[2025年10月] 検証済みOracle 1Z0-1111-25リアル豪華お試しセット試験問題集でPDF
1Z0-1111-25問題集PDF最新 [2025年最新] 究極の学習ガイド
Oracle 1Z0-1111-25 認定試験の出題範囲：
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質問 # 26
Which of the following is required to enable Stack Monitoring?
- A. Machine Learning group for resource associations
- B. Dynamic group for discovery service
- C. User group for VCN collection
正解：B
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 # 27
Choose two FluentD scenarios that apply when using continuous log collection with client-side processing. (Choose two.)
- A. Log Source
- B. Monitoring systems that are not currently supported by Management Agent
- C. Comprehensive monitoring for OKE/Kubernetes
- D. Managing apps/services which push logs to Object Storage
正解：C、D
解説：
FluentD is an open-source data collector used for continuous log collection with client-side processing in OCI Logging. Two applicable scenarios are:
Managing apps/services which push logs to Object Storage (A): FluentD can be configured to collect logs from applications or services (e.g., Oracle Functions) that write logs to Object Storage buckets. It processes these logs client-side and forwards them to OCI Logging or Logging Analytics.
Comprehensive monitoring for OKE/Kubernetes (B): FluentD is widely used in Kubernetes environments like Oracle Container Engine for Kubernetes (OKE) to collect logs from pods, containers, and nodes. It processes these logs locally before sending them to OCI services for analysis.
Why not C or D?
Monitoring unsupported systems (C): While possible, this is not a primary FluentD scenario in OCI-it's more about extending Management Agent capabilities.
Log Source (D): This is a component of Logging Analytics, not a FluentD scenario.
FluentD's flexibility makes it ideal for these use cases in OCI's observability ecosystem.
質問 # 28
Which are the two components that the Management Agent solution includes in the Cloud service? (Choose two.)
- A. Management Gateway
- B. Cloud assets
- C. OCI Logging Analytics
- D. Management Agent
正解：A、D
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 # 29
Which TWO Observability and Management (O&M) services are supported by Management Agent? (Choose two.)
- A. Enterprise Manager
- B. Logging Analytics
- C. Database Management
- D. Application Performance Management
正解：A、B
解説：
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.
質問 # 30
What is the purpose of using Resolution in a Monitoring Query Language expression?
- A. Resolution automatically resolves the alarm which is Firing state
- B. Resolution defines the start time of each time window
- C. Resolution is used with suppression to pause alarm during system maintenance
- D. Resolution controls the total length of each time window
正解：D
解説：
In OCI Monitoring's Monitoring Query Language (MQL), Resolution affects data aggregation:
Resolution controls the total length of each time window (A): It specifies the time interval (e.g., 1m for 1 minute) over which metric data is aggregated (e.g., averaged, summed), determining query granularity.
Why not B, C, or D?
B: Start time is set by the query's time range, not Resolution.
C: Resolution doesn't affect alarm states; that's a separate mechanism.
D: Suppression is an alarm feature, unrelated to Resolution.
Resolution fine-tunes metric analysis precision.
質問 # 31
Why do dedicated Vantage Points matter? Select two reasons that apply. (Choose two.)
- A. Applications on-premise or secured network can be tested from a public Vantage Point
- B. Applications on-premise or on secured network cannot be tested from a public Vantage Point
- C. Test internal customer applications
- D. Test Deployment Manager and Scheduler
正解：B、C
解説：
In OCI APM's Synthetic Monitoring, Vantage Points are locations from which synthetic tests (e.g., HTTP requests) are run. Dedicated Vantage Points are private, user-managed instances, distinct from public ones hosted by Oracle:
Applications on-premise or on secured network cannot be tested from a public Vantage Point (B): Public Vantage Points, located in Oracle-managed regions, lack access to private networks (e.g., on-premise servers or firewalled applications). Dedicated Vantage Points, deployed within a user's network, overcome this limitation.
