on Red Hat OpenShift).
You must have a Kubernetes pull secret called ibm-entitlement-key in the namespace before creating the instance. For more information, see Obtaining and applying your IBM Entitled Registry entitlement key.
When you create an App Connect Designer instance, you can enable the use of local or cloud-managed connectors. These connectors will be used to connect to the target applications that are referenced in any flows that are created, and to run the defined events, actions, or operations. If you are creating an App Connect Designer instance at version 12.0.3.0-r2 or later, you can enable local connectors only. If you are creating an App Connect Designer instance at version 12.0.3.0-r1 or earlier, you can enable local connectors only, or enable both local and cloud-managed connectors.
- 1. An instance of IBM App Connect on IBM Cloud is required, which hosts the cloud-managed connectors.
  2. Launch the instance and make a note of the instance identifier.
  3. Make a note of the region in which the instance is provisioned.
  4. Create an IBM Cloud API key while logged in to the same IBM Cloud account as the App Connect on IBM Cloud instance. You can create this key from the IBM Cloud API Keys page at: https://cloud.ibm.com/iam/apikeys. Download the key to your browser’s default location for later use. The file is named apiKey.json.
    Tip: To keep the value of the key secure, it needs to be stored in a Kubernetes secret. Depending on how you choose to create your App Connect Designer instance (Form or YAML view), you can either let the IBM App Connect Operator generate a secret for you, or you can manually create a secret by using the Red Hat OpenShift web console or CLI.
  5. Optional. To create your own secret for the IBM Cloud API key, complete either of the following steps:
    - Red Hat OpenShift web console:
      
      From the navigation, click Workloads > Secrets.
      
      If necessary, select the namespace (project) in which you installed the IBM App Connect Operator.
      
      Click Create > Key/Value Secret and then specify a name for the secret in the Secret Name field.
      
      Specify apikey in the Key field, and then specify the IBM Cloud API key in the Value field.
      
      Click Create.
      
      Make a note of the secret name so that you can specify it while creating your App Connect Designer instance.
    - Red Hat OpenShift CLI:
      
      From the command line, log in to your Red Hat OpenShift cluster by using the oc login command.
      
      Run the following command:
      
      oc create secret generic secretName --from-literal=apikey=IBMCloudAPIkey --namespace=namespaceName
      
      Where:
      
      secretName is the name of the secret for storing the IBM Cloud API key.
      
      IBMCloudAPIkey is the key within the downloaded apiKey.json file.
      
      namespaceName is the namespace in which the App Connect Designer instance will be created. You can omit the --namespace flag if you are already logged in to this namespace.
      
      Make a note of the secret name so that you can specify it while creating the App Connect Designer instance.
  Access considerations for cloud-managed connectors:
  The number of App Connect Designer instances that you create should depend on your team requirements, but take note of the following consideration for access.
  
  If you create one App Connect Designer instance for a team of users under a namespace, each user will require access to the (single) App Connect on IBM Cloud instance that hosts the connectors. (An App Connect Designer instance can be coupled with only one App Connect on IBM Cloud instance.)
  
  Each user will require Developer access to the Cloud Foundry organization and space that the App Connect on IBM Cloud instance belongs to. For more information about allocating Developer access to the App Connect on IBM Cloud instance, see Inviting users to an account in the IBM Cloud Managing identity and access documentation.

Red Hat OpenShift SecurityContextConstraints requirements

IBM App Connect runs under the default restricted SecurityContextConstraints.

Resources required

Minimum recommended requirements:

CPU: 1.85 Cores
Memory: 2.6 GB
Storage: 10 GB

With Mapping Assist:

CPU: 3.1 Cores
Memory: 3.8 GB

For information about how to configure these values, see Custom resource values.

Storage

App Connect Designer requires separate storage volumes for Apache CouchDB and the artificial intelligence (AI) model that is implemented for the Mapping Assist incremental learning feature.

Supported storage types for Apache CouchDB
Supported storage types for the AI model

Supported storage types for Apache CouchDB

The IBM App Connect Operator provides a CouchDB NOSQL database server to store flow definition artifacts within a volume in the container’s file system.

Before you create the App Connect Designer instance, you must decide what type of storage to use for CouchDB because you will need to specify this storage type while creating the instance and will not be able to change this setting after the instance is created.

The following storage types can be used to allocate storage for CouchDB:

Persistent storage

Persistent storage is recommended for extra resilience because the CouchDB server is retained when pods restart and is deleted only when you delete the Designer instance.

A persistent volume must be dynamically provisioned through a storage class that is available on the cluster by using the spec.couchdb.storage.class parameter. Storage classes must support the following modes:

Dynamic volume provisioning
ReadWriteOnce (RWO) access modes
volumeBindingMode: WaitForFirstConsumer (zone-local storage)
POSIX filesystem compatibility (for example, not NFS)

The mode requirements map to the following preferred options for common public cloud environments:

Provider	Type	Storage class	Documentation
IBM Cloud	IBM Block Storage	ibm-block-*	Documentation
AWS	Elastic Block Storage	aws-ebs	Documentation
Azure	Azure Disk	default or managed-premium	Documentation

For Google Compute Engine (GCE), Persistent Disk can be used, but a storage class must be manually created to support dynamic provisioning.

For more information about persistent volumes, see Persistent Volumes in the Kubernetes documentation.

If you choose persistent storage, you will need to specify a storage class, storage size, and number of replica pods.

Ephemeral storage

With this storage type, an ephemeral volume is created to store the CouchDB server when a Designer pod is started. The ephemeral (emptyDir) volume exists only for the lifetime of the pod, so the CouchDB server will be lost when the pod restarts. You might typically choose this storage type if creating an environment for demonstration or testing.

To define the storage type for CouchDB when creating an App Connect Designer instance, you must specify your preferred type in the custom resource settings by setting the spec.couchdb.storage.type parameter and then complete the other spec.couchdb.storage.* parameters as appropriate for the selected storage type.

Supported storage types for the AI model

When you create an App Connect Designer instance, you can optionally choose to enable the incremental learning feature, which uses AI modeling techniques to improve the accuracy of source-to-target mapping suggestions that are offered in all authored flows. A supplied AI model is retrained at periodic intervals with training data that is collected about your mapping preferences.

Before you create the App Connect Designer instance, you must decide what type of storage to use for the AI model because you will need to specify this storage type and any associated settings while creating the instance.

Note: Incremental learning is available only if the spec.version value in the App Connect Designer custom resource resolves to 12.0.1.0-r1 or later. For more information about incremental learning, see Simplifying data mapping and data transformation with AI-powered suggestions.

The following storage types can be used to allocate storage for the AI model:

Persistent storage

With this storage type, the AI model is stored in a persistent volume in the container’s file system. The persistent volume can be dynamically provisioned through a storage class that is available on the cluster, or can be requested through a claim name. With persistent storage, the AI model is retained in the file system when pods restart and is deleted only when you delete the App Connect Designer instance.

Note: Persistent storage is applicable only if the spec.version value in the App Connect Designer custom resource resolves to 12.0.1.0-r1 or later.

Incremental learning requires a storage class with ReadWriteMany (RWX) capability. If using IBM Cloud, use the ibmc-file-gold-gid storage class.

If you choose persistent storage, you will need to specify a storage class or the name of an existing claim. (A storage size does not need to be manually specified because the allocated default is suitable for requirements.)

Simple Storage Service (S3) storage

S3 storage offers an alternative option to persistent storage, and supports the use of an object storage service for storing the AI model by using the S3 REST API.

Note: S3 storage is applicable only if the spec.version value in the App Connect Designer custom resource resolves to 12.0.1.0-r4 or later.

Restriction:

S3 storage is not supported when the IBM App Connect Operator is installed in a restricted network because a cluster requires internet access to read and write training data from or to an S3 object store.
Only Amazon S3 and IBM Cloud Object Storage S3 are supported as S3 providers.

The AI model will be stored as an object with read/write access in a specified bucket in your S3 instance and can be viewed in the S3 bucket. The AI model is stored in ZIP format in the following location in the bucket, and the ZIP object will be overwritten (with the same name) each time the model is retrained:

/mapping-assist-model/mapping_assist_v1.1.0.zip

Warning: Do not delete an AI model from the S3 bucket if that model is in use by a Designer instance because the accumulated data will be lost. Although a new base model will automatically be created for the Designer instance, this model will need to undergo training at the next scheduled interval (using data collated only during that interval) before being added to the S3 bucket.

