[2025年更新]1Z0-1111-25はOracle Cloud Infrastructureリアルな無料試験練習テスト
無料Oracle Cloud Infrastructure 1Z0-1111-25試験問題を提供します
Oracle 1Z0-1111-25 認定試験の出題範囲：
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質問 # 34
Which two components are optional while creating the Monitoring Query Language (MQL) expressions in the Oracle Cloud Infrastructure (OCI) Monitoring service? (Choose two.)
- A. Previous
- B. Dimensions
- C. Interval
- D. Metric
- E. Grouping Function
- F. Statistic
正解：E、F
解説：
MQL expressions in OCI Monitoring retrieve and process metric data. Optional components include:
Statistic (B): Specifies how to summarize data (e.g., avg, max). If omitted, raw data is returned.
Grouping Function (D): Aggregates data across metric streams (e.g., by resourceId). It's optional if no grouping is needed.
Why not A, C, E, or F?
Interval (A): Defines the time window; defaults apply if omitted, but it's typically required for meaningful queries.
Previous (C): Not a standard MQL component (possibly a typo).
Metric (E): Mandatory to specify what's being queried.
Dimensions (F): Filters data; required if specific streams are targeted, though optional in basic queries.
Statistic and Grouping Function enhance flexibility but aren't mandatory.
質問 # 35
What are two examples of a Stack Monitoring deployment model? (Choose two.)
- A. Resources running on-premises
- B. Resources running on OCI compute instances
- C. Resources running on Management Gateway
- D. Resources running on a network appliance
正解：A、B
解説：
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.
質問 # 36
There are several ways to reduce Logging Analytics noise. Select the TWO options that apply. (Choose two.)
- A. Use histogram records
- B. Use parsed logs search
- C. Use time-picker to limit the volume of logs
- D. Use specific keywords
正解：B、C
解説：
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.
質問 # 37
Which is an example of Log Sources in Logging Analytics?
- A. File, Database, Windows Events System, Syslogs
- B. Long, Integer, String fields
- C. JSON, XML, CSV files
- D. Windows Events, Syslog Listener, and Database SQL parsers
正解：D
解説：
In OCI Logging Analytics, Log Sources are predefined parsers that extract fields from specific types of log data, enabling structured analysis.
Windows Events, Syslog Listener, and Database SQL parsers (B): These are examples of Log Sources in Logging Analytics. Each represents a specific log type with a predefined parser:
Windows Events: Parses event logs from Windows systems (e.g., security, application logs).
Syslog Listener: Handles logs in the Syslog format, common in Unix-based systems or network devices.
Database SQL parsers: Extracts fields from database logs (e.g., Oracle Database audit logs).
These sources come with built-in field mappings and labels for analysis.
Why not A, C, or D?
Long, Integer, String fields (A): These are data types, not Log Sources.
File, Database, Windows Events System, Syslogs (C): While close, this mixes log locations (e.g., File, Database) with source types and isn't a precise match to predefined Log Sources.
JSON, XML, CSV files (D): These are file formats, not Log Sources; Logging Analytics can parse them but they're not predefined sources.
Log Sources streamline log ingestion by providing out-of-the-box parsing for common log types.
質問 # 38
Which TWO actions can be performed using the Database Management Service in Oracle Cloud Infrastructure (OCI)? (Choose two.)
- A. Forecast capacity issues of Oracle Databases in on-premises, OCI, and multi-cloud environments
- B. Compare database performance across different time periods or perform real-time monitoring of SQL statements
- C. Forecast capacity issues of your Database services in OCI
- D. Analyze and tune SQL performance issues of Oracle Databases on-premises, OCI, and multi-cloud environments
正解：B、D
解説：
Database Management Service provides advanced database oversight:
Compare database performance across different time periods or perform real-time monitoring of SQL statements (C): Uses Performance Hub for historical and real-time SQL monitoring.
