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| Section | Weight | Objectives |
|---|---|---|
| Configure Oracle AI Database@Azure Networking | 15% | - Explain networking concepts - Configure DNS - Describe supported network topologies |
| Secure Oracle AI Database@Azure Deployments | 15% | - Security configurations and best practices |
| Provision and Operate Oracle AI Database@Azure Resources | 20% | - Provision Autonomous AI Database - Provision Base Database Service - Create and configure Azure delegated subnet - Provision Exascale infrastructure and services - Provision Exadata infrastructure and clusters - Backup and restore processes - Configure monitoring and observability |
| Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - Understand Oracle Zero Downtime Migration (ZDM) - ZDM workflows to Exadata - ZDM workflows to Autonomous AI Database |
| High Availability and Disaster Recovery | 10% | - Implement HA and DR configurations |
| Oracle AI Database@Azure Architecture and Onboarding | 20% | - Explain Oracle Database services in Oracle AI Database@Azure - Configure prerequisites for onboarding - Explain Oracle AI Database@Azure and its architecture - Understand purchase options |
| Introduction to Multicloud | 5% | - Explain multicloud and its benefits - Explain common multicloud use cases and their implementation in OCI |
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NEW QUESTION # 52
Which two database services are officially supported and available for deployment on optimized hardware in Oracle AI Database@Azure? (Choose two.)
Answer: C,D
Explanation:
Among the choices presented, Oracle Exadata Database Service on Dedicated Infrastructure and Oracle Autonomous AI Database are both native Oracle AI Database@Azure database services designed to run on Oracle-optimized database infrastructure located inside Azure data centers. Exadata Database Service provides customer-managed Oracle Database environments on purpose-built Exadata hardware, with RAC, Data Guard, elastic compute, and high-performance storage capabilities. Autonomous AI Database provides a fully managed database model in which Oracle automates provisioning, patching, tuning, backup operations, and resource scaling.
Oracle's current service portfolio has expanded further and now also includes Exadata Database Service on Exascale Infrastructure, Base Database Service, Autonomous AI Database on Dedicated Exadata Infrastructure, GoldenGate, and Autonomous Recovery Service. However, those services are not alternatives in this question. Oracle NoSQL Database Cloud Service is not one of the listed Oracle AI Database@Azure database offerings, while a generic Oracle Database Standard Edition VM running on Azure IaaS is not equivalent to a native Oracle AI Database@Azure service.
Therefore, B and C are correct. Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - supported database services and optimized Oracle infrastructure.
NEW QUESTION # 53
You are configuring logging for an Exadata Infrastructure resource in Oracle AI Database@Azure and attempt to save a second diagnostic setting that routes the same log categories to your primary Log Analytics workspace. What will occur when you attempt to save this configuration?
Answer: B
Explanation:
Microsoft's Oracle Exadata Database on Dedicated Infrastructure observability guidance explicitly defines a no-duplicate-destination rule for these resources: two diagnostic settings cannot send the same log categories to the same destination. Each diagnostic-setting configuration must therefore remain unique.
An Exadata resource can have multiple diagnostic settings-Microsoft documents a maximum of five per resource-but those settings are intended to provide different category/destination combinations. If an administrator attempts to create another setting with the same log categories targeting the same Log Analytics workspace, the duplicate configuration is rejected rather than automatically consolidated.
Microsoft Sentinel does not serve as a conflict-management mechanism for the diagnostic-settings configuration, and the platform does not resolve the collision by modifying Log Analytics retention. Retention is a separate workspace/data-management concern.
This rule prevents unintended duplicate ingestion and avoids unnecessary telemetry duplication and associated ingestion cost.
Therefore, A accurately describes the outcome.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Exadata logging, Azure Monitor diagnostic settings, Log Analytics and observability constraints.
NEW QUESTION # 54
Where is a long-term retention backup in the Oracle Database Autonomous Recovery Service automatically moved after its first 24 hours of storage?
Answer: A
Explanation:
Oracle Database Autonomous Recovery Service supports Long-Term Retention (LTR) backups for organizations that need to preserve full database backups for compliance, regulatory, legal, or business requirements. The correct destination is the OCI Object Storage Infrequent Access tier .
The question source specifies that the LTR backup initially remains in the standard storage tier and transitions after the first 24 hours to Infrequent Access storage for the remainder of its retention period. Oracle's Recovery Service documentation independently confirms that long-term retention backups are stored in the Object Storage Infrequent Access tier and can be retained for periods extending up to ten years.
The Infrequent Access tier is appropriate because LTR backups are retained for extended periods but are generally restored less frequently than operational backups. Archive Storage is not the managed destination used by Recovery Service for this workflow. Azure Archive Blob Storage is likewise not the Oracle-managed OCI storage tier identified for these backups, and there is no "OCI Legacy Backup" storage tier.
Therefore, D is correct.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Autonomous Recovery Service, LTR backups, retention and storage lifecycle.
NEW QUESTION # 55
Which of the following is NOT one of the documented supported network topologies for Oracle AI Database@Azure?
Answer: C
Explanation:
Azure Front Door single-endpoint routing is not a documented Oracle AI Database@Azure database connectivity topology.
Azure Front Door is primarily a global Layer-7 HTTP/HTTPS application-delivery, acceleration, and load- balancing service. It is designed for web applications and public-facing application endpoints rather than private SQL*Net/database connectivity into an Oracle AI Database@Azure delegated subnet.
Oracle's documented networking patterns instead center on Azure VNets and private routing. These include local/same-region VNet connectivity, VNet peering, Hub-and-Spoke VNet peering, cross-region connectivity, and hybrid on-premises Hub-and-Spoke architectures. Oracle also documents enterprise connectivity patterns involving Azure Virtual WAN.
Hub-and-Spoke is particularly important where centralized firewalls or NVAs must inspect database-bound traffic, while local VNet/VNet peering is useful for direct application-to-database private communication where minimizing network latency is the priority.
Because Azure Front Door does not provide the required private database networking architecture and is absent from Oracle's supported topology set, C is the correct answer.
Study Guide reference: Configure Oracle AI Database@Azure Networking - supported VNet, peering, Hub-and-Spoke and enterprise connectivity topologies.
NEW QUESTION # 56
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: C
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 # 57
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