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| Section | Weight | Objectives |
|---|---|---|
| Introduction to Multicloud | 5% | - Explain multicloud and its benefits - Explain common multicloud use cases and their implementation in OCI |
| High Availability and Disaster Recovery | 10% | - Implement HA and DR configurations |
| Oracle AI Database@Azure Architecture and Onboarding | 20% | - Understand purchase options - Configure prerequisites for onboarding - Explain Oracle AI Database@Azure and its architecture - Explain Oracle Database services in Oracle AI Database@Azure |
| Configure Oracle AI Database@Azure Networking | 15% | - Configure DNS - Explain networking concepts - Describe supported network topologies |
| Provision and Operate Oracle AI Database@Azure Resources | 20% | - Provision Exascale infrastructure and services - Provision Autonomous AI Database - Provision Base Database Service - Provision Exadata infrastructure and clusters - Configure monitoring and observability - Create and configure Azure delegated subnet - Backup and restore processes |
| Secure Oracle AI Database@Azure Deployments | 15% | - Security configurations and best practices |
| Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - ZDM workflows to Exadata - Understand Oracle Zero Downtime Migration (ZDM) - ZDM workflows to Autonomous AI Database |
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NEW QUESTION # 18
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
NEW QUESTION # 19
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: A
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 # 20
Which ZDM migration workflow uses an initial load followed by GoldenGate-based change data capture to achieve near-zero downtime?
Answer: D
Explanation:
Logical Online Migration combines an initial logical data load with Oracle GoldenGate change data capture to minimize production downtime.
The initial target database is populated using Oracle Data Pump export and import. Because that data movement can take a substantial amount of time for large databases, Oracle GoldenGate continuously captures transactions committed on the source while the initial load is being performed. Those transactions are subsequently applied to the target, allowing the destination to converge with the production source while the application remains active.
When synchronization reaches the required state, ZDM orchestrates the final migration phases and application cutover. The downtime requirement is therefore concentrated around the final transition rather than the entire export/import window.
Logical Offline uses Data Pump without continuous GoldenGate synchronization. Physical Online uses RMAN-based target instantiation and Oracle Data Guard redo synchronization instead of GoldenGate.
Physical Offline similarly relies on physical backup/restore processes and does not use logical change-data capture.
Thus, B. Logical Online Migration is correct.
Study Guide reference: Migrate Oracle Databases to Oracle AI Database@Azure - ZDM Logical Online, Data Pump and GoldenGate CDC.
NEW QUESTION # 21
A mid-size retailer wants to move a moderately sized seasonal transactional workload to Oracle AI Database@Azure. They want to avoid provisioning dedicated database and storage servers, want to start with a small committed footprint and elastically scale ECPUs and storage online as holiday sales volume grows, and want the ability to create instant, space-efficient thin clones of production for their developers. As the architect, you must select the Oracle AI Database@Azure deployment option that meets all of these needs.
Choose ONE.
Answer: B
Explanation:
Oracle Exadata Database Service on Exascale Infrastructure precisely matches the scenario. Exascale uses Oracle-managed, multitenant physical database-server infrastructure, allowing customers to provision relatively small VM Clusters rather than committing to dedicated Exadata database and storage servers.
A VM Cluster can begin at 8 ECPUs per VM and scale its compute allocation in 4-ECPU increments.
Exascale storage is also elastic and can be expanded without requiring customers to add or manage physical Exadata Storage Servers.
A distinctive Exascale feature is redirect-on-write thin cloning . Oracle documents the ability to create space-efficient PDB clones in which unchanged blocks remain shared between the parent and clone. This makes development and test copies fast to provision and economical in storage consumption.
Dedicated Infrastructure contradicts the requirement to avoid dedicated server capacity. Base Database Service does not offer the same Exascale thin-clone architecture, while Autonomous Serverless represents a different autonomous operating model.
Therefore, B is correct.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Exascale elasticity and thin clones.
NEW QUESTION # 22
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 # 23
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