Analyze and tune SQL performance issues of Oracle Databases on-premises, OCI, and multi-cloud environments (D): Offers SQL tuning across diverse deployments.
Why not A or B?
A and B: Capacity forecasting is an Operations Insights feature, not Database Management.
These actions enhance database performance management.
質問 # 39
Which step is essential while building a reliable log monitoring environment?
- A. Creation of the Key Performance Indicators (KPIs) to monitor
- B. Determination of the Machine Learning models you need to program
- C. Define permissions for the user roles in the region
- D. Noise baseline determination
正解：D
解説：
A reliable log monitoring environment filters signal from noise:
Noise baseline determination (B): Establishes the typical level of irrelevant log data, allowing filters (e.g., severity levels) to focus on meaningful events, improving monitoring effectiveness.
Why not A, C, or D?
A: ML models are advanced, not essential for baseline setup.
C: KPIs are useful but secondary to noise reduction.
D: Permissions are administrative, not core to reliability.
Noise baseline is foundational.
質問 # 40
When would you use a vantage point in Application Performance Monitoring (APM)?
- A. Synthetic Monitoring
- B. Distributed Tracing
- C. Application Insights
- D. Java Management
正解：A
解説：
In APM, a vantage point is used in:
Synthetic Monitoring (D): Runs tests from specific locations (vantage points) to monitor web application or API availability and performance globally.
Why not A, B, or C?
Java Management (A): Unrelated to vantage points.
Distributed Tracing (B): Tracks internal request flows, not external tests.
Application Insights (C): Not a formal APM feature; vague term.
Vantage points simulate user access from different regions.
質問 # 41
What two APM agents can Application Performance Monitoring use to collect data? (Choose two.)
- A. Browser Agent
- B. Management Agent
- C. Java Agent
- D. Cloud Agent
正解：A、C
解説：
OCI APM uses specific agents for data collection:
Java Agent (B): Attaches to Java applications to collect traces, metrics, and errors for APM.
Browser Agent (D): A JavaScript snippet embedded in web pages to collect Real User Monitoring (RUM) data (e.g., page load times).
Why not A or C?
Management Agent (A): Used for Stack Monitoring/Operations Insights, not APM.
Cloud Agent (C): Monitors compute instances, not an APM-specific agent.
These agents target application and user experience monitoring.
質問 # 42
Which two features are provided by Application Performance Monitoring? (Choose two.)
- A. Real User Monitoring
- B. Capacity Planning
- C. Java Management
- D. Distributed Tracing
正解：A、D
解説：
OCI Application Performance Monitoring (APM) provides tools to monitor application performance:
Distributed Tracing (A): Tracks requests across microservices, showing latency and dependencies via traces and spans.
Real User Monitoring (C): Captures real user interactions with web applications (e.g., page load times) using a Browser Agent.
Why not B or D?
Capacity Planning (B): Available in Operations Insights, not APM.
Java Management (D): Not a feature of APM; Java Agent is a tool, not a feature.
These features align with APM's focus on performance and user experience.
質問 # 43
Which two future resource usages are identified by Exadata Warehouse Insights custom analytics under Operations Insights? (Choose two.)
- A. Memory
- B. AIOps
- C. Network usage
- D. CPU
正解：A、D
解説：
Exadata Warehouse Insights in OCI Operations Insights provides advanced analytics to forecast resource usage for Exadata systems.
Memory (A): Tracks and predicts memory utilization based on historical trends, aiding capacity planning.
CPU (D): Forecasts CPU usage, helping identify potential bottlenecks or over-provisioning.
Why not B or C?
Network usage (B): While monitored, it's not a primary focus of Exadata Warehouse Insights' future usage predictions.
AIOps (C): This is a methodology, not a resource usage metric.
These forecasts leverage historical data and what-if analysis for proactive management.
質問 # 44
How does a user start collecting a specific log for an Entity in Logging Analytics?