If you choose S3 storage, you will need to specify the following storage settings for your provisioned S3 instance:

The name of an existing bucket for storing the AI model
You are not restricted from using an S3 bucket that already contains other objects because the AI model is separately stored in a dedicated folder (mapping-assist-model). If you want to enable S3 storage for AI models in multiple App Connect Designer instances, you must use a separate S3 bucket for each instance to ensure that the AI model for one instance does not get overwritten by the AI model for another instance.
An S3 endpoint to which the S3 REST API sends requests for reading and writing objects
You should be able to locate the available endpoints from your S3 instance. For example, on IBM Cloud Object Storage S3, you can locate the endpoints from the Endpoints page.

To minimize latency, it is recommended that you use an S3 bucket that is in the same geographic area as your App Connect Designer instance. Also use an endpoint with a location or region that is similar to where Designer is deployed. For more information, see Endpoints and storage locations in the IBM Cloud Object Storage S3 documentation and Amazon Simple Storage Service endpoints and quotas in the Amazon Web Services documentation.
S3 credentials for connecting to the bucket
You will need to supply these credentials by creating a configuration of type S3Credentials. For more information, see Creating a configuration of type S3Credentials for use with App Connect Designer.

To define the storage type for the AI model when creating an App Connect Designer instance, you must specify your preferred type in the custom resource settings by setting the spec.designerMappingAssist.incrementalLearning.storage.type parameter and then complete the other spec.designerMappingAssist.incrementalLearning.storage.* parameters as appropriate for the selected storage type. If you want to create a Designer instance that uses S3 storage for the AI model, your must first create a configuration object of type S3Credentials to store the credentials for accessing the bucket.

Data encryption

To secure data that is stored at rest, the following options are supported for enabling data encryption:

Portworx Enterprise
For more information, see Step 4: Set up volume encryption with IBM Key Protect.
IBM Cloud File Storage
For more information, see Setting up encryption for Block Storage for VPC.
Amazon services

Other options, such as Network File System (NFS), are not supported.

Creating an instance

You can create an App Connect Designer instance from the IBM Cloud Pak Platform UI, or the Red Hat OpenShift web console or CLI.

Before you begin

Ensure that the Prerequisites are met.
If you want to create an App Connect Designer instance that uses S3 storage for the AI model, ensure that you have created a configuration object of type S3Credentials as described in Creating a configuration of type S3Credentials for use with App Connect Designer.
Decide how to control upgrades to the instance when a new version becomes available. The spec.version value that you specify while creating the instance will determine how that instance is upgraded after installation, and whether you will need to specify a different license or version number for the upgrade. To help you decide whether to specify a spec.version value that either lets you subscribe to a channel for updates, or that uses a specific version for the instance, review the Upgrade considerations for channels, versions, and licenses before you start this task.

Namespace restriction for an instance, server, configuration, or trace:
The namespace in which you create an instance or object must be no more than 40 characters in length.

Create options:

Creating an instance from the IBM Cloud Pak Platform UI
Creating an instance from the Red Hat OpenShift web console
Creating an instance from the Red Hat OpenShift CLI

Creating an instance from the IBM Cloud Pak Platform UI

To create an App Connect Designer instance from the IBM Cloud Pak Platform UI, complete the following steps:

From a browser window, log in to the IBM Cloud Pak Platform UI.
Tip: You can use the generated URL for a deployed IBM Cloud Pak for Integration Platform UI instance to access the IBM Cloud Pak Platform UI.

The Platform UI home page opens with cards and navigation menu options that provide access to the instances and other resources that you are authorized to create, manage, or use. For information about completing administration tasks (such as user management or platform customization) from this page, see Platform UI in the IBM Cloud Pak foundational services documentation.
From the navigation menu , expand Administration and click Integration instances.
From the "Integration instances" page, click Create an instance.
To create an App Connect Designer instance from the Create an instance page, click the Integration design tile and click Next.
From the "Create an integration design instance" page, click a tile to select which type of instance you want to create:
- Quick start with AI enabled: Deploy an App Connect Designer instance with one replica pod, and with AI-powered mapping assist and transformation generation enabled.
  Consider choosing this option if you are the sole user or if you want to quickly get started for evaluative purposes, and additionally want to try out these features:
  - Mapping assist, which provides "smart mapping" that enables you to auto-populate the fields within a flow with the best possible matches from previous nodes
  - Transformation generation, which uses supplied sample data or drop-down list values to construct complex (JSONata) transformations that let you easily map source data to target data
- Development with AI enabled: Deploy an App Connect Designer instance with multiple replica pods for resilience and high availability, and with AI-powered mapping assist and transformation generation enabled.
  Consider choosing this option to create a Development deployment that additionally provides the following features:
  - Mapping assist, which provides "smart mapping" that enables you to auto-populate the fields within a flow with the best possible matches from previous nodes
  - Transformation generation, which uses supplied sample data or drop-down list values to construct complex (JSONata) transformations that let you easily map source data to target data
- Quick start: Deploy an App Connect Designer instance with one replica pod.
  Consider choosing this option if you are the sole user and want to quickly get started for evaluative purposes. AI-powered mapping assist and transformation generation are disabled by default.
- Development: Deploy an App Connect Designer instance with multiple replica pods for resilience and high availability.
  Consider choosing this option for a multi-user environment with larger workloads than the Quick start deployment, with the capability to switch between replica pods to support failover. AI-powered mapping assist and transformation generation are disabled by default.
Click Next. A UI form view opens with the minimum configuration required to create the instance.
Complete either of the following steps:
- To quickly get going, complete the standard set of configuration fields. You can display advanced settings in the UI form view by setting Advanced settings to On. Note that some fields might not be represented in the form.
  - Name: Enter a short distinctive name that uniquely identifies this Designer instance.
  - Namespace: Enter the name of the namespace (project) where you want to create the Designer instance.
  - Channel or version: Select an App Connect product (fix pack) version that the Designer instance is based on. You can select a channel that will resolve to the latest fully qualified version on that channel, or select a specific fully qualified version. If you are using IBM App Connect Operator 5.0.4 or later, the supported channels or versions will depend on the Red Hat OpenShift version that is installed in your cluster. For more information about these values, see spec.version values.
  - Accept: Review the license in the supplied link and then click this check box to accept the terms and conditions.
  - License LI: Select a license identifier that aligns with the channel or the fully qualified version that you selected. For more information, see Licensing reference for IBM App Connect Operator.
  - License use: Select an appropriate CloudPakForIntegration or AppConnectEnterprise license type that you are entitled to use.
  - Replicas: Specify the number of replica pods to run for this deployment.
  - Connectors to use: Specify what type of connectors you want to use. The default value of local enables the use of locally deployed connectors only.
    - Applicable only if creating an App Connect Designer instance at version 12.0.3.0-r1 or earlier:
      If you set the Connectors to use field to all (to enable both local and cloud-managed connectors), you must specify an IBM Cloud API key that provides access to the App Connect on IBM Cloud instance that hosts the cloud-managed connectors.
      
      You can either specify the IBM Cloud API key in the IBM Cloud API key field, or specify the name of a manually created secret, which stores the IBM Cloud API key, in the IBM Cloud API key secret field. For information about creating an IBM Cloud API key or secret, see Prerequisites. You can specify the key or secret in either of the following ways:
      
      Specify the IBM Cloud API key to automatically generate a secret:
      
      Switch to the YAML view.
      
      Update the YAML settings to include the spec.ibmCloudAPIKeyValue parameter and set its value to the IBM Cloud API key. For example:
      
      spec: ibmCloudAPIKeyValue: abc_123
      
      Specify the name of a manually created secret that stores the IBM Cloud API key:
      
      From the IBM Cloud API key drop-down list, select ProvideAsASecretInIBMCloudAPIKeySecret.
      
      From the IBM Cloud API key secret drop-down list, select the name of the secret that you created earlier, which stores the IBM Cloud API key. For information about creating this secret, see Prerequisites.
      
      For information about the spec.ibmCloudAPIKeyValue and spec.ibmCloudAPIKeySecret parameters (which represent the IBM Cloud API key and IBM Cloud API key secret fields), see Custom resource values.
      
