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| Section | Weight | Objectives |
|---|---|---|
| Provision and Operate Oracle AI Database@Azure Resources | 20% | - Database operations
|
| Oracle AI Database@Azure Architecture and Onboarding | 20% | - Subscription and onboarding
|
| HA and DR with Oracle AI Database@Azure | 10% | - Disaster recovery and backup
|
| Configure Oracle AI Database@Azure Networking | 15% | - Azure and Oracle networking
|
| Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - Migration planning
|
| Secure Oracle AI Database@Azure | 15% | - Data protection
|
| Introduction to Multicloud | 5% | - Multicloud concepts and Oracle AI Database@Azure
|
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NEW QUESTION # 23
Your team is migrating a processing-intensive workload to Oracle Autonomous AI Database Serverless on Oracle AI Database@Azure and needs to scale up the compute allocation during provisioning. What is the maximum number of ECPUs that can be configured for a single database instance using the slider user interface?
Answer: D
Explanation:
The standard Oracle Autonomous AI Database Serverless resource-allocation interface permits the administrator to configure the base compute allocation up to 512 ECPUs using the ECPU slider. This value represents the configured base ECPU count for a single database instance rather than the potential temporary compute consumption obtainable through compute auto scaling.
Oracle distinguishes configured ECPUs from auto-scaled usage. For eligible Autonomous AI Database configurations, compute auto scaling can allow the database to consume additional processing capacity above the configured base according to workload demand. For example, a database configured with 512 ECPUs may be capable of consuming substantially more effective processing capacity when auto scaling is enabled, subject to the service and licensing model.
The 1024-ECPU option therefore does not represent the normal single-instance slider ceiling addressed by this question. The 256- and 128-ECPU values are valid intermediate configurations but are below the maximum.
Consequently, A. 512 ECPUs is correct.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Autonomous AI Database Serverless provisioning, ECPU configuration and compute scaling.
NEW QUESTION # 24
What are the core ECPU scaling increments required when configuring the enabled ECPU count per virtual machine for an Exadata VM Cluster on Exascale Infrastructure?
Answer: D
Explanation:
Oracle Exadata Database Service on Exascale Infrastructure uses the Elastic Compute Processing Unit (ECPU) model for allocating database-server processing capacity. Oracle's Exascale technical architecture specifies that a VM requires at least eight enabled ECPUs for initial VM Cluster provisioning and that vertical compute scaling is performed in increments of four ECPUs .
This model provides substantially finer-grained scaling than traditional fixed Exadata infrastructure shapes while maintaining predictable resource allocation across the underlying Exascale compute pool.
Administrators can increase enabled ECPUs as workload demand grows, and Exascale also supports reserved ECPU concepts that allow capacity to be physically reserved for future growth. The distinction between enabled and reserved capacity is operationally important: enabled ECPUs are active compute resources used by the VM, whereas reserved capacity can facilitate future scale-up.
An increment of eight would unnecessarily double the required scaling step; one- or two-ECPU increments are not the documented unit for Exadata VM scaling on Exascale Infrastructure. The correct granularity is therefore four ECPUs .
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Exadata Database Service on Exascale Infrastructure, ECPU compute model, VM Cluster provisioning and scaling.
NEW QUESTION # 25
Which three are valid destination types that can be configured when setting up Azure Monitor diagnostic settings for Exadata VM Clusters in Oracle AI Database@Azure? (Choose three.)
Answer: A,B,D
Explanation:
Oracle AI Database@Azure integrates its operational telemetry with Azure Monitor diagnostic settings so organizations can apply existing Azure observability, compliance, and SIEM architectures to Oracle database infrastructure.
Three standard destinations are relevant here. An Azure Log Analytics workspace receives telemetry for centralized querying, dashboarding, alerting, and Kusto Query Language analysis. An Azure Storage account can archive logs or metrics for retention, compliance, or later processing. Azure Event Hubs provides a streaming destination for forwarding telemetry to SIEM products, custom consumers, event-processing pipelines, or other downstream platforms.
