Enabling the IBM App Connect Enterprise Agent in an App Connect Dashboard instance
You can enable the IBM® App Connect Enterprise Agent in an App Connect Dashboard instance by adding parameters to the Dashboard custom resource (CR) to configure the Agent.
Before you begin
- Review the prerequisites and limitations for the Agent.
- Collate the following credentials for your IBM
watsonx.ai Runtime service that hosts the large language models (LLMs) for the Agent.
- The watsonx.ai host URL
- The watsonx.ai project ID
- The watsonx.ai API key
For more information, see Prerequisite requirements for the IBM App Connect Enterprise Agent.
- If you want to implement identity and access management (IAM) by using Keycloak to control access to the Dashboard instance, ensure that the prerequisites for IAM are met. For more information, see Implementing identity and access management for App Connect Designer and App Connect Dashboard instances.
- Ensure that you have cluster administrator authority with
cluster-adminpermissions, or have been granted the appropriate role-based access control (RBAC) to administer the cluster.
About this task
You can enable the Agent when you create a Dashboard instance or you can update the CR of an existing Dashboard instance to enable the Agent. You need to also provide a secret that stores your watsonx.ai credentials. Create this secret before you create a Dashboard instance or before you update an existing Dashboard CR.
You can enable the Agent from the Red Hat® OpenShift® web console, or from the Red Hat OpenShift or Kubernetes CLI.
Procedure
To enable the Agent in a new or an existing Dashboard instance, complete the following steps:
Results
After the Dashboard is created or updated, your cluster is configured as follows for the Agent:
- Agent artifacts, which include the following
resources, are created in the same namespace where the Dashboard is deployed:
- An Agent deployment, which is named in the format
dashboardName-aiagent; for example,db-fd-rc1-aiagent - A pod that is named in the format
dashboardName-aiagent-generatedID(within the deployment); for example,db-fd-rc1-aiagent-77bfbd49f6-grjp2This pod contains the following containers:ace-embedding-service: The App Connect Enterprise Embedding Service container provides AI-powered capabilities that generate vector embeddings for improved semantic searching when using the Agent.This container is available in Dashboard instances at version 13.0.8.1-r1 or later only.
acemcp: The Model Context Protocol (MCP) server container provides tools for retrieving information about your App Connect containers and the environment that they are running in.langgraph: The LangGraph container runs and manages the Agent workflows, and maintains context by recording the input, output, and steps in the chat sessions.
If needed, you can update the default values for theace-embedding-service,acemcp, andlanggraphcontainers by updating the following settings in the Dashboard CR. For example, you might want to adjust the CPU or memory limits or requests. For more information, see App Connect Dashboard reference: Custom resource values.- spec.pod.containers.ace-embedding-service.*
- spec.pod.containers.acemcp.*
- spec.pod.containers.langgraph.*
- An Agent deployment, which is named in the format
- A connection is configured to enable the Agent deployment to authenticate and connect to a designated IBM watsonx.ai Runtime service to access hosted LLMs that are used for inferencing.
- In the Dashboard UI, a chat button is activated for the Agent. You can use the chat button to open a chat window that provides responses to your questions.
What to do next
Access the App Connect Dashboard UI to interact with the Agent from a chat window.