      When the Connectors to use field is set to all, you must also specify the instance identifier (spec.appConnectInstanceID) and endpoint (spec.appConnectURL) of the App Connect on IBM Cloud instance.
  - Enable Mapping Assist: Set this switch to on to enable the Mapping Assist components.
    Consider whether you want to enable Mapping Assist for smart mapping and data transformation (which requires extra resources). You can also optionally enable Mapping Assist incremental learning to use AI modeling for enhanced smart mapping. If you enable incremental learning, you'll need to specify a "learning" frequency, and indicate whether the AI model should be stored in a persistent volume or an S3 bucket. If you are using an S3 bucket, you'll need to provide details for connecting to this bucket, including the name of the configuration object of type S3Credentials, which you created to store your S3 credentials. In YAML view, you can use the spec.designerMappingAssist.enabled and spec.designerMappingAssist.incrementalLearning.* parameters to configure the Mapping Assist features. For more information about Mapping Assist and the configuration object for S3 storage, see Simplifying data mapping and data transformation with AI-powered suggestions and Creating a configuration of type S3Credentials for use with App Connect Designer.
  - Storage type: Select the type of storage to use for CouchDB.
    - persistent-claim: Choose this option for storage in a persistent volume in the container’s file system. Retains the existing configuration, logs, and persistent messages when pods restart.
    - ephemeral: Choose this option for storage in an ephemeral volume that exists only for the lifetime of the pod.
  - Storage class: Select a supported storage class for your cluster, which should be used to dynamically provision a persistent volume that belongs to that class. This value is required if Storage type is set to persistent-claim.
  - Size: Specify the maximum amount of storage required for a persistent volume for CouchDB in decimal or binary format; that is, Gi or G. This value is required if Storage type is set to persistent-claim.
- For a more advanced configuration, click YAML to switch to the YAML view and then update the editor with your required parameters.
  - For information about the available parameters and their values, see Custom resource values.
    In the default parameters that are presented, be aware that a value is required for spec.couchdb.storage.class (and for spec.couchdb.storage.size) when spec.couchdb.storage.type is set to persistent-claim. The spec.couchdb.storage.class value must match a supported storage class for your cluster. (The UI form view presents these classes in a drop-down list.)
```
spec:
  couchdb:
    storage:
      class: 'storageClassValue'
      size: 10Gi
      type: persistent-claim
```
  - For licensing information, see Licensing reference for IBM App Connect Operator.
Click Create. You are redirected to the Integration instances page. An entry for the instance is shown in the table with an initial status of Pending, which you can click to check the progress of the deployment. When the deployment completes, the status changes to Ready.

Users with the required permission can access this Designer (Integration design) instance by clicking the name, and then use the instance to author flows.

Creating an instance from the Red Hat OpenShift web console

To create an App Connect Designer instance by using the Red Hat OpenShift web console, complete the following steps:

Applicable to IBM Cloud Pak for Integration only:
1. If not already logged in, log in to the IBM Cloud Pak Platform UI for your cluster.
2. From the Platform UI home page, click Install operators or OpenShift Container Platform, and log in if prompted.
Applicable to an independent deployment of IBM App Connect Operator only: From a browser window, log in to the Red Hat OpenShift Container Platform web console. Ensure that you are in the Administrator perspective .
From the navigation, click Operators > Installed Operators.
If required, select the namespace (project) in which you installed the IBM App Connect Operator.
From the Installed Operators page, click IBM App Connect.
From the Operator details page for the App Connect Operator, click the Designer Authoring tab. Any previously created Designer instances are displayed in a table.
Click Create DesignerAuthoring.
From the Details tab on the Operator details page, you can also locate the Designer Authoring tile and click Create instance to specify installation settings for the instance.
To use the Form view, ensure that Form view is selected and then complete the fields. Note that some fields might not be represented in the form. For information about completing the standard set of configuration fields, refer to the field descriptions in Creating an instance from the IBM Cloud Pak Platform UI. (In the web console, the namespace or project is not included in the form and should already be selected from an earlier step.)
Optional: For a finer level of control over your installation settings, click YAML view to switch to the YAML view. Update the content of the YAML editor with the parameters and values that you require for this Designer instance.
- To view the full set of parameters and values available, see Custom resource values.
  In the default parameters that are presented, be aware that a value is required for spec.couchdb.storage.class (and for spec.couchdb.storage.size) when spec.couchdb.storage.type is set to persistent-claim. The spec.couchdb.storage.class value must match a supported storage class for your cluster. (The Form view presents these classes in the Storage class drop-down list.)
```
spec:
  couchdb:
    storage:
      class: 'storageClassValue'
      size: 10Gi
      type: persistent-claim
```
  Note: If you want to create and run callable flows in the Designer instance, you must configure the instance to use a switch server that you created earlier. For information about how to create a switch server, see App Connect Switch Server reference. Update the YAML to include the spec.switchServer.name parameter and set its value to the name of the switch server. For example:
```
spec:
  switchServer:
    name: default
```
  Consider whether you want to enable Mapping Assist for smart mapping and data transformation (which requires extra resources). You can also optionally enable Mapping Assist incremental learning to use AI modeling for enhanced smart mapping. If you enable incremental learning, you'll need to specify a "learning" frequency, and indicate whether the AI model should be stored in a persistent volume or an S3 bucket. If you are using an S3 bucket, you'll need to provide details for connecting to this bucket, including the name of the configuration object of type S3Credentials, which you created to store your S3 credentials. In YAML view, you can use the spec.designerMappingAssist.enabled and spec.designerMappingAssist.incrementalLearning.* parameters to configure the Mapping Assist features. For more information about Mapping Assist and the configuration object for S3 storage, see Simplifying data mapping and data transformation with AI-powered suggestions and Creating a configuration of type S3Credentials for use with App Connect Designer.
- For licensing information, see Licensing reference for IBM App Connect Operator.
Click Create to start the deployment. An entry for the Designer instance is shown in the DesignerAuthorings table, initially with a Pending status.
Click the Designer instance name to view information about its definition and current status.
On the Details tab of the page, the Conditions section reveals the progress of the deployment.

Note: The UI URL field provides the URL for accessing the Designer instance. You can also locate this URL under Networking > Routes in the console navigation.

Share this URL with users who have access to this namespace, and who will need to use the Designer instance to author flows.

You can use the breadcrumb trail to return to the (previous) Operator details page for the App Connect Operator. When the deployment is complete, the status is shown as Ready in the DesignerAuthorings table.

Creating an instance from the Red Hat OpenShift CLI

To create an App Connect Designer instance from the Red Hat OpenShift CLI, complete the following steps.

From your local computer, create a YAML file that contains the configuration for the App Connect Designer instance that you want to create. Include the metadata.namespace parameter to identify the namespace in which you want to create the instance; this should be the same namespace where the other App Connect instances or resources are created.

To view the full set of parameters and values that you can specify, see Custom resource values.
In the default parameters that are presented, be aware that a value is required for spec.couchdb.storage.class (and for spec.couchdb.storage.size) when spec.couchdb.storage.type is set to persistent-claim. The spec.couchdb.storage.class value must match a supported storage class for your cluster.
```
spec:
  couchdb:
    storage:
      class: 'storageClassValue'
      size: 10Gi
      type: persistent-claim
```
Note: If you want to create and run callable flows in the Designer instance, you must configure the instance to use a switch server that you created earlier. For information about how to create a switch server, see App Connect Switch Server reference. Update the YAML to include the spec.switchServer.name parameter and set its value to the name of the switch server. For example:
```
spec:
  switchServer:
    name: default
```
Consider whether you want to enable Mapping Assist for smart mapping and data transformation (which requires extra resources). You can also optionally enable Mapping Assist incremental learning to use AI modeling for enhanced smart mapping. If you enable incremental learning, you'll need to specify a "learning" frequency, and indicate whether the AI model should be stored in a persistent volume or an S3 bucket. If you are using an S3 bucket, you'll need to provide details for connecting to this bucket, including the name of the configuration object of type S3Credentials, which you created to store your S3 credentials. In YAML view, you can use the spec.designerMappingAssist.enabled and spec.designerMappingAssist.incrementalLearning.* parameters to configure the Mapping Assist features. For more information about Mapping Assist and the configuration object for S3 storage, see Simplifying data mapping and data transformation with AI-powered suggestions and Creating a configuration of type S3Credentials for use with App Connect Designer.
For licensing information, see Licensing reference for IBM App Connect Operator

The following examples (Example 1 and Example 2) show a Designer CR with settings to enable local connectors only, and to configure CouchDB storage and a switch server. The settings also enable Mapping Assist and incremental learning with a persistent-claim storage definition for the AI model.

