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Oracle 1z0-1147 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Introduction to Multicloud5%- Explain multicloud and its benefits
- Explain common multicloud use cases and their implementation in OCI
Topic 2: Provision and Operate Oracle AI Database@Azure Resources20%- Provision Exadata infrastructure and clusters
- Provision Autonomous AI Database
- Create and configure Azure delegated subnet
- Provision Exascale infrastructure and services
- Backup and restore processes
- Configure monitoring and observability
- Provision Base Database Service
Topic 3: Secure Oracle AI Database@Azure Deployments15%- Security configurations and best practices
Topic 4: High Availability and Disaster Recovery10%- Implement HA and DR configurations
Topic 5: Oracle AI Database@Azure Architecture and Onboarding20%- Understand purchase options
- Configure prerequisites for onboarding
- Explain Oracle AI Database@Azure and its architecture
- Explain Oracle Database services in Oracle AI Database@Azure
Topic 6: Migrate Oracle Databases to Oracle AI Database@Azure15%- ZDM workflows to Exadata
- ZDM workflows to Autonomous AI Database
- Understand Oracle Zero Downtime Migration (ZDM)
Topic 7: Configure Oracle AI Database@Azure Networking15%- Explain networking concepts
- Describe supported network topologies
- Configure DNS

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Oracle AI Database@Azure Architect Professional Sample Questions (Q31-Q36):

NEW QUESTION # 31
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: A

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 # 32
You have provisioned an Exadata VM Cluster on Exascale Infrastructure with 8 ECPUs per VM and a 300 GB Exascale Database Storage Vault. Your workload has grown and additional compute capacity is now required. What should you do?

Answer: A

Explanation:
Elastic resource allocation is a fundamental design characteristic of Oracle Exadata Database Service on Exascale Infrastructure . A VM requires a minimum of 8 enabled ECPUs at initial provisioning, but its compute allocation can subsequently be increased in 4-ECPU increments .
Oracle's Exascale architecture draws compute resources from Oracle-managed shared infrastructure rather than requiring the customer to purchase or provision dedicated database servers. This permits a customer to start with a relatively small footprint and increase capacity as workload requirements develop.
The workload therefore does not need to be migrated to Dedicated Infrastructure merely because additional processing power is required. Nor is it necessary to destroy and rebuild the VM Cluster or create an entirely new Exadata Infrastructure resource. Exascale is specifically intended to avoid those fixed-capacity operational patterns.
Oracle additionally supports online scaling of Exascale storage independently through the associated Database Storage Vault, reinforcing the service's elastic consumption model.
Therefore, D is correct.
Study Guide reference: Provision and operate Oracle AI Database@Azure Resources - Exascale elastic ECPU scaling.


NEW QUESTION # 33
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: C

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 # 34
Your enterprise is configuring federated single sign-on (SSO) and authentication for administrators operating Oracle AI Database@Azure resources. Which identity provider natively provides federated identity and access management for this co-located database service?

Answer: B

Explanation:
For Oracle AI Database@Azure's documented Azure-to-OCI federation architecture, Microsoft Entra ID functions as the enterprise identity provider. Oracle's reference architecture explicitly states that Microsoft Entra ID provides federated identity and access management for Oracle AI Database@Azure.
The OCI IAM Identity Domain remains an essential component because it is the Oracle-side service provider and identity domain that trusts the Microsoft Entra identity provider. However, when the question asks which platform provides the federated corporate identity in the Azure-integrated architecture, the answer is Microsoft Entra ID.
Oracle's onboarding instructions configure an Oracle Cloud Infrastructure Console enterprise application in Entra ID and then configure the OCI identity domain with Microsoft Entra ID as its SAML identity provider.
Administrators can subsequently use their corporate Entra credentials for SSO into OCI when Oracle-native management tasks require it.
AD FS represents an older on-premises Microsoft federation service, while Okta is a third-party identity platform rather than the natively documented Azure integration.
Therefore, A is correct.
Study Guide reference: Secure Oracle AI Database@Azure - Entra ID federation, OCI IAM Identity Domains and SSO.


NEW QUESTION # 35
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: B

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 # 36
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