IBM C1000-173 Exam Dumps

According to the IBM Cloud Pak for Data 4.7 Installation Guide and official IBM documentation, when deploying Cloud Pak for Data (CP4D) via a cloud provider marketplace (such as Red Hat OpenShift OperatorHub or a cloud marketplace), the deployment process offers an automated installation method that simplifies the setup. However, there are certain limitations and manual steps that may be required during the initial installation phase.

CP4D supports installation on an existing OpenShift Container Platform cluster, so option A is incorrect.

Some core services and operators, including foundational services, can be installed automatically via operators, so option B is incorrect.

Cloud Pak for Data operators and IBM foundational services operators can coexist in the same OpenShift cluster, so option C is incorrect.

The official installation documentation for version 4.7 specifies that the initial installation requires manual intervention for partial installation --- for example, manually setting up foundational services or configuring specific operators before automated installation of the rest of the platform can continue smoothly. This partial manual setup is especially relevant when using marketplace deployment to ensure all prerequisites and configurations are met.

Exact extract from IBM Cloud Pak for Data 4.7 Installation documentation:

'When deploying Cloud Pak for Data via the OperatorHub or cloud marketplace, the initial setup requires manual installation of foundational services operators and configuration of the cluster environment before proceeding with the automated installation of Cloud Pak for Data services. This partial manual step ensures proper configuration and avoids conflicts during automated deployment.'

--- IBM Cloud Pak for Data Installation Guide v4.7, section 'Installing from OperatorHub and Marketplace'

IBM Cloud Pak for Data 4.7 Installation Guide (https://www.ibm.com/docs/en/cloud-paks/cp-data/4.7?topic=deployment-installing-from-operatorhub-marketplace)

IBM Knowledge Center for Cloud Pak for Data 4.7

In air-gapped (offline) environments, it's not just the container images that require preparation. Package managers like pip (for Python) and other utilities commonly attempt to pull dependencies from public internet repositories. These must be redirected to internal mirrors or handled via offline bundles. If left unaddressed, certain operations within components like Jupyter notebooks, Watson Studio, or pipelines may fail. License validation and monitoring do not inherently require internet access, and data movement between nodes is part of normal cluster function---not something to be blocked.

Configuring access to a Git repository in Cloud Pak for Data projects allows teams to collaborate on code, notebooks, and assets while benefiting from version control and branching. This setup ensures that all project files can be tracked, reverted, or merged, enabling collaborative development and continuous integration workflows. It is not used for model deployment management (B) or visualization enhancements (C). Option D is unrelated to the actual purpose of Git integration.

Collaborators in IBM Knowledge Catalog are granted access to data assets that have been properly governed and made available through connections. Once a connection is established by an administrator or asset owner, users with collaborator roles can access the data without needing to re-enter credentials. This simplifies secure data consumption and aligns with enterprise access control policies. They do not see underlying credentials, and access is not limited to document types like PDFs.

'You can create a maximum of 10 instances per deployment. After you reach the maximum number, the New instance button is not displayed in IBM Cloud Pak for Data.'