Test internal customer applications (C): Dedicated Vantage Points enable testing of internal applications (e.g., intranet sites) not exposed to the public internet, ensuring performance monitoring from within the secured environment.
Why not A or D?
Test from public Vantage Point (A): Contradicts B; public Vantage Points can't access private networks.
Test Deployment Manager and Scheduler (D): These are unrelated OCI components, not Synthetic Monitoring targets.
Dedicated Vantage Points extend monitoring to restricted environments.
質問 # 32
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
正解：A、D
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 # 33
Which two future resource usages are identified by Exadata Warehouse Insights custom analytics under Operations Insights? (Choose two.)
- A. Memory
- B. Network usage
- C. CPU
- D. AIOps
正解：A、C
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 # 34
Which two are use cases of Oracle Cloud Infrastructure (OCI) Events Service? (Choose two.)
- A. Process files when they are uploaded in an Object Storage bucket
- B. Migrate Events generated by OCI resources from a Source to Target services
- C. Perform cleanup tasks when an OCI resource is terminated
- D. Perform configuration management for deploying, configuring, and managing servers
正解：A、C
解説：
The OCI Events Service enables event-driven automation by reacting to changes in OCI resources. Two valid use cases are:
Process files when they are uploaded in an Object Storage bucket (A): You can create an event rule to trigger an action (e.g., invoking an Oracle Function) when an object is created (com.oraclecloud.objectstorage.createobject). The function could process the file (e.g., image resizing).
Perform cleanup tasks when an OCI resource is terminated (B): An event rule can detect resource termination (e.g., com.oraclecloud.computeapi.terminateinstance.end) and trigger a function to clean up associated resources (e.g., delete volumes).
Why not C or D?
Migrate Events (C): Events Service doesn't "migrate" events; it triggers actions. Migration is more aligned with Service Connector Hub.
Configuration management (D): This is handled by services like Resource Manager or Ansible, not Events Service.
These use cases showcase the service's ability to automate workflows based on resource state changes.
質問 # 35
What two APM agents can Application Performance Monitoring use to collect data? (Choose two.)
- A. Java Agent
- B. Browser Agent
- C. Cloud Agent
- D. Management Agent
正解：A、B
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 # 36
What are the TWO benefits of Observability Lakehouse in Operations Insights? (Choose two.)
- A. Enables custom analytics such as trending, forecasting, capacity planning, workload characterizations
- B. Allows Oracle Enterprise Manager's operations data for various use-cases
- C. Identifies future resource usage Oracle Cloud
- D. Provides data based on a statistical analysis of AI data
正解：A、B
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 # 37
Which of the following capabilities does the performance management feature of Database Management Services offer to a managed database?
- A. Visualizes and performs trend analysis from AWR data to detect issues using AWR Explorer
- B. Automatically invokes full stats gathering of objects to improve performance of regressed SQLs
- C. Dynamically modifies database initialization parameters to improve performance
正解：A
解説：
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.
質問 # 38
In Application Performance Monitoring (APM), a distributed tracing user initiates a request through a browser. What is the first span called?
- A. Root span
- B. Trace ID
- C. Ajax call
正解：A
解説：
In distributed tracing within OCI APM:
Root span (C): The first span in a trace, representing the entry point of a user request (e.g., an HTTP request from a browser). It has no parent span and initiates the chain of subsequent spans across services.
Why not A or B?
Ajax call (A): A type of request, not a span term.
Trace ID (B): A unique identifier for the entire trace, not a span.
The root span is foundational to tracing a request's journey.
質問 # 39
Which of the following features of Logging Analytics is used for identifying and tagging problem logs during ingestion time?
- A. Labels
- B. Log Origin
- C. Entity Type
- D. Extended Fields
正解：A
解説：
In OCI Logging Analytics, Labels enhance log analysis by tagging specific records:
Labels (B): Predefined tags applied during ingestion based on conditions (e.g., "Error" for logs with "error" or "exception"). Labels help categorize and filter problem logs for easier searching and troubleshooting.
