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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Introduction to Multicloud | 5% | - Multicloud concepts and Oracle AI Database@Azure |
| Topic 2: Provision and Operate Oracle AI Database@Azure Resources | 20% | - Monitoring and database management - Autonomous Database Serverless - Quotas and service limits - Scaling and resource management - Exadata Infrastructure and VM Clusters - Cloning and refreshing databases - Container and Pluggable Databases - Patching and maintenance |
| Topic 3: HA and DR with Oracle AI Database@Azure | 10% | - Point-in-time recovery - Switchover and failover - Availability zones and Exadata redundancy - High availability architecture - Data Guard and Autonomous Data Guard - Backup and restore - RTO and RPO considerations |
| Topic 4: Configure Oracle AI Database@Azure Networking | 15% | - Network security groups - ExpressRoute and site-to-site connectivity - VNet peering and connectivity - Default and advanced networking - Oracle.Database network attachments - Delegated subnets - User-defined routes - DNS resolution and private connectivity |
| Topic 5: Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - Data Guard and GoldenGate - Oracle Data Pump - Zero Downtime Migration - Migration validation and cutover - RMAN-based migration - Migration strategy selection |
| Topic 6: Oracle AI Database@Azure Architecture and Onboarding | 20% | - Oracle AI Database@Azure architecture - Microsoft Entra ID and OCI IAM federation - Azure regions and OCI availability zones - Azure Marketplace purchase and onboarding - Roles and permissions - Azure subscription and OCI tenancy linking |
| Topic 7: Secure Oracle AI Database@Azure | 15% | - Network isolation - Azure and OCI separation of duties - Transparent Data Encryption - Oracle-managed and customer-managed keys - Database and infrastructure access control - Auditing and logging - Encryption in transit |
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NEW QUESTION # 35
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: C
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 # 36
By default, how many delegated subnets can Oracle AI Database@Azure use before a service limit increase must be requested?
Answer: A
Explanation:
Oracle AI Database@Azure has a default regional service limit of five delegated subnets . Once a deployment requires more than five delegated subnet links in a region, the customer must request a service- limit increase.
This aggregate regional limit must not be confused with the separate VNet design rule. An individual Azure VNet can contain a maximum of one delegated subnet for Oracle AI Database@Azure, but an organization can have several VNets and therefore several delegated subnets across the same region up to the default service limit.
Oracle identifies the relevant service-limit metadata as:
Service: Multicloud
Resource: Delegated Subnet Multicloud Links
Limit name: azure-delegated-subnet-count
The limit operates at regional scope. Therefore, creating additional peerings or Route Servers does not bypass it; the correct approach is to request additional service capacity through Oracle's service-limit process.
Values of 1, 3, and 10 do not represent the default regional limit.
Therefore, A. 5 is correct.
Study Guide reference: Configure Oracle AI Database@Azure Networking - delegated subnet quotas and service-limit increases.
NEW QUESTION # 37
When monitoring metrics for Oracle Exadata Database Service on Dedicated Infrastructure within Oracle AI Database@Azure, which specific metric label must you select in the Azure Portal to view the performance of individual Pluggable Databases (PDBs)?
Answer: D
Explanation:
Oracle AI Database@Azure exposes database and infrastructure metrics through Azure Monitor, but similarly named metrics correspond to different levels of the Oracle resource hierarchy. Correct interpretation of the label is therefore essential.
Oracle's monitoring documentation explicitly differentiates the namespaces. OCI Database Cluster represents VM-cluster-level measurements. OCI Database represents Container Database (CDB) metrics.
Oracle OCI Database identifies Pluggable Database-level metrics. Consequently, to examine CPU utilization for an individual PDB, the administrator selects CPU Utilization (Oracle OCI Database) .
This distinction is particularly important for consolidated Exadata environments. A cluster-level CPU metric can show overall infrastructure utilization but cannot determine which PDB is responsible for a workload spike. Similarly, CDB-level utilization aggregates activity at the container-database layer. The Oracle OCI Database-labelled metric enables the administrator to work at the PDB scope needed for tenant or application- specific performance analysis.
The Azure Monitor integration therefore provides several metrics with superficially similar names, but their resource dimensions are deliberately different.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Azure Monitor integration, Exadata monitoring, VM Cluster/CDB/PDB metric scopes and operational observability.
NEW QUESTION # 38
What is the allowed range of days for the automatic backup retention period when configuring an instance of Oracle Autonomous AI Database Serverless in Oracle AI Database@Azure?
Answer: D
Explanation:
Oracle Autonomous AI Database Serverless allows administrators to configure the automatic backup- retention window according to business recovery and compliance requirements. Oracle's current Autonomous AI Database provisioning documentation specifies an allowable automatic backup-retention range of 1 through 60 days .
Within that period, the database can be restored and recovered to an appropriate point in time, subject to the normal Autonomous AI Database backup and recovery mechanisms. A longer retention window provides a broader point-in-time recovery horizon but must also be considered alongside governance, compliance, and backup-protection requirements.
Oracle also supports Backup Retention Lock , which materially changes administrative behavior. When the retention period is locked, administrators cannot simply disable the lock or alter the protected retention setting through ordinary provisioning controls; Oracle Support intervention is required for those changes. This distinction is important for regulated workloads where backup immutability or protection from malicious administrative actions is required.
The alternatives beginning at seven days incorrectly raise the minimum, while the 30-day options incorrectly reduce the supported maximum. The complete configurable range is therefore 1-60 days .
Study Guide reference: Secure Oracle AI Database@Azure - Autonomous AI Database automatic backups, point-in-time recovery, backup-retention configuration and retention lock.
NEW QUESTION # 39
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: C
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 # 40
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