Tip: If you are creating an App Connect Designer instance at version 12.0.3.0-r1 or earlier, and want to enable both local and cloud-managed connectors, ensure that spec.designerFlowsOperationMode is set to all, and include the parameters for connecting to your App Connect on IBM Cloud instance. Also ensure that spec.license.license is set to a value for a 12.0.3.0-r1 or earlier license, and spec.version is set to a value that resolves to 12.0.3.0-r1 or earlier. For example:

spec:
  license:
    license: SET_TO_12.0.3.0-r1_OR_EARLIER_LICENSE
...
  designerFlowsOperationMode: all
  appConnectURL: 'https://firefly-api-prod.appconnect.ibmcloud.com'
  ibmCloudAPIKeyValue: 123456asdfg789hjklluiop
  appConnectInstanceID: abcde123
...
  version: SET_TO_12.0.3.0-r1_OR_EARLIER_VERSION

Example 1:

apiVersion: appconnect.ibm.com/v1beta1
kind: DesignerAuthoring
metadata:
  name: des-mapast
  namespace: mynamespace
spec:
  license:
    accept: true
    license: L-QECF-MBXVLU
    use: CloudPakForIntegrationNonProduction
  couchdb:
    storage:
      size: 10Gi
      type: persistent-claim
      class: ibmc-block-gold
    replicas: 1
  designerMappingAssist:
    enabled: true
    incrementalLearning:
      schedule: Every 15 days
      storage:
        class: csi-cephfs
        type: persistent-claim
      useIncrementalLearning: true
  useCommonServices: true
  designerFlowsOperationMode: local
  switchServer:
    name: default
  version: 12.0-lts
  replicas: 3

Example 2:

apiVersion: appconnect.ibm.com/v1beta1
kind: DesignerAuthoring
metadata:
  name: des-mapast
  namespace: mynamespace
spec:
  license:
    accept: true
    license: L-QECF-MBXVLU
    use: AppConnectEnterpriseProduction
  couchdb:
    storage:
      size: 10Gi
      type: persistent-claim
      class: valid-storage-class
    replicas: 1
  designerMappingAssist:
    enabled: true
    incrementalLearning:
      schedule: Every 15 days
      storage:
        class: valid-storage-class
        type: persistent-claim
      useIncrementalLearning: true
  useCommonServices: false
  designerFlowsOperationMode: local
  switchServer:
    name: default
  version: 12.0-lts
  replicas: 3

The following examples (Example 3 and Example 4) show a Designer CR with settings to enable local connectors only, and to configure CouchDB storage and a switch server. The settings also enable Mapping Assist and incremental learning with an s3 storage definition for the AI model.

Example 3:

apiVersion: appconnect.ibm.com/v1beta1
kind: DesignerAuthoring
metadata:
  name: des-mapast
  namespace: mynamespace
spec:
  license:
    accept: true
    license: L-QECF-MBXVLU
    use: CloudPakForIntegrationNonProduction
  couchdb:
    storage:
      size: 10Gi
      type: persistent-claim
      class: ibmc-block-gold
    replicas: 1
  designerMappingAssist:
    enabled: true
    incrementalLearning:
      schedule: Every 15 days
      storage:
        bucket: appc-operator-e2e
        host: s3.eu-gb.cloud-object-storage.appdomain.cloud
        s3Configuration: s3credentials-ibmcosiam
        type: s3
      useIncrementalLearning: true
  useCommonServices: true
  designerFlowsOperationMode: local
  switchServer:
    name: default
  version: 12.0-lts
  replicas: 3

Example 4:

apiVersion: appconnect.ibm.com/v1beta1
kind: DesignerAuthoring
metadata:
  name: des-mapast
  namespace: mynamespace
spec:
  license:
    accept: true
    license: L-QECF-MBXVLU
    use: AppConnectEnterpriseProduction
  couchdb:
    storage:
      size: 10Gi
      type: persistent-claim
      class: valid-storage-class
    replicas: 1
  designerMappingAssist:
    enabled: true
    incrementalLearning:
      schedule: Every 15 days
      storage:
        bucket: appc-operator-e2e
        host: s3.eu-gb.cloud-object-storage.appdomain.cloud
        s3Configuration: s3credentials-ibmcosiam
        type: s3
      useIncrementalLearning: true
  useCommonServices: false
  designerFlowsOperationMode: local
  switchServer:
    name: default
  version: 12.0-lts
  replicas: 3

Save this file with a .yaml extension; for example, designer_cr.yaml.
From the command line, log in to your Red Hat OpenShift cluster by using the oc login command.
Run the following command to create the App Connect Designer instance. (Use the name of the .yaml file that you created.)
```
oc apply -f designer_cr.yaml
```

Run the following command to check the status of the App Connect Designer instance and verify that it is ready:

oc get designerauthorings -n namespace

The output will also provide the URL of the Designer instance; for example:

NAME         RESOLVEDVERSION   REPLICAS   CUSTOMIMAGES   STATUS    URL                                                                        AGE
des-mapast   12.0.12.2-r1-lts  3          false          Ready     https://des-mapast-designer-https-mynamespace.apps.acecc-abcde.icp4i.com   50m12s

Share the URL value in the output with users who have access to this namespace, and who will need to use the Designer instance to author flows.

Updating the custom resource settings for an instance

If you want to change the settings of an existing App Connect Designer instance, you can edit its custom resource settings from the IBM Cloud Pak Platform UI, or the Red Hat OpenShift web console or CLI. For example, you might want to enable Mapping Assist if currently disabled, or configure the instance to use a switch server for callable flows.

Restriction: You cannot update standard settings such as the kind of resource (kind), and the name and namespace (metadata.name and metadata.namespace), as well as some system-generated settings, or settings such as the storage type of certain components. An error message will be displayed when you try to save.

Ensure that you have cluster administrator authority or have been granted the appropriate role-based access control (RBAC).

Update options:

Updating an instance from the IBM Cloud Pak Platform UI
Updating an instance from the Red Hat OpenShift web console
Updating an instance from the Red Hat OpenShift CLI

Updating an instance from the IBM Cloud Pak Platform UI

To update an App Connect Designer instance from the IBM Cloud Pak Platform UI, complete the following steps:

From a browser window, log in to the IBM Cloud Pak Platform UI.
Tip: You can use the generated URL for a deployed IBM Cloud Pak for Integration Platform UI instance to access the IBM Cloud Pak Platform UI.

The Platform UI home page opens with cards and navigation menu options that provide access to the instances and other resources that you are authorized to create, manage, or use. For information about completing administration tasks (such as user management or platform customization) from this page, see Platform UI in the IBM Cloud Pak foundational services documentation.
From the navigation menu , expand Administration and click Integration instances.
From the "Integration instances" page, locate the App Connect Designer (Integration design) instance that you want to update.
Click the options icon to open the options menu, and then click Edit. The "Edit" page opens for that instance.
Either use the fields in the "UI form" view or switch to the YAML view to update the required settings. You can update existing values, add new entries, or delete entries. For information about the available parameters and their values, see Custom resource values.
Click Update to save your changes.

Updating an instance from the Red Hat OpenShift web console

To update an App Connect Designer instance by using the Red Hat OpenShift web console, complete the following steps:

Applicable to IBM Cloud Pak for Integration only:
1. If not already logged in, log in to the IBM Cloud Pak Platform UI for your cluster.
2. From the Platform UI home page, click Install operators or OpenShift Container Platform, and log in if prompted.
Applicable to an independent deployment of IBM App Connect Operator only: From a browser window, log in to the Red Hat OpenShift Container Platform web console. Ensure that you are in the Administrator perspective .
From the navigation, click Operators > Installed Operators.
If required, select the namespace (project) in which you installed the IBM App Connect Operator.
From the Installed Operators page, click IBM App Connect.
From the Operator details page for the App Connect Operator, click the Designer Authoring tab.
Locate and click the name of the instance that you want to update.
Click the YAML tab.
Update the content of the YAML editor as required. You can update existing values, add new entries, or delete entries. For information about the available parameters and their values, see Custom resource values.
Click Save to save your changes.