Oracle's Oracle AI Database@Azure monitoring documentation specifically lists Log Analytics Workspace, Storage Account, and Event Hub among the available Azure Monitor diagnostic-routing destinations. Oracle Enterprise Manager can monitor Oracle environments but is not an Azure Monitor diagnostic-settings destination. OCI Object Storage is likewise not selected directly as a destination from the Azure diagnostic- settings workflow. Azure SQL Database is a database service rather than a supported diagnostic sink.
Therefore, the three correct selections are A, C, and D .
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - monitoring, Azure diagnostic settings, Log Analytics, Storage accounts and Event Hubs.
NEW QUESTION # 26
You are planning a ZDM Physical Online migration of a 10 TB production database to Exadata on Oracle Database@Azure and want to avoid using intermediate storage for backups. Which database creation method will ZDM automatically utilize to build the target database directly from the source database?
Answer: C
Explanation:
Oracle's preferred ZDM Physical Online workflow for Oracle Database@Azure supports direct data transfer
, specifically to avoid staging large RMAN backups in intermediate object or file storage. In this workflow, ZDM creates the target database using the Restore From Service method.
RMAN streams the required database blocks directly from the source database service to the target environment over the configured network connection. After the target database has been instantiated, Oracle Data Guard maintains synchronization between source and target by transporting and applying redo. ZDM then orchestrates the cutover when the migration reaches the appropriate stage.
This approach is particularly significant for a large database such as the 10 TB system in the scenario because intermediate backup staging would require substantial temporary storage, additional I/O, and backup-transfer operations. Oracle explicitly states that the physical online direct-data-transfer workflow creates the target through Restore From Service and avoids backing up the source to an intermediate storage location.
Backup and Restore therefore describes the physical offline/staged model. Transportable Tablespaces is not the standard ZDM physical-online instantiation mechanism.
Study Guide reference: Migrate Oracle Databases to Oracle AI Database@Azure - ZDM Physical Online, direct data transfer, RMAN Restore From Service and Data Guard.
NEW QUESTION # 27
Your organization is deploying a business-critical database on Oracle Exadata Database Service on Dedicated Infrastructure within Oracle AI Database@Azure. Your security and compliance officer mandates that all database backups must remain exclusively within the local Azure region to satisfy strict data residency laws, and they must be protected against ransomware using an immutable, policy-based retention lock.
Additionally, the business requires real-time database protection that reduces potential data loss to less than one second in the event of an outage. Finally, the procurement team wants to ensure that the storage cost of these backups draws down on their existing Microsoft Azure Consumption Commitment (MACC). Which backup option should you implement to meet all of these requirements? Choose ONE.
Answer: D
Explanation:
Oracle Database Autonomous Recovery Service with Azure-based storage is specifically designed to satisfy this combination of data residency, ransomware protection, near-zero data loss, and Azure commercial integration.
Oracle allows the protection policy to specify Store backups in the same cloud provider as the database , which keeps Oracle Database@Azure Recovery Service backups within Azure rather than the paired OCI region. A protection policy can also enable Retention Lock , preventing backups from being modified or deleted before policy expiration and providing protection against accidental or malicious deletion.
For business-critical databases, Real-time Data Protection can be enabled. Oracle describes this as providing recovery to the last sub-second, materially reducing potential data-loss exposure compared with ordinary periodic backups.
Oracle AI Database@Azure usage is billed through Azure Marketplace and counts toward Microsoft Azure Consumption Commitment. Standard OCI Object Storage would not satisfy the stated local-Azure-only storage requirement. Customer-managed Blob Storage lacks the integrated Recovery Service real-time protection model, while ZDLRA is an engineered on-premises recovery appliance rather than the native Oracle AI Database@Azure service.
Therefore, B is correct.
Study Guide reference: Secure Oracle AI Database@Azure - Autonomous Recovery Service, retention lock, real-time protection and data residency.
NEW QUESTION # 28
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