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| Section | Weight | Objectives |
|---|---|---|
| Secure Oracle AI Database@Azure | 15% | - Data protection
|
| Oracle AI Database@Azure Architecture and Onboarding | 20% | - Subscription and onboarding
|
| Introduction to Multicloud | 5% | - Multicloud concepts and Oracle AI Database@Azure
|
| Configure Oracle AI Database@Azure Networking | 15% | - Network security and connectivity
|
| Migrate Oracle Databases to Oracle AI Database@Azure | 15% | - Migration planning
|
| HA and DR with Oracle AI Database@Azure | 10% | - Disaster recovery and backup
|
| Provision and Operate Oracle AI Database@Azure Resources | 20% | - Database operations
|
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NEW QUESTION # 21
You have enabled automatic backups on an Autonomous AI Database with a 30-day retention period. You subsequently terminate the Autonomous Container Database. What happens to the previously retained automatic backups?
Answer: B
Explanation:
Oracle Autonomous Container Database backup configuration includes an explicit backup-retention policy on termination . Administrators can select one of two supported behaviors: retain backups according to the normal configured backup-retention period, or retain them for 72 hours after termination and then delete them .
Oracle documentation identifies these options as RETAIN_PER_RETENTION_WINDOW and RETAIN_FOR_72_HOURS. The latter is the default in relevant API/Terraform configuration. Therefore, terminating an Autonomous Container Database does not inherently result in the immediate deletion of all automatic backups. Their post-termination lifetime is governed by the configured termination-retention policy.
Standard automatic backups are also not automatically converted into Long-Term Retention backups when the database is terminated. LTR backups have their own lifecycle and are explicitly excluded from the ordinary ACD termination-retention setting. No automatic export to Azure Blob Storage occurs as part of ACD termination.
Thus, B correctly reflects Oracle's documented post-termination backup behavior.
Study Guide reference: Secure Oracle AI Database@Azure - Autonomous Container Database automatic backups, termination and retention policy.
NEW QUESTION # 22
You have successfully deployed a two-node Exadata VM Cluster on Oracle AI Database@Azure to provide hardware-level high availability using Oracle RAC. What client-side feature should you implement at the application layer to mask database node failures and transparently replay in-flight uncommitted transactions without throwing errors to end users?
Answer: C
Explanation:
Oracle Application Continuity (AC) is the application-availability technology designed to mask recoverable database outages and replay database requests transparently after a connection is re-established.
Oracle RAC provides database-service continuity when one database instance or node becomes unavailable, but an application may still have active sessions or in-flight work on the failed instance. Application Continuity works with Oracle's high-availability connection infrastructure, database services, FAN, Transaction Guard, and supported clients to reconnect to an available instance and replay eligible database requests. This significantly reduces the application errors that would otherwise be exposed during node failure or planned maintenance.
Fast-Start Failover and Data Guard Broker operate at the Data Guard database-role and disaster-recovery level. They manage primary/standby transitions rather than transparently replaying an individual application session after a RAC node failure. Transparent Data Encryption protects database data at rest and has no role in request replay or failure masking.
Therefore, C. Oracle Application Continuity is correct.
Study Guide reference: HA and DR with Oracle AI Database@Azure - RAC application availability, FAN, Transaction Guard and Application Continuity.
NEW QUESTION # 23
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: B,D,E
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 # 24
Your organization runs its critical billing workloads on Oracle Exadata Database Service on Dedicated Infrastructure within Oracle AI Database@Azure. The security and operations teams require a unified dashboard in the Azure Portal to monitor Exadata VM cluster lifecycle management actions, database events, Exadata infrastructure health, and Data Guard replication logs. The solution must allow administrators to write Kusto Query Language (KQL) queries to correlate these logs with Azure application VM logs in real time without deploying custom agents inside the database VMs. As the multicloud architect, which configuration should you recommend to meet these requirements? Choose ONE.
Answer: B
Explanation:
The native architecture is to configure Azure Monitor diagnostic settings on the Oracle Exadata resources and route the selected log categories into an Azure Log Analytics workspace .
Oracle AI Database@Azure exposes relevant Exadata lifecycle and operational events through Azure diagnostic settings without requiring agents to be installed on Oracle-managed Exadata nodes. Once the telemetry reaches Log Analytics, administrators can query it using Kusto Query Language (KQL) and correlate the Oracle resource events with telemetry generated by Azure application infrastructure.
This architecture satisfies the requirement for centralized Azure-side observability while preserving the managed-service boundary of Exadata. It also integrates naturally with Azure dashboards, alerting, Microsoft Sentinel, and other Azure Monitor capabilities.
Using OCI Object Storage would introduce an unnecessary cross-platform telemetry pipeline. Oracle Enterprise Manager remains useful in broader Oracle management scenarios but is not required for this native Azure integration. Installing Azure Monitor Agent directly on Oracle-managed Exadata infrastructure is neither necessary nor the documented implementation pattern.
Therefore, A provides the supported integrated monitoring architecture.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Azure Monitor, diagnostic settings, Log Analytics, KQL and Exadata observability.
NEW QUESTION # 25
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: D
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 # 26
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