Why not A, C, or D?
Entity Type (A): Defines the resource type (e.g., host), not a tagging mechanism.
Log Origin (C): Metadata about log source, not for problem identification.
Extended Fields (D): Custom fields extracted post-ingestion, not tags applied during ingestion.
Labels streamline issue detection at the ingestion stage.
質問 # 40
What are the two items required to create a rule for the Oracle Cloud Infrastructure (OCI) Events Service? (Choose two.)
- A. Rule Conditions
- B. Actions
- C. Install Key
- D. Service Connector
- E. Management Agent Cloud Service
正解：A、B
解説：
To create a rule in the OCI Events Service, you need to define what triggers the rule and what happens when it's triggered. The two required components are:
Actions (B): These specify the tasks to perform when an event matches the rule (e.g., invoking a function, sending a notification, or streaming to a service). Without an action, the rule has no effect.
Rule Conditions (C): These define the criteria for matching events (e.g., event type like com.oraclecloud.computeapi.launchinstance.end or resource attributes). Conditions filter which events trigger the rule.
Why not A, D, or E?
Management Agent Cloud Service (A): This is unrelated to Events Service rules; it's for monitoring resources.
Install Key (D): This is used for agent installation, not event rules.
Service Connector (E): While it can work with Events Service, it's a separate service and not a required component of an event rule itself.
These two elements form the core of an OCI Events Service rule, enabling event-driven automation.
質問 # 41
Your on-premises private cloud environment consists of virtual machines hosting a set of application servers. These VMs are currently monitored using a 3rd party monitoring tool for resource metrics such as CPU and Memory utilization. You have created an automation workflow to transform these application servers into Oracle Cloud Infrastructure (OCI) which will deploy a set of new compute instances. There are a few requirements to consider while running this task: Ensure continuous monitoring is enabled, so the current monitored resource metrics are continuously collected and reported; Monitor the completion of Compute Instance deployment during the workflow and notify with email on each execution; Notify with email for any new OCI Object Storage buckets created after the migration workflow. What solution would you recommend to achieve these requirements?
- A. Configure OCI Compute agent on on-premises VMs and OCI compute instances to collect required resource metrics. Use OCI Events service to track the end-to-end deployment process (com.oraclecloud.computeapi.launchinstance.end) and creation of new bucket (com.oraclecloud.objectstorage.createbucket). Use OCI Notifications and Events services to notify these changes.
- B. Configure OCI Compute agent on OCI compute instances to collect required resource metrics. Use OCI Events and Functions services to track the Instance deployment (com.oraclecloud.computeapi.launchinstance.end) and creation of new buckets (com.oraclecloud.objectstorage.createbucket). Use OCI Notifications and Events service to notify these changes.
- C. Configure OCI Compute agent on on-premises VMs to collect required resource metrics. Use OCI Events service to track all deployments (com.oraclecloud.computeapi.launchinstance.end) with OCI Notifications service to track and report all changes occurring in the target environment.
- D. Configure both 3rd party monitoring tool and OCI Compute Agent on OCI compute instances to collect required resource metrics. Use OCI Events service (com.oraclecloud.computeapi.launchinstance.end) with Notifications service to track and notify all changes occurring in the target OCI environment.
正解：A
解説：
The solution must address continuous monitoring and event-driven notifications:
D:
OCI Compute agent on on-premises VMs and OCI instances: Ensures metric continuity (e.g., CPU, memory) across the migration, using Management Agents for both environments.
Events service: Tracks launchinstance.end for deployment completion and createbucket for new buckets.
Notifications and Events: Sends email alerts for these events.
Why not A, B, or C?
A: Misses on-premises monitoring continuity.
B: Lacks bucket creation tracking.
C: Redundant 3rd-party tool use; OCI agents suffice.
D provides end-to-end coverage.
質問 # 42
How does Application Performance Monitoring track all related spans for a single user request?
