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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.

IBM Cloud Pak for Data supports NFS‑backed persistent volumes (RWX storage class) for services that require access to shared file storage. Among the available services, IBM Knowledge Catalog and Watson Discovery are known to support NFS storage classes in installation configuration (e.g. “managed‑nfs‑storage”) for persistent metadata and document storage. Other services like watsonx Assistant, Watson Knowledge Studio, and Planning Analytics use different storage mechanisms and do not necessarily support NFS shared storage in the standard CP4D 4.7 deployment.

You can use the IBM Software Hub monitoring and alerting framework to monitor the state of the platform. You can set up events to alert when action is needed, based on thresholds that you define.

By default, IBM Software Hub is initialized with one monitor that runs every ten minutes. The diagnostic monitor records the status of deployments, StatefulSets, and persistent volume claims. It also tracks your system usage of virtual processors (vCPUs) and memory. The data that is collected can be used for analysis and to alert customers in a production environment based on set alert rules.

"You can create a maximum of10instances per deployment. After you reach the maximum number, the New instance button is not displayed in IBM Cloud Pak for Data."

Applications interact with Db2 Big SQL using industry-standard protocols. The most common and supported interface is through a REST (Representative State Transfer) API endpoint. REST endpoints allow for external applications to query, manage, and manipulate data within Big SQL using simple HTTP calls. None of the other options—SLEEP, SNORE, or DREAM—are valid or recognized interfaces in IBM Cloud Pak for Data or Db2 Big SQL documentation.

The Audit Logging service in IBM Cloud Pak for Data uses Fluentd as the core log forwarding mechanism. Fluentd output plug-ins are configured to route audit logs to external SIEM systems such as Splunk or QRadar. These plug-ins are versatile and support multiple formats and transport protocols. Other options listed—like Logstash, OSS/J, or Kafka—are not the designated default forwarding mechanisms used within the CP4D Audit Logging architecture.

For Cloud Pak for Data deployed on a FIPS-enabled cluster, the supported method for backup and restore is the online backup and restore to the same cluster. This method ensures that the data and configuration remain compliant with FIPS encryption standards. Offline and cross-cluster restore methods are not supported under FIPS constraints due to strict requirements around key handling and encryption. The Snap and Restore Tool and Watson Backup Assistant are not applicable to this context.

In IBM Cloud Pak for Data, DataStage access is managed using predefined roles that grant specific permissions. The DataStage Developer role is explicitly designed to allow users to create and manage DataStage flows. The Data Steward role is involved in managing data access, lineage, and metadata, which supports governance aspects within DataStage projects. Business Analyst and Governance Steward roles are focused on cataloging and governance workflows, not DataStage design or execution. Reporting Administrator is not applicable in this context.

For environments deployed via automated cloud options (such as Azure or AWS), upgrades are performed using the Command Line Interface (CLI). The CLI allows administrators to pull the latest operators, update foundational services, and upgrade installed services. The cloud marketplace is used only for initial provisioning, not for upgrades. PowerShell and GitHub repositories are not used as upgrade mechanisms within the official CP4D deployment lifecycle.

Within IBM Knowledge Catalog as part of IBM Cloud Pak for Data, governing data lakes is enabled via integration with Data Virtualization. This approach supports automated data discovery, cataloging, tagging, and virtualization, allowing users to access enterprise data virtually—without physical movement. Policies and governance metadata are applied automatically to virtualized assets, enabling secure and efficient data consumption. Manual processes are not required for discovery, and data is masked selectively based on policies—not completely masked without user intervention. Thus automation and virtualization are central, making statement B correct.