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[General] Exam 1Z0-1111-25 Objectives Pdf, Latest 1Z0-1111-25 Study Materials

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【General】 Exam 1Z0-1111-25 Objectives Pdf, Latest 1Z0-1111-25 Study Materials

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Oracle 1Z0-1111-25 Exam Syllabus Topics:
TopicDetails
Topic 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.
Topic 2
  • 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.
Topic 3
  • 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.
Topic 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.

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Oracle Cloud Infrastructure 2025 Observability Professional Sample Questions (Q29-Q34):NEW QUESTION # 29
Which is an example of Log Sources in Logging Analytics?
  • A. Windows Events, Syslog Listener, and Database SQL parsers
  • B. File, Database, Windows Events System, Syslogs
  • C. JSON, XML, CSV files
  • D. Long, Integer, String fields
Answer: A
Explanation:
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.

NEW QUESTION # 30
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. Forecast capacity issues of your Database services in OCI
  • C. Compare database performance across different time periods or perform real-time monitoring of SQL statements
  • D. Analyze and tune SQL performance issues of Oracle Databases on-premises, OCI, and multi-cloud environments
Answer: C,D
Explanation:
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.

NEW QUESTION # 31
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. Ajax call
  • C. Trace ID
Answer: A
Explanation:
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.

NEW QUESTION # 32
Which pillars of Observability are available as a single view from the Dashboard?
  • A. Log data, Query language, Dashboard widgets
  • B. Logs, Metrics, and Traces
  • C. Compute, Storage, and Network
  • D. Logging Analytics, Database Management, Stack Monitoring
Answer: B
Explanation:
OCI Dashboards consolidate the three pillars of observability:
Logs, Metrics, and Traces (A):
Logs: Event records from Logging Service.
Metrics: Numeric data from Monitoring Service.
Traces: Request flows from APM.
These can be visualized together in OCI Dashboards for unified observability.
Why not B, C, or D?
B: Resource categories, not pillars.
C: Tools or components, not pillars.
D: OCI services, not the core concepts.
This integration enhances system visibility.

NEW QUESTION # 33
What are the TWO SQL Warehouse categories to analyze SQL Performance in Operations Insights? (Choose two.)
  • A. Plan changes
  • B. Degraded
  • C. Efficient
  • D. Climbing
Answer: A,B
Explanation:
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.

NEW QUESTION # 34
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