Updating an instance from the Red Hat OpenShift CLI

To update an App Connect Designer instance from the Red Hat OpenShift CLI, complete the following steps.

From the command line, log in to your Red Hat OpenShift cluster by using the oc login command.
From the namespace where the Designer instance is deployed, run the oc edit command to partially update the instance, where instanceName is the name (metadata.name value) of the instance.
```
oc edit designerauthoring instanceName
```
The Designer CR automatically opens in the default text editor for your operating system.
Update the contents of the file as required. You can update existing values, add new entries, or delete entries. For information about the available parameters and their values, see Custom resource values.
Save the YAML definition and close the text editor to apply the changes.

Tip:

If preferred, you can also use the oc patch command to apply a patch with some bash shell features, or use oc apply with the appropriate YAML settings.

For example, you can save the YAML settings to a file with a .yaml extension (for example, updatesettings.yaml), and then run oc patch as follows to update the settings for an instance:

oc patch designerauthoring instanceName --type='merge' --patch "$(cat updatesettings.yaml)"

Deleting an instance

If no longer required, you can delete an App Connect Designer instance. You can do so from the IBM Cloud Pak Platform UI, or the Red Hat OpenShift web console or CLI.

Ensure that you have cluster administrator authority or have been granted the appropriate role-based access control (RBAC).

Note:

If you have an App Connect Designer instance for which incremental learning is enabled with S3 storage, the associated AI model (in ZIP format) will be retained in the S3 bucket when you delete the instance. You can delete the model from the bucket if no longer required.

Delete options:

Deleting an instance from the IBM Cloud Pak Platform UI
Deleting an instance from the Red Hat OpenShift web console
Deleting an instance from the Red Hat OpenShift CLI

Deleting an instance from the IBM Cloud Pak Platform UI

To delete an App Connect Designer instance from the IBM Cloud Pak Platform UI, complete the following steps:

From a browser window, log in to the IBM Cloud Pak Platform UI.
Tip: You can use the generated URL for a deployed IBM Cloud Pak for Integration Platform UI instance to access the IBM Cloud Pak Platform UI.

The Platform UI home page opens with cards and navigation menu options that provide access to the instances and other resources that you are authorized to create, manage, or use. For information about completing administration tasks (such as user management or platform customization) from this page, see Platform UI in the IBM Cloud Pak foundational services documentation.
From the navigation menu , expand Administration and click Integration instances.
From the "Integration instances" page, locate the App Connect Designer (Integration design) instance that you want to delete.
Click the options icon () to open the options menu, and then click Delete.
Confirm the deletion.

Deleting an instance from the Red Hat OpenShift web console

To delete an App Connect Designer instance by using the Red Hat OpenShift web console, complete the following steps:

Applicable to IBM Cloud Pak for Integration only:
1. If not already logged in, log in to the IBM Cloud Pak Platform UI for your cluster.
2. From the Platform UI home page, click Install operators or OpenShift Container Platform, and log in if prompted.
Applicable to an independent deployment of IBM App Connect Operator only: From a browser window, log in to the Red Hat OpenShift Container Platform web console. Ensure that you are in the Administrator perspective .
From the navigation, click Operators > Installed Operators.
If required, select the namespace (project) in which you installed the IBM App Connect Operator.
From the Installed Operators page, click IBM App Connect.
From the Operator details page for the App Connect Operator, click the Designer Authoring tab.
Locate the instance that you want to delete.
Click the options icon () to open the options menu, and then click the Delete option.
Confirm the deletion.

Deleting an instance from the Red Hat OpenShift CLI

To delete an App Connect Designer instance from the Red Hat OpenShift CLI, complete the following steps.

From the command line, log in to your Red Hat OpenShift cluster by using the oc login command.
From the namespace where the Designer instance is deployed, run the following command to delete the instance, where instanceName is the value of the metadata.name parameter.
```
oc delete designerauthoring instanceName
```

Validation for custom resource values

IBM Cloud Pak foundational services (formerly IBM Cloud Platform Common Services) must be enabled for IBM Cloud Pak for Integration. (If using an IBM Cloud Pak licence, set useCommonServices: true.)
Applicable to App Connect Designer 12.0.3.0-r1 or earlier only: If using cloud-managed connectors (specified by using spec.designerFlowsOperationMode: all), the following parameters must all be set:
- spec.appConnectInstanceID
- spec.appConnectURL
- spec.ibmCloudAPIKeyValue or spec.ibmCloudAPIKeySecret
Limits on length of name and namespace when creating resources: To allow for valid routes and child objects with names that are derived from the CR name, limit the length of the CR name:
- If the namespace name is too long, routes will not work. The name value that you specify should be less than maxNameLength always.
- DesignerAuthoring has a smaller maxNameLength than the other custom resources because it creates an integration server.
- Allow 12 characters for suffixes that are added to child resources.
- If a namespace name is 40 characters in length, then 10 characters are available for the CR name for DesignerAuthoring.
A storage class must be provided when using persistent storage with CouchDB.
The number of replicas, storage type, storage class, or storage size of the CouchDB server cannot be modified after creation.

Custom resource values

The following table lists the configurable parameters and default values for the custom resource.

