IBM Cloud Pak for Data v4.7 Architect study plan

Map every Cloud Pak for Data v4.7 component (control plane, Zen/Cloud Pak for Data control plane, platform services, and the analytics services catalog) into a one-page diagram you draw from memory, labeling which services are installable independently and which require the control plane first.

Explain out loud, without notes, how the platform operator, the Cloud Pak for Data operator, and the per-service operators relate, and where the operand CRs live in the namespace model.

Compare the reference architectures for a small single-cluster deployment versus a multi-namespace, multi-instance design, and justify when a dedicated instance is warranted.

List the supported storage classes and the persistence requirements (ReadWriteMany needs for shared services versus ReadWriteOnce for single-pod databases) and identify which services force each choice.

Size a cluster against published v4.7 minimums: compute the worker node count and per-node CPU/memory for a control plane plus three services, and record the arithmetic.

Draft the pre-install checklist covering entitlement key handling, image registry or private registry mirroring, storage class validation, and cluster-wide prerequisites such as the certificate manager and scheduler settings.

Walk through the install sequence for the platform operator and a service instance, noting where the cpd-cli or the operand-config approach diverges between online and air-gapped installs.

Identify the top five install-time failure modes (image pull errors, insufficient resources, storage class mismatch, missing CRDs, certificate issues) and write the first diagnostic command for each.

Perform or simulate a patch upgrade of a service operand and record the observed order of operations: operator upgrade, CR update, reconciliation, and workload restart behavior.

Document the backup and restore prerequisites for the control plane and at least one stateful service, including which resources are captured and which are out of scope.

Enumerate the post-upgrade verification steps (component health checks via cpd-cli, pod status review, and functional smoke test) and run them against your scenario.

Explain the rollback constraints: what can be reverted, what cannot, and what the supported path is when a service upgrade fails mid-flight.

Configure identity and access end to end in a scenario: connect an enterprise LDAP, define user groups, and assign platform roles versus service-level roles, explaining the difference in scope.

Design a project and catalog permission model for three personas (data engineer, analyst, steward) and justify each grant against least privilege.

Implement or describe platform-level and service-level security controls: TLS certificates, secret management, and the encryption options for data at rest and in transit.

Trace how audit records flow from a service to the platform audit log and identify what events are and are not captured.

Build a governance workflow that assigns assets to a catalog, attaches business terms and classifications, and enforces a data protection rule that masks a sensitive column.

Explain the relationship between the metadata assets, the governance catalog, and the data protection rules, and show where policy is evaluated at query time.

Set up a connection from the platform to an external relational source and a cloud object store, and verify connectivity and credential handling for each.

Compare data virtualization against physical data movement for a given latency and freshness requirement, and state when federation is the wrong choice.

Create a virtualized view that joins data from two different source systems, then measure and record the query latency and any pushdown behavior observed.

Design a data integration pipeline that ingests source data, applies transformation, and writes to a target, and document the scheduling and error-handling strategy.

Explain how the platform's data integration and virtualization services share connections and metadata, and where duplication of connection definitions should be avoided.

Identify the performance levers for federated queries (predicate pushdown, source-side aggregation, result set size limits) and test at least two of them.

Work through five troubleshooting scenarios end to end (pod crash-looping, service unreachable, authentication failure, slow query, failed upgrade) and write the diagnostic path for each from symptom to root cause.

Practice reading platform logs and status output: identify which logs belong to which operator or service and what a healthy versus degraded reconciliation looks like.

Produce a design for a highly available deployment, addressing failure domains, node affinity, and the impact of losing a worker node on each service.

Articulate the trade-offs in a solution design review: cost versus resilience, single instance versus multi-instance, and self-managed versus managed services.

Re-derive the full architecture diagram and the install, upgrade, and governance runbooks from memory, then correct them against your earlier notes to expose weak spots.

Take timed practice sets weighted to the domain percentages and log every missed question by domain and by concept.

Close the three weakest concepts by re-teaching each one in writing in under 200 words, then verify against documentation.

Rehearse the solution-design narrative: given a business requirement, state the architecture, the security model, the integration approach, and the operational risk in a structured answer.