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| Section | Weight | Objectives |
|---|---|---|
| Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - Migration strategy selection - RMAN-based migration - Migration validation and cutover - Data Guard and GoldenGate - Oracle Data Pump - Zero Downtime Migration |
| Configure Oracle AI Database@Azure Networking | 15% | - DNS resolution and private connectivity - Default and advanced networking - ExpressRoute and site-to-site connectivity - Oracle.Database network attachments - VNet peering and connectivity - User-defined routes - Network security groups - Delegated subnets |
| Provision and Operate Oracle AI Database@Azure Resources | 20% | - Monitoring and database management - Container and Pluggable Databases - Scaling and resource management - Exadata Infrastructure and VM Clusters - Patching and maintenance - Autonomous Database Serverless - Cloning and refreshing databases - Quotas and service limits |
| Secure Oracle AI Database@Azure | 15% | - Network isolation - Auditing and logging - Transparent Data Encryption - Oracle-managed and customer-managed keys - Encryption in transit - Database and infrastructure access control - Azure and OCI separation of duties |
| Oracle AI Database@Azure Architecture and Onboarding | 20% | - Azure regions and OCI availability zones - Microsoft Entra ID and OCI IAM federation - Oracle AI Database@Azure architecture - Azure subscription and OCI tenancy linking - Roles and permissions - Azure Marketplace purchase and onboarding |
| HA and DR with Oracle AI Database@Azure | 10% | - Switchover and failover - Backup and restore - Data Guard and Autonomous Data Guard - Availability zones and Exadata redundancy - High availability architecture - RTO and RPO considerations - Point-in-time recovery |
| Introduction to Multicloud | 5% | - Multicloud concepts and Oracle AI Database@Azure |
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NEW QUESTION # 78
Your company wants to purchase Oracle Exadata Database Service on Dedicated Infrastructure via the Azure Marketplace but finds that it is only eligible through custom Private Offers. Which alternative high- performance database service should you select that is eligible for purchase via both Public Offers and Private Offers in the Azure Marketplace?
Answer: A
Explanation:
Oracle's current Oracle AI Database@Azure service matrix explicitly identifies Oracle Exadata Database Service on Exascale Infrastructure as eligible for both Private Offer and Public Offer purchasing models.
A Public Offer uses a pay-as-you-go Azure Marketplace model and allows customers to begin consuming supported services without first negotiating a custom contract with Oracle Sales. A Private Offer is based on negotiated commercial terms and is appropriate for enterprise commitments and customized pricing.
Exadata Database Service on Dedicated Infrastructure is Private Offer eligible but not Public Offer eligible.
The same Private-Offer-only restriction applies to Autonomous AI Database on Dedicated Exadata Infrastructure. Oracle Database Autonomous Recovery Service is a database protection service rather than the alternative primary high-performance Exadata database platform requested by the scenario, and it is also listed as Private Offer only.
Exascale therefore combines Exadata database capabilities with a lower-entry, elastic shared-infrastructure model and marketplace flexibility.
Thus, A is correct.
Study Guide reference: Oracle AI Database@Azure Architecture and Onboarding - Azure Marketplace offers and available database services.
NEW QUESTION # 79
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: B
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 # 80
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: B
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 # 81
A company runs Oracle Exadata Database Service on Dedicated Infrastructure on Oracle AI Database@Azure and must retain full database backups for up to 10 years to satisfy a financial services regulation. The compliance team also requires that these backups cannot be deleted or have their retention shortened before the mandated period expires, even by an administrator with backup-delete permissions. As the architect, you must select the backup configuration that satisfies both the long retention period and the immutability requirement. Choose ONE.
Answer: B
Explanation:
The correct solution combines Oracle Database Autonomous Recovery Service Long-Term Retention (LTR) with Retention Lock .
Recovery Service permits an LTR backup to be retained for up to 3,650 days-10 years . LTR backups are independent of the normal operational backup window and are designed specifically for compliance, regulatory, legal, and archival requirements.
Retention Lock adds the required immutability control. Oracle describes Retention Lock as an enforcement mechanism that protects retained backups against inadvertent changes and malicious actions such as ransomware. Once governed by the locked protection policy, backup retention cannot simply be shortened or deleted through normal backup-administration privileges before the protected period expires.
A 60-day Object Storage policy fails the ten-year requirement. Manual NFS backups lack the managed LTR and retention-lock framework, while Data Guard standby databases solve availability and disaster-recovery problems rather than replacing governed backup retention.
Therefore, C uniquely satisfies both long-term retention and immutability.
Study Guide reference: Secure Oracle AI Database@Azure - Autonomous Recovery Service, LTR and Retention Lock.
NEW QUESTION # 82
What is the minimum number of ECPUs required per VM to provision a VM cluster on Oracle Exadata Database Service on Exascale Infrastructure?
Answer: B
Explanation:
Oracle Exadata Database Service on Exascale Infrastructure uses the Elastic Compute Processing Unit (ECPU) resource model. During initial VM Cluster provisioning, Oracle requires a minimum of 8 ECPUs enabled per VM .
The distinction between the initial minimum and subsequent scaling increments is important. After the VM Cluster exists, enabled compute capacity is adjusted in increments of 4 ECPUs . Therefore, 4 ECPUs represents the scaling granularity, not the minimum provisionable starting configuration. Oracle also allows enabled ECPUs to be reduced to zero after provisioning when administrators need to temporarily shut down the VMs and suspend enabled-ECPU usage billing, but zero cannot be used as the initial active configuration.
Current Oracle documentation defines the supported total ECPU allocation per VM within the applicable Exascale service limits and explicitly states that the provisioned value must be a multiple of four.
Consequently, neither 1 nor 4 meets the initial provisioning baseline, while 16 is valid but exceeds the minimum. The correct answer is A. 8 ECPUs .
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Exascale VM Cluster sizing and ECPU configuration.
NEW QUESTION # 83
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