Parameter	Description	Default
apiVersion	The API version that identifies which schema is used for this instance.	`appconnect.ibm.com/v1beta1`
kind	The resource type.	`DesignerAuthoring`
metadata.name	A unique short name by which the Designer instance can be identified.
metadata.namespace	The namespace (project) in which the Designer instance is installed. The namespace in which you create an instance or object must be no more than 40 characters in length.
spec.appConnectInstanceID (Only applicable if spec.version resolves to 12.0.3.0-r1 or earlier)	The instance identifier of the App Connect on IBM Cloud instance that hosts the cloud-managed connectors that will be used when running flows. For information about locating this value, see Prerequisites. Required if spec.designerFlowsOperationMode is set to `all`.
spec.appConnectURL (Only applicable if spec.version resolves to 12.0.3.0-r1 or earlier)	The base URL that is associated with the region where the App Connect on IBM Cloud instance (which hosts the cloud-managed connectors) is provisioned. Specify the value that matches the region: For the us-south or sydney region, specify `https://firefly-api-prod.appconnect.ibmcloud.com`. For the eu-gb region, specify `https://firefly-api-produk.eu-gb.appconnect.ibm.com`. Required if spec.designerFlowsOperationMode is set to `all`.
spec.couchdb.replicas	The number of CouchDB replica pods to run between 1-10.	`3`
spec.couchdb.resources.requests.cpu Deprecated: (Only applicable if spec.version resolves to 12.0.4.0-r2 or earlier)	The minimum number of CPU cores that are allocated for running CouchDB. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core). Tip: If spec.version resolves to 12.0.5.0-r1-lts or later, use spec.pod.containers.couchdb.resources.* instead.	`100m`
spec.couchdb.resources.requests.memory Deprecated: (Only applicable if spec.version resolves to 12.0.4.0-r2 or earlier)	The minimum memory (in bytes) that is allocated for running CouchDB. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki. Tip: If spec.version resolves to 12.0.5.0-r1-lts or later, use spec.pod.containers.couchdb.resources.* instead.	`128Mi`
spec.couchdb.storage.class	A supported storage class for your cluster, which should be used to dynamically provision a persistent volume that belongs to that class. For information about persistent storage requirements for CouchDB, see Supported storage types for Apache CouchDB. (Required if spec.couchdb.storage.type is set to `persistent-claim`.)
spec.couchdb.storage.size	The maximum amount of storage required for a persistent volume for CouchDB in decimal or binary format; that is, Gi or G. (Required if spec.couchdb.storage.type is set to `persistent-claim`.)
spec.couchdb.storage.type	The type of storage to use for CouchDB. Valid values are: `persistent-claim`: Choose this option for storage in a persistent volume in the container’s file system. Retains the existing configuration, logs, and persistent messages when pods restart. `ephemeral`: Choose this option for storage in an ephemeral volume that exists only for the lifetime of the pod. For more information, see Supported storage types for Apache CouchDB.
spec.designerFlowsOperationMode	The set of connectors to use in the App Connect Designer instance: `local`: Enable the use of locally deployed connectors only. `all`: Enable the use of both cloud-managed and locally deployed connectors. To enable access to the cloud-managed connectors, you must also set the following parameters: spec.appConnectInstanceID, spec.appConnectURL, and either spec.ibmCloudAPIKeyValue or spec.ibmCloudAPIKeySecret. Note: This value is available only if spec.version resolves to 12.0.3.0-r1 or earlier.	`local`
spec.designerMappingAssist.enabled	Controls deployment of Mapping Assist components. Valid values are `true` and `false`. For more information about Mapping Assist, see Simplifying data mapping and data transformation with AI-powered suggestions.
spec.designerMappingAssist.incrementalLearning.schedule (Only applicable if spec.version resolves to 12.0.1.0-r1 or later)	Determines how often mapping preferences in the Designer instance are collated and used to retrain the supplied artificial intelligence (AI) model that is used to implement the incremental learning feature. Valid values are `Every 15 days` and `Every month`. Required if spec.designerMappingAssist.incrementalLearning.useIncrementalLearning is set to `true`.	`Every 15 days`
spec.designerMappingAssist.incrementalLearning.storage.bucket (Only applicable if spec.version resolves to 12.0.1.0-r4 or later)	The name of an existing bucket that is used for object storage in a Simple Storage Service (S3) instance. You must have read/write access to this bucket, which will be used to store the trained AI model for the incremental learning feature. For a list of supported S3 providers and considerations for choosing a bucket, see Supported storage types for the AI model. Required if spec.designerMappingAssist.incrementalLearning.useIncrementalLearning is set to `true` and spec.designerMappingAssist.incrementalLearning.storage.type is set to `s3`.
spec.designerMappingAssist.incrementalLearning.storage.claimName (Only applicable if spec.version resolves to 12.0.1.0-r1 or later)	The name of an existing claim that should be used to request a persistent volume (with ReadWriteMany access mode) for storing the AI model for the incremental learning feature. This claim must exist in the same namespace as App Connect Designer. When spec.designerMappingAssist.incrementalLearning.useIncrementalLearning is set to `true` and spec.designerMappingAssist.incrementalLearning.storage.type is set to `persistent-claim`, either spec.designerMappingAssist.incrementalLearning.storage.class or spec.designerMappingAssist.incrementalLearning.storage.claimName is required.
spec.designerMappingAssist.incrementalLearning.storage.class (Only applicable if spec.version resolves to 12.0.1.0-r1 or later)	A supported storage class for your cluster, which should be used to dynamically provision a persistent volume that belongs to that class. Incremental learning requires a persistent volume with ReadWriteMany access mode for storing the trained AI model. If using IBM Cloud, set the storage class to `ibmc-file-gold-gid` for best performance. For more information about requirements for the persistent volume, see Supported storage types for the AI model. When spec.designerMappingAssist.incrementalLearning.useIncrementalLearning is set to `true` and spec.designerMappingAssist.incrementalLearning.storage.type is set to `persistent-claim`, either spec.designerMappingAssist.incrementalLearning.storage.class or spec.designerMappingAssist.incrementalLearning.storage.claimName is required.
spec.designerMappingAssist.incrementalLearning.storage.host (Only applicable if spec.version resolves to 12.0.1.0-r4 or later)	An endpoint associated with your Simple Storage Service (S3) system, to which the S3 REST API sends requests for reading from and writing to the AI model in the bucket specified in spec.designerMappingAssist.incrementalLearning.storage.bucket. For more information, see Supported storage types for the AI model. Required if spec.designerMappingAssist.incrementalLearning.useIncrementalLearning is set to `true` and spec.designerMappingAssist.incrementalLearning.storage.type is set to `s3`.
spec.designerMappingAssist.incrementalLearning.storage.s3Configuration (Only applicable if spec.version resolves to 12.0.1.0-r4 or later)	The name of an existing configuration object of type `S3Credentials`, which stores credentials for accessing the bucket specified in spec.designerMappingAssist.incrementalLearning.storage.bucket. Set this parameter to the metadata.name value that was specified while creating the configuration object. For more information, see Creating a configuration of type S3Credentials for use with App Connect Designer. Required if spec.designerMappingAssist.incrementalLearning.useIncrementalLearning is set to `true` and spec.designerMappingAssist.incrementalLearning.storage.type is set to `s3`.
spec.designerMappingAssist.incrementalLearning.storage.type (Only applicable if spec.version resolves to 12.0.1.0-r4 or later)	The type of storage to use for storing the AI model for the incremental learning feature. Valid values are: `persistent-claim`: Choose this option for storage in a persistent volume in the container’s file system. `s3`: Choose this option for storage in a bucket in a Simple Storage Service (S3) instance. For more information, see Supported storage types for the AI model.
spec.designerMappingAssist.incrementalLearning.useIncrementalLearning (Only applicable if spec.version resolves to 12.0.1.0-r1 or later)	Indicates whether to enable the incremental learning feature, which uses AI modeling to periodically analyze mapping preferences in authored flows and memorize patterns in order to improve the accuracy of suggested mappings. This feature will use an additional 3 CPU and 3Gi of memory. Valid values are `true` and `false`. For more information about incremental learning, see Simplifying data mapping and data transformation with AI-powered suggestions.	`false`
spec.ibmCloudAPIKey Deprecated: (Only applicable if spec.version resolves to 11.0.0.9-r3 or earlier)	Superseded by spec.ibmCloudAPIKeyValue. The spec.ibmCloudAPIKey parameter is retained for backward compatibility only.
spec.ibmCloudAPIKeySecret (Only applicable if spec.version resolves to 11.0.0.10-r1 or a later version up to 12.0.3.0-r1)	The name of an auto-generated or manually created secret that stores the IBM Cloud API key, which provides access to your App Connect on IBM Cloud instance. Required when spec.designerFlowsOperationMode is set to `all`, and spec.ibmCloudAPIKeyValue is either not specified or is set to `ProvideAsASecretInIBMCloudAPIKeySecret`. The IBM Cloud API key needs to be stored in a secret to keep its value secure. You can either create your own secret, or have the IBM App Connect Operator create one for you: If you specify an IBM Cloud API key in spec.ibmCloudAPIKeyValue (without manually creating a secret), when the Designer instance is created, a secret is automatically created to store the IBM Cloud API key and the secret name is assigned to spec.ibmCloudAPIKeySecret. The secret name is generated as `instanceName-apikey-generatedCharacters`, where `instanceName` is the metadata.name value. Also, spec.ibmCloudAPIKeyValue is then automatically updated to `ProvideAsASecretInIBMCloudAPIKeySecret`. If spec.ibmCloudAPIKeyValue is unspecified or set to `ProvideAsASecretInIBMCloudAPIKeySecret`, you must create a secret to store the IBM Cloud API key, as described in Prerequisites. Assign this secret name to spec.ibmCloudAPIKeySecret.
spec.ibmCloudAPIKeyValue (Only applicable if spec.version resolves to 11.0.0.10-r1 or a later version up to 12.0.3.0-r1)	An IBM Cloud API key that is generated under the same IBM Cloud account as your App Connect on IBM Cloud instance. This key will be used to authenticate to that cloud instance. For information about generating an IBM Cloud API key, see Prerequisites. Required when spec.designerFlowsOperationMode is set to `all`, and spec.ibmCloudAPIKeySecret is not specified. If you specify an IBM Cloud API key in spec.ibmCloudAPIKeyValue (without manually creating a secret), when the Designer instance is created, a secret is automatically created to store the IBM Cloud API key and the secret name is assigned to spec.ibmCloudAPIKeySecret. The secret name is generated as `instanceName-apikey-generatedCharacters`, where `instanceName` is the metadata.name value. Also, spec.ibmCloudAPIKeyValue is then automatically updated to `ProvideAsASecretInIBMCloudAPIKeySecret`.
spec.imagePullSecrets.name	An optional list of references to secrets in the same namespace to use for pulling any of the images used. If specified, these secrets will be passed to individual puller implementations for them to use. For example, in the case of Docker, only DockerConfig type secrets are honored. For more information, see https://kubernetes.io/docs/concepts/containers/images#specifying-imagepullsecrets-on-a-pod.
spec.integrationServer.containers.connectors.image (Only applicable if spec.version resolves to 11.0.0.10-r2 or earlier)	The path to the Docker image.
