最新の[2025年06月13日]Oracle 1Z0-1111-25試験練習テスト最高成績で最速合格をゲットせよ! [Q11-Q33]

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最新の[2025年06月13日]Oracle 1Z0-1111-25試験練習テスト最高成績で最速合格をゲットせよ!

これを使えば必ず合格させる問題集でOracle 1Z0-1111-25

質問 # 11
Which two features are provided by Application Performance Monitoring? (Choose two.)

  • A. Distributed Tracing
  • B. Java Management
  • C. Capacity Planning
  • D. Real User Monitoring

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 # 12
You are part of a team that manages a set of workload instances running in an on-premises environment. The Architect team is tasked with designing and configuring Oracle Cloud Infrastructure (OCI) Logging service to collect logs from these instances. There is a requirement to archive Info-level logging data of these instances into OCI Object Storage. Which two features of OCI can help you achieve this? (Choose two.)

  • A. Cloud Agent Plugin Grouping Function
  • B. Service Connectors
  • C. ObjectCollection Rule
  • D. Agent Configuration

正解:B、C

解説:
To collect logs from on-premises instances and archive Info-level logs in OCI Object Storage, you need tools for log ingestion and data movement:
Service Connectors (A): This feature enables data transfer from OCI Logging (source) to Object Storage (target). You can configure a service connector with a filter (e.g., log level = Info) to archive only Info-level logs.
ObjectCollection Rule (D): Part of Logging Analytics, this rule collects logs from Object Storage buckets into Logging Analytics for analysis. If logs are first written to Object Storage by an agent, this rule ensures continuous ingestion.
Why not B or C?
Agent Configuration (B): Used to set up Management Agents but doesn't handle archiving to Object Storage.
Cloud Agent Plugin Grouping Function (C): This is not a valid OCI feature.
The workflow involves agents sending logs to Logging, Service Connectors filtering and moving them to Object Storage, and ObjectCollection Rules enabling further analysis.


質問 # 13
Which pillars of Observability are available as a single view from the Dashboard?

  • A. Logs, Metrics, and Traces
  • B. Log data, Query language, Dashboard widgets
  • C. Logging Analytics, Database Management, Stack Monitoring
  • D. Compute, Storage, and Network

正解:A


質問 # 14
What is enabled by the SQL Warehouse application within Operations Insights?

  • A. Insights into the SQL performance
  • B. Trend and Forecast resource requirements
  • C. Reduced Operations costs
  • D. Consolidated Databases

正解:A

解説:
The SQL Warehouse in Operations Insights focuses on SQL-level analysis:
Insights into the SQL performance (A): Provides a centralized repository of SQL performance data (e.g., execution time, resource usage) from monitored databases, enabling detailed analysis and optimization.
Why not B, C, or D?
Trend and Forecast (B): Handled by Capacity Planning in Operations Insights, not SQL Warehouse.
Consolidated Databases (C): A misnomer; it's about data, not database consolidation.
Reduced costs (D): An outcome, not a direct feature.
SQL Warehouse enhances database performance visibility.


質問 # 15
Which is one of the primary use cases for the Oracle Cloud Infrastructure (OCI) Observability and Management (O&M) Logging Analytics service?

  • A. Create OCI resources automatically based on log events and reports
  • B. Centralize and relocate any log based on a subscription model
  • C. Monitor, aggregate, index, and analyze log data

正解:C

解説:
Logging Analytics is a core O&M service:
Monitor, aggregate, index, and analyze log data (A): Collects logs from OCI and external sources, indexes them for search, and provides analytics (e.g., clustering) to monitor and troubleshoot systems.
Why not B or C?
B: Log centralization occurs, but "subscription model" isn't a feature.
C: Resource creation is an Events Service use case, not Logging Analytics.
This is its primary observability role.


質問 # 16
Which TWO Observability and Management (O&M) services are supported by Management Agent? (Choose two.)

  • A. Logging Analytics
  • B. Enterprise Manager
  • 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 # 17
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 # 18
What two APM agents can Application Performance Monitoring use to collect data? (Choose two.)

