IBM Cloud Pak for Data v4.x Solution Architect Advanced Practice Exam: Hard Questions 2025

An enterprise is designing IBM Cloud Pak for Data (CP4D) on Red Hat OpenShift across two data centers for high availability. They want CP4D services to tolerate loss of a single data center with minimal recovery time, while keeping user access endpoints stable. Which architecture best aligns with these requirements without relying on a stretched OpenShift cluster?

A CP4D platform team is sizing and planning for a multi-tenant deployment. Several lines of business will run independent projects with strict isolation and different lifecycle cadences. Security requires that admin privileges be delegated per tenant and that operational blast radius be minimized (upgrades, quotas, and failures). Which design best meets these constraints while staying aligned with OpenShift and CP4D operating models?

After a CP4D upgrade, the platform works, but users report intermittent failures when accessing CP4D routes through the corporate ingress layer. Direct access to OpenShift routes from inside the cluster succeeds. The network team confirms TLS re-encryption at the edge and a strict enterprise proxy. Which troubleshooting approach is MOST likely to identify the root cause efficiently?

A team uses Data Virtualization (DV) to federate queries across Db2, Oracle, and a cloud object store. A critical dashboard intermittently times out only when filtering on a date range; other filters perform well. Query plans show large remote scans. They cannot replicate data due to governance constraints, but they can change DV configuration and modeling. What is the BEST next action to improve performance while preserving virtualization?

A platform integrates CP4D with an enterprise Kafka bus. They ingest streaming data into analytics workloads and also expose curated data through DV. Under load, DV queries that include recently ingested attributes return inconsistent results compared to the curated tables, even though schemas appear aligned. The architecture uses schema evolution in Kafka and automatic mapping downstream. What is the MOST likely design gap and best corrective action?

An organization uses Watson Knowledge Catalog (WKC) with multiple catalogs: one for raw data, one for curated data, and one for regulated data. They want lineage to remain accurate when datasets are promoted from raw to curated and when DV views are created on curated assets. Auditors require that the lineage clearly shows transformation responsibility and approvals. Which approach best satisfies this requirement?

A data steward defines policies so that PII columns are masked for most users but fully visible for a small compliance team. Some consumers access the data through curated tables, others through DV views, and some through notebook workloads. After policy rollout, PII is still visible in certain DV queries executed by power users, but not in the catalog preview. What is the most plausible cause and the best resolution?

A regulated bank needs to train an AI model using CP4D services. They must ensure training data is restricted to approved, cataloged datasets, and that the resulting model can be promoted to production only after passing bias and explainability checks. They also need to reproduce any past model version with its training data snapshot and feature definitions. Which solution design best meets these requirements?

A team deploys a real-time scoring service for a fraud model. The service must handle bursty traffic and maintain consistent latency. During bursts, requests queue and eventually time out; cluster metrics show CPU headroom but high network and storage latency. The model uses large reference data loaded at startup and periodically refreshed. What is the BEST architectural change to improve latency and resilience under bursts?

A CP4D administrator integrates the platform with an enterprise IdP using OIDC. Authentication works, but authorization is inconsistent: users intermittently lose access to projects and catalogs after logging in, and group-based entitlements appear to change between sessions. The IdP team notes that group membership is returned via a nested claim and can exceed token size limits for some users. What is the MOST appropriate fix?