spec.integrationServer.containers.connectors.imagePullPolicy (Only applicable if spec.version resolves to 11.0.0.10-r2 or earlier)	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.integrationServer.containers.connectors.resources.limits.cpu (Only applicable if spec.version resolves to 11.0.0.10-r2 or earlier)	The upper limit of CPU core. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.integrationServer.containers.connectors.resources.limits.memory (Only applicable if spec.version resolves to 11.0.0.10-r2 or earlier)	The memory upper limit in bytes. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`512Mi`
spec.integrationServer.containers.connectors.resources.requests.cpu (Only applicable if spec.version resolves to 11.0.0.10-r2 or earlier)	The minimum required CPU core. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`250m`
spec.integrationServer.containers.connectors.resources.requests.memory (Only applicable if spec.version resolves to 11.0.0.10-r2 or earlier)	The minimum memory in bytes. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.integrationServer.containers.designereventflows.image (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The path to the Docker image.
spec.integrationServer.containers.designereventflows.imagePullPolicy (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.integrationServer.containers.designereventflows.resources.limits.cpu (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The upper limit of CPU core. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.integrationServer.containers.designereventflows.resources.limits.memory (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The memory upper limit in bytes. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`512Mi`
spec.integrationServer.containers.designereventflows.resources.requests.cpu (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The minimum required CPU core. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`250m`
spec.integrationServer.containers.designereventflows.resources.requests.memory (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The minimum memory in bytes. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.integrationServer.containers.designerflows.image	The path to the Docker image.
spec.integrationServer.containers.designerflows.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.integrationServer.containers.designerflows.resources.limits.cpu	The upper limit of CPU core. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.integrationServer.containers.designerflows.resources.limits.memory	The memory upper limit in bytes. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`512Mi`
spec.integrationServer.containers.designerflows.resources.requests.cpu	The minimum required CPU core. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`250m`
spec.integrationServer.containers.designerflows.resources.requests.memory	The minimum memory in bytes. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.integrationServer.containers.proxy.image (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The path to the Docker image.
spec.integrationServer.containers.proxy.imagePullPolicy (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.integrationServer.containers.proxy.resources.limits.cpu (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The upper limit of CPU core. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.integrationServer.containers.proxy.resources.limits.memory (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The memory upper limit in bytes. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.integrationServer.containers.proxy.resources.requests.cpu (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The minimum required CPU core. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.integrationServer.containers.proxy.resources.requests.memory (Only applicable if spec.version resolves to 11.0.0.10-r3-eus, 11.0.0.11-r1, or later)	The minimum memory in bytes. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.integrationServer.containers.runtime.image	The path to the Docker image.
spec.integrationServer.containers.runtime.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.integrationServer.containers.runtime.resources.limits.cpu	The upper limit of CPU core. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.integrationServer.containers.runtime.resources.limits.memory	The memory upper limit in bytes. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1Gi`
spec.integrationServer.containers.runtime.resources.requests.cpu	The minimum required CPU core. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`200m`
spec.integrationServer.containers.runtime.resources.requests.memory	The minimum memory in bytes. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.license.accept	An indication of whether the license should be accepted. Valid values are `true` and `false`. To install, this value must be set to `true`.	`false`
spec.license.license	See Licensing reference for IBM App Connect Operator for the valid values.
spec.license.use	See Licensing reference for IBM App Connect Operator for the valid values. If using an IBM Cloud Pak for Integration license, spec.useCommonServices must be set to `true`.
spec.pod.containers.connectorAuthService.image	The path to the Docker image.
spec.pod.containers.connectorAuthService.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.connectorAuthService.livenessProbe.failureThreshold	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.connectorAuthService.livenessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`30`
spec.pod.containers.connectorAuthService.livenessProbe.periodSeconds	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`5`
spec.pod.containers.connectorAuthService.livenessProbe.timeoutSeconds	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`3`
spec.pod.containers.connectorAuthService.readinessProbe.failureThreshold	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.connectorAuthService.readinessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`30`
spec.pod.containers.connectorAuthService.readinessProbe.periodSeconds	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`5`
spec.pod.containers.connectorAuthService.readinessProbe.timeoutSeconds	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`3`
spec.pod.containers.connectorAuthService.resources.limits.cpu	The upper limit of CPU core that is allocated for running the connector auth service container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.connectorAuthService.resources.limits.memory	The memory upper limit in bytes that is allocated for running the connector auth service container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.connectorAuthService.resources.requests.cpu	The minimum required CPU core that is allocated for running the connector auth service container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.pod.containers.connectorAuthService.resources.requests.memory	The minimum memory in bytes that is allocated for running the connector auth service container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.pod.containers.couchdb.image (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The path to the Docker image.
spec.pod.containers.couchdb.imagePullPolicy (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.couchdb.livenessProbe.failureThreshold (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The number of times the liveness probe (which checks whether the CouchDB container is still running) can fail before taking action.	`1`
spec.pod.containers.couchdb.livenessProbe.initialDelaySeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How long to wait (in seconds) before starting the liveness probe, which checks whether the CouchDB container is still running. Increase this value if your system cannot start the container in the default time period.	`30`
spec.pod.containers.couchdb.livenessProbe.periodSeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How often (in seconds) to perform the liveness probe that checks whether the CouchDB container is still running.	`5`
spec.pod.containers.couchdb.livenessProbe.timeoutSeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How long (in seconds) before the liveness probe (which checks whether the CouchDB container is still running) times out.	`3`
spec.pod.containers.couchdb.readinessProbe.failureThreshold (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The number of times the readiness probe (which checks whether the CouchDB container is ready) can fail before taking action.	`1`
spec.pod.containers.couchdb.readinessProbe.initialDelaySeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How long to wait (in seconds) before starting the readiness probe, which checks whether the CouchDB container is ready.	`30`
spec.pod.containers.couchdb.readinessProbe.periodSeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How often (in seconds) to perform the readiness probe that checks whether the CouchDB container is ready.	`5`
spec.pod.containers.couchdb.readinessProbe.timeoutSeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How long (in seconds) before the readiness probe (which checks whether the CouchDB container is ready) times out.	`3`
spec.pod.containers.couchdb.resources.limits.cpu (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The upper limit of CPU core that is allocated for running the CouchDB container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.couchdb.resources.limits.memory (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The memory upper limit in bytes that is allocated for running the CouchDB container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.couchdb.resources.requests.cpu (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The minimum required CPU core that is allocated for running the CouchDB container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.pod.containers.couchdb.resources.requests.memory (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The minimum memory in bytes that is allocated for running the CouchDB container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.pod.containers.couchdb.startupProbe.failureThreshold (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The minimum consecutive failures for the probe to be considered failed after having succeeded. For more information about startup probes, see Protect slow starting containers with startup probes in the Kubernetes documentation.	`150`
spec.pod.containers.couchdb.startupProbe.initialDelaySeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The number of seconds after the CouchDB container has started before liveness probes are initiated. For more information, see Container probes.	`0`
spec.pod.containers.couchdb.startupProbe.periodSeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	How often (in seconds) to perform the probe.	`2`
spec.pod.containers.couchdb.startupProbe.timeoutSeconds (Only applicable if spec.version resolves to 12.0.5.0-r1-lts or later)	The number of seconds after which the probe times out. For more information, see Container probes.	`1`
spec.pod.containers.flowdocAuthoring.image (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The path to the Docker image.
spec.pod.containers.flowdocAuthoring.imagePullPolicy (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.flowdocAuthoring.livenessProbe.failureThreshold (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.flowdocAuthoring.livenessProbe.initialDelaySeconds (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`30`
spec.pod.containers.flowdocAuthoring.livenessProbe.periodSeconds (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`5`
spec.pod.containers.flowdocAuthoring.livenessProbe.timeoutSeconds (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`3`
spec.pod.containers.flowdocAuthoring.readinessProbe.failureThreshold (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.flowdocAuthoring.readinessProbe.initialDelaySeconds (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`30`
spec.pod.containers.flowdocAuthoring.readinessProbe.periodSeconds (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`5`
spec.pod.containers.flowdocAuthoring.readinessProbe.timeoutSeconds (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`3`
