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Oracle 1Z0-1111-25 시험요강:

주제	소개
주제 1	Define the Pillars of Observability: This section of the exam measures the skills of Cloud Architects and Site Reliability Engineers (SREs) in understanding the three pillars of observability: logs, metrics, and traces. It explains how these components provide insights into system health and performance, enabling effective monitoring and troubleshooting in distributed cloud environments.
주제 2	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.
주제 3	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.
주제 4	Centrally Manage and Visualize Log Data: This section assesses the abilities of Logging Analysts and Security Engineers in managing logs across an entire IT environment. It includes enabling log collection, creating connectors for log transitions, identifying log patterns, and visualizing logs for advanced analytics using OCI Logging Service.
주제 5	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.

최신 Oracle Cloud Infrastructure 1Z0-1111-25 무료샘플문제 (Q46-Q51):

질문 # 46
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. ObjectCollection Rule
B. Cloud Agent Plugin Grouping Function
C. Service Connectors
D. Agent Configuration

정답：A,C

설명：
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.

질문 # 47
You are working on a project to automate the deployment of Oracle Cloud Infrastructure (OCI) compute instances that are pre-configured with web services. As part of the deployment workflow, you also need to create a corresponding OCI object storage bucket bearing the same name as that of the compute instance. Which of these two options can help you achieve this requirement? (Choose two.)

A. Service Connector Hub
B. Oracle Functions
C. Events Service
D. Cloud Agent Plugin for the compute instance
E. OCI CLI command, oci os bucket create auto

정답：A,B

설명：
To automate the creation of an OCI Object Storage bucket with the same name as a compute instance during deployment, you need a mechanism to detect the instance creation event and trigger an action to create the bucket. Two OCI services that can achieve this are Service Connector Hub and Oracle Functions, used in conjunction with the Events Service.
Service Connector Hub (B): This service acts as a cloud message bus that facilitates data movement between OCI services. You can configure a service connector with the Events Service as the source (to detect compute instance creation events, e.g., com.oraclecloud.computeapi.launchinstance.end) and Oracle Functions as the target. The service connector filters and routes the event to trigger a function.
Oracle Functions (C): This is a serverless platform that allows you to write and execute code in response to events. You can create a function that retrieves the compute instance name from the event payload and uses the OCI SDK or API to create an Object Storage bucket with the same name.
Why not A, D, or E alone?
Cloud Agent Plugin (A): This is used for monitoring and managing compute instances but does not directly support bucket creation automation.
OCI CLI command (D): The command oci os bucket create auto is not a valid OCI CLI command (oci os bucket create is valid but requires manual invocation or scripting, not event-driven automation).
Events Service (E): While critical for detecting instance creation, it alone cannot execute the logic to create a bucket-it needs a target like Functions or Notifications.
This solution leverages the event-driven architecture of OCI, combining Events Service (implicitly used with Service Connector Hub) and Oracle Functions for execution.

질문 # 48
Which TWO actions can be performed using the Database Management Service in Oracle Cloud Infrastructure (OCI)? (Choose two.)

A. Analyze and tune SQL performance issues of Oracle Databases on-premises, OCI, and multi-cloud environments
B. Forecast capacity issues of Oracle Databases in on-premises, OCI, and multi-cloud environments
C. Forecast capacity issues of your Database services in OCI
D. Compare database performance across different time periods or perform real-time monitoring of SQL statements

정답：A,D

설명：
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.

질문 # 49
Which is NOT a valid statement regarding the Oracle Cloud Infrastructure (OCI) Audit logs?

A. One of the key reasons to view Audit Logs is to collect security-related events.
B. Audit Logs are disabled by default and must be manually enabled for each compartment in your tenancy.
C. Audit logs can be displayed at the Compartment level.

정답：B

설명：
OCI Audit logs track API operations for security and compliance.
Invalid statement: Audit Logs are disabled by default (B): Audit Logs are enabled by default across all compartments in a tenancy-no manual activation is required. They automatically record all API activities.
Why A and C are valid:
Security-related events (A): Audit Logs capture user actions, making them critical for security monitoring.
Compartment-level display (C): Logs can be filtered and viewed by compartment or tenancy level via the Console or API.
Audit Logs are always active, with a 90-day retention period by default.

질문 # 50
Which is an example of Log Sources in Logging Analytics?

A. JSON, XML, CSV files
B. File, Database, Windows Events System, Syslogs
C. Windows Events, Syslog Listener, and Database SQL parsers
D. Long, Integer, String fields

정답：C

설명：
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.

질문 # 51
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