  • A. Management Agent
  • B. Browser Agent
  • C. Java Agent
  • D. Cloud Agent

正解:B、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 # 19
You have configured an Alarm Definition in the Oracle Cloud Infrastructure (OCI) Monitoring service to send notifications through email. The alarm should resend notifications at specified intervals if the alarm continues to be in the firing state. A subscriber in the Notifications Topic complains about not receiving multiple emails upon failures. Which of the following could be the possible cause of this issue?

  • A. OCI Monitoring service can send only one notification per Alarm Definition when the alarm condition is met.
  • B. Resending notifications depends on the total metric streams returned from the query.
  • C. Trigger Condition was not configured while defining the Alarm.
  • D. Repeat notification was not enabled while creating the Alarm.

正解:D

解説:
For repeated notifications in OCI Monitoring:
Repeat notification was not enabled while creating the Alarm (B): The "Repeat Notification" option must be enabled in the alarm definition, specifying an interval (e.g., every 5 minutes). If disabled, only one notification is sent when the alarm fires, explaining the subscriber's issue.
Why not A, C, or D?
A: False; OCI supports repeat notifications if configured.
C: Trigger condition is mandatory for any alarm; this isn't the issue.
D: Notification frequency isn't tied to metric streams, only the repeat setting.
Repeat Notification ensures ongoing alerts.


質問 # 20
Which TWO items describe the capabilities of the Oracle Cloud Infrastructure (OCI) Database Management Service? (Choose two.)

  • A. Analyze SQL response time across a group of databases
  • B. Monitor database performance
  • C. Perform management tasks across a group of databases
  • D. View database log entries

正解:B、C

解説:
The Database Management Service enhances database oversight:
Monitor database performance (B): Provides tools like Performance Hub to track real-time and historical metrics (e.g., CPU, I/O).
Perform management tasks across a group of databases (C): Database Fleet Management enables bulk operations (e.g., configuration checks, SQL execution) across multiple databases.
Why not A or D?
A: Log viewing is via Logging Service, not a core DM feature.
D: SQL analysis is in Operations Insights, not DM directly.
These capabilities streamline database administration.


質問 # 21
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 # 22
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

正解:B

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 # 23
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 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.
  • B. 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.
  • C. 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.
  • D. 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.

正解:D

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 # 24
Which two are use cases of Oracle Cloud Infrastructure (OCI) Events Service? (Choose two.)

  • A. Perform configuration management for deploying, configuring, and managing servers
  • B. Process files when they are uploaded in an Object Storage bucket
  • C. Migrate Events generated by OCI resources from a Source to Target services
  • D. Perform cleanup tasks when an OCI resource is terminated

正解:B、D

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 # 25
Which of the following details stored in the External Database service's database connection resource are required to connect to an external database?

  • A. DNS hostname, port, service name, network protocol, connection type and management agent OCID, user credentials, and role
  • B. DNS hostname, database name, connection type and management agent OCID, user credentials, and role
  • C. Port, service name, connection type and management agent OCID, user credentials, and role
  • D. Port, database name, connection type and management agent OCID, user credentials, and role

正解:B

解説:
Connecting to an external database via OCI's External Database service requires specific connection details:
DNS hostname, database name, connection type and management agent OCID, user credentials, and role (C):
DNS hostname: The fully qualified domain name of the database host.
Database name: Unique identifier of the database.
Connection type: Protocol (e.g., JDBC, OCI).
Management agent OCID: Identifier of the agent on the host.
User credentials: Username and password.
Role: Privilege level (e.g., SYSDBA).
These are the minimum required fields for secure connectivity.
Why not A, B, or D?
A: Missing DNS hostname, critical for locating the host.
B: Missing DNS hostname; port alone isn't sufficient.
D: Includes extras (e.g., port, network protocol) that are optional or inferred.
This ensures accurate database connectivity.


質問 # 26
Which of the following features of Logging Analytics is used for identifying and tagging problem logs during ingestion time?

  • A. Labels
  • B. Entity Type
  • C. Extended Fields
  • D. Log Origin

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 # 27
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. Alarm rules will trigger when resources are down or performance thresholds are crossed
  • D. OCI Notifications send email notifications

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 # 28
Which step is essential while building a reliable log monitoring environment?

  • A. Define permissions for the user roles in the region
  • B. Determination of the Machine Learning models you need to program
  • C. Noise baseline determination
  • D. Creation of the Key Performance Indicators (KPIs) to monitor

正解:C

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 # 29
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 # 30
Which is a valid Log Category name in Oracle Cloud Infrastructure (OCI) Logging Service?

