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| Section | Weight | Objectives |
|---|---|---|
| Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - Migration technologies
|
| Configure Oracle AI Database@Azure Networking | 15% | - Azure and Oracle networking
|
| Provision and Operate Oracle AI Database@Azure Resources | 20% | - Database operations
|
| Introduction to Multicloud | 5% | - Multicloud concepts and Oracle AI Database@Azure
|
| Secure Oracle AI Database@Azure | 15% | - Security and access control
|
| Oracle AI Database@Azure Architecture and Onboarding | 20% | - Subscription and onboarding
|
| HA and DR with Oracle AI Database@Azure | 10% | - High availability
|
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NEW QUESTION # 16
Which Microsoft Azure native service is used to provide the NFS file share for storing Oracle Data Pump dump files during a ZDM Logical Online or Logical Offline migration to Exadata on Oracle Database@Azure?
Answer: D
Explanation:
Oracle's documented ZDM logical migration architecture for Oracle Database@Azure uses Azure Files to provide the NFS share used for Oracle Data Pump dump-file staging.
During a logical offline migration, Data Pump exports the source data to dump files placed on the NFS share, and the target database reads those files during import. For a logical online migration, the initial load similarly uses Data Pump, while Oracle GoldenGate captures and applies ongoing changes so that source and target remain synchronized until cutover.
The NFS share must be accessible from the participating database environments. Oracle's migration walkthrough uses an Azure Files NFSv4.1 mount and creates a database directory such as DATA_PUMP_DIR_NFS that points to the mounted path.
Azure Disk Storage is block storage rather than a cross-host NFS file share, while Azure Blob Storage exposes an object-storage interface rather than the mounted filesystem expected by standard Data Pump staging. Other NFS technologies can be used in broader ZDM architectures, but the documented Oracle Database@Azure workflow identified in this question uses Azure Files .
Study Guide reference: Migrate Oracle Databases to Oracle AI Database@Azure - ZDM logical migration, Data Pump, NFS staging and Azure Files.
NEW QUESTION # 17
Which two key management options are available for protecting transparent data encryption (TDE) master keys on Exadata databases in Oracle AI Database@Azure? (Choose two.)
Answer: A,B
Explanation:
Oracle AI Database@Azure supports two broad TDE master-key management approaches: Oracle-managed keys and customer-managed keys .
With the default Oracle-managed model, the TDE master encryption key is generated and stored in an Oracle Wallet within the database environment. Oracle manages key generation, storage, rotation, backup, and restoration activities associated with this model.
For customer-controlled key management, Oracle supports several external key stores. For Exadata Database Service on Dedicated Infrastructure, these include Azure Key Vault , OCI Vault, and Oracle Key Vault.
Azure Key Vault integration is particularly useful for organizations that want their database encryption-key governance aligned with existing Azure key-management, auditing, and separation-of-duties practices.
AWS KMS and Google Cloud KMS are not native key-management choices for an Oracle AI Database@Azure Exadata deployment.
Therefore, the two correct selections from this answer set are A and D .
Study Guide reference: Secure Oracle AI Database@Azure - Transparent Data Encryption, Oracle Wallet, customer-managed keys and Azure Key Vault.
NEW QUESTION # 18
Which core Oracle Database technology is utilized under the hood to deliver localized node-level high availability in the MAA Silver tier for Exadata Database Service on Dedicated Infrastructure in Oracle AI Database@Azure?
Answer: B
Explanation:
Oracle Maximum Availability Architecture Silver adds Oracle Real Application Clusters (RAC) to the MAA Bronze foundation. RAC provides active-active database clustering across multiple database-server nodes while all instances access the same underlying database storage.
For Exadata Database Service on Dedicated Infrastructure, RAC supplies localized protection against database-instance and database-server failure. If one RAC instance or compute node fails, services and connections can relocate to surviving instances that are already running. RAC also materially reduces or eliminates database downtime for many planned maintenance operations.
Oracle Active Data Guard addresses a different availability layer: it maintains a physically separate standby database and is primarily used for site, availability-zone, or regional disaster recovery. Oracle GoldenGate performs logical data replication and integration, while Oracle Sharding distributes data across independent database shards for scale and fault isolation.
Oracle's current MAA documentation explicitly identifies RAC as the technology introduced at the Silver tier and recommends Exadata as the optimized RAC platform.
Therefore, B is correct.
Study Guide reference: HA and DR with Oracle AI Database@Azure - MAA Silver, Oracle RAC and local high availability.
NEW QUESTION # 19
Which capability is uniquely supported by the flexible VM.BaseDB.x86 virtual machine shape in Oracle Base Database Service on Oracle AI Database@Azure?
Answer: A
Explanation:
The VM.BaseDB.x86 shape introduces a flexible ECPU allocation model for Oracle Base Database Service in Oracle AI Database@Azure. Its key capability is that administrators can modify the number of allocated ECPUs after the DB system has already been provisioned .
Oracle announced support for this shape in July 2026 and documents the ability to create and manage Base Database DB systems with flexible ECPU allocation. In the resource-management workflow, the administrator can select the option to update the ECPU count and save the revised configuration. Supported systems using VM.Standard.x86 can also be migrated to the new flexible shape.
The shape does not provide independent arbitrary memory scaling divorced from its compute model. It does not convert database storage into local logical volumes. Most importantly, Oracle explicitly states that Oracle Real Application Clusters (RAC) is not supported for this Base Database configuration, eliminating option C.
Therefore, the defining capability represented in the choices is D: modification of ECPU allocations after provisioning .
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Oracle Base Database Service, VM.BaseDB.x86 flexible shape and ECPU scaling.
NEW QUESTION # 20
A financial services firm is migrating its legacy core banking application to Microsoft Azure to leverage Azure's extensive app modernization and containerization ecosystem. However, the firm's strict service-level agreements (SLAs) for transactional throughput and database availability require keeping the system on Oracle Exadata Database Service. The database must remain in OCI to leverage native OCI management, while the containerized application microservices must be hosted on Azure. To minimize latency and egress costs, the architect must choose the OCI-recommended multicloud use-case pattern that supports running the application front-end and the relational database on different public clouds connected via private, high-speed links. Choose ONE.
Answer: B
Explanation:
The scenario directly matches Oracle's documented multicloud use case of running applications in one cloud and databases in another , also described here as an application and database split-stack architecture .
This design allows an organization to place its application tier in the cloud offering the preferred application- development ecosystem while retaining the database on the cloud platform offering the required database capabilities. In this case, Azure provides containerization and application modernization services, while OCI continues hosting Oracle Exadata Database Service for high transaction throughput, database availability, and Oracle-native operational control.
Private, high-bandwidth intercloud connectivity is critical because application-to-database latency directly affects transaction response time. Keeping data movement predictable and minimizing unnecessary public- internet routing also improves security and can reduce data-transfer overhead.
Horizontal workload distribution instead spreads workloads across clouds rather than separating application and database tiers. Production/development separation addresses lifecycle environments, while SaaS/ERP integration addresses data interoperability rather than a transactional split-stack application.
Therefore, C is the correct architectural pattern.
Study Guide reference: Introduction to Multicloud - Running Applications in One Cloud and Databases in Another.
NEW QUESTION # 21
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