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Oracle Cloud Infrastructure 2025 Observability Professional Sample Questions (Q20-Q25):
NEW QUESTION # 20
What are two examples of a Stack Monitoring deployment model? (Choose two.)
- A. Resources running on Management Gateway
- B. Resources running on-premises
- C. Resources running on a network appliance
- D. Resources running on OCI compute instances
Answer: B,D
Explanation:
Stack Monitoring monitors application stacks across environments:
Resources running on OCI compute instances (B): Monitors components (e.g., WebLogic, databases) on OCI VMs using Management Agents.
Resources running on-premises (D): Tracks on-premises resources (e.g., Oracle Databases) via Enterprise Manager Bridge or agents.
Why not A or C?
A: Management Gateway is a proxy, not a resource host.
C: Network appliances aren't typical Stack Monitoring targets.
These models cover cloud and on-premises stacks.
NEW QUESTION # 21
Which of the following capabilities does the performance management feature of Database Management Services offer to a managed database?
- A. Automatically invokes full stats gathering of objects to improve performance of regressed SQLs
- B. Visualizes and performs trend analysis from AWR data to detect issues using AWR Explorer
- C. Dynamically modifies database initialization parameters to improve performance
Answer: B
Explanation:
The performance management feature in Database Management leverages AWR data:
Visualizes and performs trend analysis from AWR data to detect issues using AWR Explorer (B): AWR Explorer displays Automatic Workload Repository data, enabling trend analysis and issue detection (e.g., performance bottlenecks).
Why not A or C?
A: Stats gathering is manual or scheduled, not automatic in this context.
C: Parameter changes require user intervention, not dynamic automation.
AWR Explorer is key for performance insights.
NEW QUESTION # 22
Which TWO Observability and Management (O&M) services are supported by Management Agent? (Choose two.)
- A. Database Management
- B. Logging Analytics
- C. Enterprise Manager
- D. Application Performance Management
Answer: B,C
Explanation:
Management Agents collect and send data to OCI services:
Logging Analytics (B): Agents gather log data from various sources (e.g., files, databases) and send it to Logging Analytics for indexing and analysis.
Enterprise Manager (C): Agents integrate with Oracle Enterprise Manager, enabling monitoring of on-premises or cloud targets within OCI.
Why not A or D?
Application Performance Management (A): Uses Java and Browser Agents, not Management Agents.
Database Management (D): Leverages agents indirectly via other services, not a direct target.
These services leverage Management Agents for observability.
NEW QUESTION # 23
How does a user start collecting a specific log for an Entity in Logging Analytics?
- A. Create an Association of required Log Source with that Entity
- B. Identify Fields to extract
- C. Enable a Parser for the Log
- D. Configure a path for the Log File
Answer: A
Explanation:
In OCI Logging Analytics, collecting logs for an Entity (a logical representation of a resource like a host or database) requires linking it to a Log Source.
Create an Association of required Log Source with that Entity (B): This is the correct step. An association connects an Entity (e.g., a server) to a Log Source (e.g., Syslog), specifying where and how logs are collected. Once associated, Logging Analytics begins ingestion and parsing.
Why not A, C, or D?
Configure a path (A): The path is part of the Log Source definition, not the act of starting collection.
Identify Fields (C): Field extraction is a post-collection step, not the initiation process.
Enable a Parser (D): Parsers are embedded in Log Sources; enabling them is implicit in the association, not a separate step.
This association is the foundational action to enable log collection.
NEW QUESTION # 24
There are several ways to reduce Logging Analytics noise. Select the TWO options that apply. (Choose two.)
- A. Use time-picker to limit the volume of logs
- B. Use histogram records
- C. Use specific keywords
- D. Use parsed logs search
Answer: A,D
Explanation:
Reducing noise in Logging Analytics improves log analysis focus:
Use parsed logs search (C): Searches based on extracted fields (e.g., severity=ERROR) filter out irrelevant logs, targeting specific issues.
Use time-picker to limit the volume of logs (D): Narrows the time range (e.g., last hour), reducing the dataset to relevant periods.
Why not A or B?
Histogram records (A): Visualizes data distribution, not a noise reduction method.
Specific keywords (B): Useful but less precise than parsed fields; raw text search isn't emphasized in Logging Analytics.
These methods enhance signal-to-noise ratio.
NEW QUESTION # 25
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