  • A. OCI Agent Logs
  • B. System Logs
  • C. VCN Logs
  • D. Custom Logs

正解:D

解説:
In OCI Logging Service, Log Categories classify logs based on their origin or purpose.
Custom Logs (D): This is a valid Log Category for logs generated by user applications or services not natively integrated with OCI. Custom Logs are collected using agents, SDKs, or APIs and are user-defined.
Why not A, B, or C?
VCN Logs (A): Virtual Cloud Network (VCN) flow logs exist, but "VCN Logs" isn't a formal Log Category; it's a type of service log.
OCI Agent Logs (B): Agent logs are internal to Management Agents, not a user-facing Log Category.
System Logs (C): While system logs exist in some contexts, OCI Logging uses specific categories like "Audit Logs" or "Service Logs," not a generic "System Logs."
"Custom Logs" is explicitly supported for user-generated log data.


質問 # 31
What are the TWO SQL Warehouse categories to analyze SQL Performance in Operations Insights? (Choose two.)

  • A. Efficient
  • B. Degraded
  • C. Climbing
  • D. Plan changes

正解:B、D

解説:
SQL Warehouse in Operations Insights categorizes SQL performance:
Degraded (A): SQL statements with declining performance over time (e.g., increased latency), indicating potential issues.
Plan changes (C): SQL statements with altered execution plans, impacting performance or resource use.
Why not B or D?
Climbing (B): Not a standard category; possibly a misnomer.
Efficient (D): Positive performance isn't a focus category.
These help identify and resolve SQL issues.


質問 # 32
What are the two capabilities available in Operations Insights? (Choose two.)

  • A. Entity Topology Viewing
  • B. Capacity Planning
  • C. Exadata Insights
  • D. Database Fleet Monitoring

正解:B、C

解説:
Operations Insights provides:
Capacity Planning (A): Forecasts resource needs based on historical trends and scenarios.
Exadata Insights (D): Analyzes Exadata system performance and capacity.
Why not B or C?
Database Fleet Monitoring (B): A goal, not a named capability; covered under broader features.
Entity Topology Viewing (C): More aligned with Stack Monitoring, not Operations Insights.
These capabilities optimize resource management.


質問 # 33
......


Oracle 1Z0-1111-25 認定試験の出題範囲:

トピック出題範囲
トピック 1
  • Monitor Cloud Environments with Metrics and Alarms: This section tests Oracle Cloud Operators' knowledge of configuring OCI Monitoring Service. It includes enabling metrics for resource monitoring, setting up alarms based on best practices, and responding to real-time changes in cloud environments to ensure system reliability.
トピック 2
  • Summarize OCI Observability and Management Services: This section evaluates the expertise of DevOps Engineers and IT Operations Managers in utilizing Oracle Cloud Infrastructure (OCI) Observability and Management services. It covers tools for monitoring, auditing, and managing cloud resources, emphasizing automation and machine learning-driven insights to optimize IT operations.
トピック 3
  • Monitor Applications with Deep Visibility into End-User Experience: This domain tests the knowledge of Application Performance Engineers and DevOps Specialists in using OCI Application Performance Monitoring (APM). It includes instrumenting applications for data collection, analyzing performance metrics, visualizing distributed application components, and diagnosing issues across multi-tier architectures.
トピック 4
  • Respond to Cloud Resource Changes in Real-Time: This domain measures the skills of Event Managers and Integration Specialists in using OCI Events Service. It covers event structures, types, rules, and integration with other OCI services to respond effectively to resource changes and automate workflows.
トピック 5
  • Monitor Distributed Components of an Application Stack: This section measures the skills of Stack Monitoring Specialists and Cloud Administrators in using OCI Stack Monitoring. It covers discovering resources within application stacks, monitoring metrics across distributed components, and ensuring optimal performance through effective resource management.
トピック 6
  • Distinguish the Key Concepts of Logging Analytics: This section evaluates the expertise of Data Analysts and Troubleshooting Specialists in using OCI Logging Analytics. It covers log ingestion methods, searching and filtering logs, performing advanced analytics, and leveraging machine learning-powered insights for proactive issue resolution.

 

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