spec.pod.containers.flowdocAuthoring.resources.limits.cpu (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The upper limit of CPU core that is allocated for running the flow doc authoring container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.flowdocAuthoring.resources.limits.memory (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The memory upper limit in bytes that is allocated for running the flow doc authoring container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.flowdocAuthoring.resources.requests.cpu (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The minimum required CPU core. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.pod.containers.flowdocAuthoring.resources.requests.memory (Only applicable if spec.version resolves to 12.0.11.3-r1-lts or earlier)	The minimum memory in bytes that is allocated for running the flow doc authoring container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.pod.containers.flowTestManager.image	The path to the Docker image.
spec.pod.containers.flowTestManager.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.flowTestManager.livenessProbe.failureThreshold	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.flowTestManager.livenessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`30`
spec.pod.containers.flowTestManager.livenessProbe.periodSeconds	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`5`
spec.pod.containers.flowTestManager.livenessProbe.timeoutSeconds	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`3`
spec.pod.containers.flowTestManager.readinessProbe.failureThreshold	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.flowTestManager.readinessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`30`
spec.pod.containers.flowTestManager.readinessProbe.periodSeconds	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`5`
spec.pod.containers.flowTestManager.readinessProbe.timeoutSeconds	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`3`
spec.pod.containers.flowTestManager.resources.limits.cpu	The upper limit of CPU core that is allocated for running the flow test manager container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.flowTestManager.resources.limits.memory	The memory upper limit in bytes that is allocated for running the flow test manager container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.flowTestManager.resources.requests.cpu	The minimum required CPU core that is allocated for running the flow test manager container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.pod.containers.flowTestManager.resources.requests.memory	The minimum memory in bytes that is allocated for running the flow test manager container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.pod.containers.mappingAssist.image	The path to the Docker image.
spec.pod.containers.mappingAssist.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.mappingAssist.livenessProbe.failureThreshold	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.mappingAssist.livenessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`30`
spec.pod.containers.mappingAssist.livenessProbe.periodSeconds	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`5`
spec.pod.containers.mappingAssist.livenessProbe.timeoutSeconds	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`3`
spec.pod.containers.mappingAssist.readinessProbe.failureThreshold	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.mappingAssist.readinessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`30`
spec.pod.containers.mappingAssist.readinessProbe.periodSeconds	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`5`
spec.pod.containers.mappingAssist.readinessProbe.timeoutSeconds	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`3`
spec.pod.containers.mappingAssist.resources.limits.cpu	The upper limit of CPU core that is allocated for running the Mapping Assist container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`2300m`
spec.pod.containers.mappingAssist.resources.limits.memory	The memory upper limit in bytes that is allocated for running the Mapping Assist container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`2765Mi`
spec.pod.containers.mappingAssist.resources.requests.cpu	The minimum required CPU core that is allocated for running the Mapping Assist container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`800m`
spec.pod.containers.mappingAssist.resources.requests.memory	The minimum memory in bytes that is allocated for running the Mapping Assist container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`900Mi`
spec.pod.containers.proxy.image	The path to the Docker image.
spec.pod.containers.proxy.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.proxy.livenessProbe.failureThreshold	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.proxy.livenessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`60`
spec.pod.containers.proxy.livenessProbe.periodSeconds	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`5`
spec.pod.containers.proxy.livenessProbe.timeoutSeconds	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`3`
spec.pod.containers.proxy.readinessProbe.failureThreshold	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.proxy.readinessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`5`
spec.pod.containers.proxy.readinessProbe.periodSeconds	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`5`
spec.pod.containers.proxy.readinessProbe.timeoutSeconds	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`3`
spec.pod.containers.proxy.resources.limits.cpu	The upper limit of CPU core that is allocated for running the Designer proxy container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.proxy.resources.limits.memory	The memory upper limit in bytes that is allocated for running the Designer proxy container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.proxy.resources.requests.cpu	The minimum required CPU core that is allocated for running the Designer proxy container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`200m`
spec.pod.containers.proxy.resources.requests.memory	The minimum memory in bytes that is allocated for running the Designer proxy container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.pod.containers.runtime.image	The path to the Docker image.
spec.pod.containers.runtime.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.runtime.livenessProbe.failureThreshold	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.runtime.livenessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`30`
spec.pod.containers.runtime.livenessProbe.periodSeconds	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`5`
spec.pod.containers.runtime.livenessProbe.timeoutSeconds	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`3`
spec.pod.containers.runtime.readinessProbe.failureThreshold	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.runtime.readinessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`30`
spec.pod.containers.runtime.readinessProbe.periodSeconds	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`5`
spec.pod.containers.runtime.readinessProbe.timeoutSeconds	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`3`
spec.pod.containers.runtime.resources.limits.cpu	The upper limit of CPU core that is allocated for running the Designer runtime container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.runtime.resources.limits.memory	The memory upper limit in bytes that is allocated for running the Designer runtime container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.runtime.resources.requests.cpu	The minimum required CPU core that is allocated for running the Designer runtime container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.pod.containers.runtime.resources.requests.memory	The minimum memory in bytes that is allocated for running the Designer runtime container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.pod.containers.ui.image	The path to the Docker image.
spec.pod.containers.ui.imagePullPolicy	corev1.PullPolicy Indicate whether you want images to be pulled every time, never, or only if they're not present. Valid values are `Always`, `Never`, and `IfNotPresent`.	`IfNotPresent`
spec.pod.containers.ui.livenessProbe.failureThreshold	The number of times the liveness probe (which checks whether the container is still running) can fail before taking action.	`1`
spec.pod.containers.ui.livenessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the liveness probe, which checks whether the container is still running. Increase this value if your system cannot start the container in the default time period.	`60`
spec.pod.containers.ui.livenessProbe.periodSeconds	How often (in seconds) to perform the liveness probe that checks whether the container is still running.	`30`
spec.pod.containers.ui.livenessProbe.timeoutSeconds	How long (in seconds) before the liveness probe (which checks whether the container is still running) times out.	`10`
spec.pod.containers.ui.readinessProbe.failureThreshold	The number of times the readiness probe (which checks whether the container is ready) can fail before taking action.	`1`
spec.pod.containers.ui.readinessProbe.initialDelaySeconds	How long to wait (in seconds) before starting the readiness probe, which checks whether the container is ready.	`60`
spec.pod.containers.ui.readinessProbe.periodSeconds	How often (in seconds) to perform the readiness probe that checks whether the container is ready.	`2`
spec.pod.containers.ui.readinessProbe.timeoutSeconds	How long (in seconds) before the readiness probe (which checks whether the container is ready) times out.	`10`
spec.pod.containers.ui.resources.limits.cpu	The upper limit of CPU core that is allocated for running the Designer UI container. Specify integers, fractions (for example, 0.5), or millicores values (for example, 100m, where 100m is equivalent to .1 core).	`1`
spec.pod.containers.ui.resources.limits.memory	The memory upper limit in bytes that is allocated for running the Designer UI container. Specify integers with suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`1024Mi`
spec.pod.containers.ui.resources.requests.cpu	The minimum required CPU core that is allocated for running the Designer UI container. Specify integers, fractions (for example, 0.5), or millicore values (for example, 100m, where 100m is equivalent to .1 core).	`100m`
spec.pod.containers.ui.resources.requests.memory	The minimum memory in bytes that is allocated for running the Designer UI container. Specify integers with one of these suffixes: E, P, T, G, M, K, or power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki.	`256Mi`
spec.replicas	The number of replica pods to run for each deployment. A number between 1-10.	`3`
spec.switchServer.name	The name of an existing switch server that was created to configure secure connectivity when running callable flows in the Designer instance. For information about how to create a switch server, see App Connect Switch Server reference.
spec.useCommonServices	An indication of whether to enable use of IBM Cloud Pak foundational services (formerly IBM Cloud Platform Common Services). Valid values are `true` and `false`. Must be set to `true` if using an IBM Cloud Pak for Integration license (specified via spec.license.use). Can be set to `true` or `false` if using an App Connect Enterprise license. Applicable only if spec.version resolves to 11.0.0.11-r2 or later: When set to `true`, only essential IBM Cloud Pak foundational services are requested, which means that only the Identity and Access Management (IAM) service is installed by default, together with a Common UI component that provides a login page for secure access to the instance.	`true`
spec.version	The product version that the Designer instance is based on. Can be specified by using a channel or as a fully qualified version. If you specify a channel, you must ensure that the license aligns with the latest fully qualified version in the channel. If you are using IBM App Connect Operator 5.0.4 or later, the supported channels or versions will depend on the Red Hat OpenShift version that is installed in your cluster. To view the available values that you can choose from, see spec.version values.	`12.0-lts`

Supported platforms

Red Hat OpenShift: Supports the amd64 and ppc64le CPU architectures, although the Mapping Assist component is unsupported on ppc64le. For more information, see Supported platforms.