- A. Using Trace ID
- B. Using User ID
- C. Using Application Name
正解：A
解説：
APM tracks request flows using:
Using Trace ID (A): A unique identifier assigned to a trace (collection of spans) for a single user request. Propagated via HTTP headers, it links all spans across services.
Why not B or C?
User ID (B): Identifies users, not request flows.
Application Name (C): Too broad; doesn't correlate specific requests.
Trace ID ensures end-to-end visibility in distributed systems.
質問 # 43
Which two functions does the Trace Explorer allow you to do in Application Performance Monitoring (APM)? (Choose two.)
- A. Display status of monitored systems
- B. Select pre-defined queries for common use cases
- C. Define custom metrics for traces
- D. View the details of specific spans
正解：B、D
解説：
The Trace Explorer in OCI Application Performance Monitoring (APM) is a tool for analyzing distributed traces and spans. Its key functions include:
View the details of specific spans (A): Trace Explorer allows users to drill into individual spans within a trace, displaying details such as duration, status, tags, logs, and errors. This helps identify performance bottlenecks or failures in specific service calls.
Select pre-defined queries for common use cases (B): It provides built-in queries (e.g., slowest traces, error traces, traces by service) to quickly filter and analyze common scenarios, enhancing troubleshooting efficiency.
Why not C or D?
Display status of monitored systems (C): System status is monitored via OCI Monitoring or Stack Monitoring, not Trace Explorer, which focuses on traces.
Define custom metrics for traces (D): Custom metrics are defined in OCI Monitoring, not Trace Explorer, which is for viewing, not creating metrics.
Trace Explorer enhances visibility into distributed application performance.
質問 # 44
Which are the different data sources from where the Application Performance Monitoring (APM) Java agent can collect spans and metrics data?
- A. VMware ESXi
- B. NginX
- C. WebLogic, Tomcat, or JBoss
- D. Jaeger or Zipkin
正解：D
解説：
The APM Java Agent collects telemetry from Java applications:
Jaeger or Zipkin (C): These are open-source distributed tracing systems. The Java Agent can integrate with Jaeger- or Zipkin-compatible applications, collecting spans and metrics for APM analysis.
Why not A, B, or D?
NginX (A): A web server; APM uses other agents (e.g., Browser Agent) for such systems.
WebLogic, etc. (B): Application servers, but not direct data sources; the agent collects from the app, not the server type.
VMware ESXi (D): A hypervisor, unrelated to Java tracing.
Jaeger and Zipkin compatibility extends APM's reach.
質問 # 45
What happens in Stack Monitoring after Management Agents are set up and resources are discovered?
- A. Metric data is immediately collected
- B. Management Agents discover resources that are running locally on the instance
- C. OCI Notifications send email notifications
- D. Alarm rules will trigger when resources are down or performance thresholds are crossed
正解：A
解説：
In OCI Stack Monitoring, once Management Agents are deployed and resources (e.g., databases, applications) are discovered, the immediate next step is the collection of metric data.
Metric data is immediately collected (A): Management Agents are lightweight processes that continuously collect performance and health metrics from discovered resources (e.g., CPU usage, memory utilization) and send them to OCI services like Monitoring or Stack Monitoring. This data becomes available for visualization and analysis right after discovery.
Why not B, C, or D?
Alarm rules (B): Alarms are configured separately in the OCI Monitoring service and only trigger after metric data is collected and thresholds are breached-not an immediate post-discovery action.
Resource discovery (C): Discovery happens before this stage, as the question assumes resources are already discovered. Agents don't rediscover resources post-setup.
Notifications (D): Notifications require separate configuration (e.g., via the Notifications service) and are not an automatic outcome of agent setup and discovery.
This aligns with Stack Monitoring's purpose of providing real-time visibility into resource performance.
質問 # 46
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. Analyze and tune SQL performance issues of Oracle Databases on-premises, OCI, and multi-cloud environments
- D. Forecast capacity issues of your Database services in OCI
正解：B、C
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 # 47
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