- A. Identify Fields to extract
- B. Enable a Parser for the Log
- C. Configure a path for the Log File
- D. Create an Association of required Log Source with that Entity
正解：D
解説：
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.
質問 # 45
Which are the two components that the Management Agent solution includes in the Cloud service? (Choose two.)
- A. Cloud assets
- B. Management Agent
- C. Management Gateway
- D. OCI Logging Analytics
正解：B、C
解説：
The Management Agent solution comprises:
Management Gateway (B): A secure proxy that encrypts and forwards data from Management Agents to OCI services.
Management Agent (D): A lightweight process that collects and sends telemetry data from resources.
Why not A or C?
OCI Logging Analytics (A): A consumer of agent data, not a component of the solution.
Cloud assets (C): A vague term, not a specific component.
These components enable secure data collection.
質問 # 46
Which is the recommended method to continuously monitor and ingest logs from Object Storage buckets?
- A. Object Store Bucket
- B. Object Storage
- C. Object Store
- D. ObjectCollection Rule
正解：D
解説：
For continuous log ingestion from Object Storage:
ObjectCollection Rule (A): A Logging Analytics feature that monitors Object Storage buckets and ingests logs based on defined patterns (e.g., bucket name, object prefix). It's designed for this purpose.
Why not B, C, or D?
Object Store (B), Object Storage (C), Object Store Bucket (D): These refer to the storage service or its components, not a method for log ingestion.
ObjectCollection Rule ensures automated, ongoing log collection.
質問 # 47
Which of the following is required to enable Stack Monitoring?
- A. Dynamic group for discovery service
- B. User group for VCN collection
- C. Machine Learning group for resource associations
正解：A
解説：
To enable Stack Monitoring:
Dynamic group for discovery service (A): A dynamic group defines resources (e.g., compute instances) that Stack Monitoring can discover and monitor. A policy granting permissions to this group is also required.
Why not B or C?
Machine Learning group (B): Not a valid OCI concept for Stack Monitoring.
User group for VCN collection (C): User groups manage human access, not service discovery.
This setup ensures Stack Monitoring can access and monitor resources.
質問 # 48
Which Logging Analytics concept represents an asset on your host that could provide log data?
- A. Parser
- B. Association
- C. Source
- D. Entity
正解：C
解説：
In OCI Logging Analytics, a Source defines the origin of log data from an asset on a host.
Source (B): Represents a log-generating asset (e.g., a file, database audit log, or Windows event log), specifying its location, format, and collection frequency. It's associated with an Entity to enable log ingestion and parsing.
Why not A, C, or D?
Association (A): Links a Source to an Entity, not the asset itself.
Entity (C): A logical representation of a resource (e.g., a host), not the log source.
Parser (D): Extracts fields from logs, not the asset providing data.
Sources are foundational to log collection in Logging Analytics.
質問 # 49
What are the TWO benefits of Observability Lakehouse in Operations Insights? (Choose two.)
- A. Identifies future resource usage Oracle Cloud
- B. Provides data based on a statistical analysis of AI data
- C. Enables custom analytics such as trending, forecasting, capacity planning, workload characterizations
- D. Allows Oracle Enterprise Manager's operations data for various use-cases
正解：C、D
解説：
The Observability Lakehouse in Operations Insights is a data repository for operational analytics:
Enables custom analytics (B): Supports trending (e.g., usage patterns), forecasting (e.g., resource needs), capacity planning, and workload profiling using advanced analytical tools, enhancing resource optimization.
Allows Oracle Enterprise Manager's data (D): Integrates operational data from Enterprise Manager (e.g., database metrics) for use cases like performance analysis and anomaly detection.
Why not A or C?
Statistical analysis of AI data (A): Too vague; Lakehouse focuses on operational data, not AI-specific stats.
Identifies future resource usage (C): Partial benefit of B, but not a standalone feature.
These capabilities improve operational decision-making.
質問 # 50
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