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Oracle 1Z0-1111-25 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
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	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.
Topic 4	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 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.
Topic 6	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.

Oracle Cloud Infrastructure 2025 Observability Professional Sample Questions (Q57-Q62):

NEW QUESTION # 57
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. Events Service
B. Oracle Functions
C. Service Connector Hub
D. OCI CLI command, oci os bucket create auto
E. Cloud Agent Plugin for the compute instance

Answer: B,C

Explanation:
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.

NEW QUESTION # 58
What two APM agents can Application Performance Monitoring use to collect data? (Choose two.)

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

Answer: B,C

Explanation:
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.

NEW QUESTION # 59
Which are the different data sources from where the Application Performance Monitoring (APM) Java agent can collect spans and metrics data?

A. NginX
B. WebLogic, Tomcat, or JBoss
C. VMware ESXi
D. Jaeger or Zipkin

Answer: D

Explanation:
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.

NEW QUESTION # 60
Which step is essential while building a reliable log monitoring environment?

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

Answer: C

Explanation:
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.

NEW QUESTION # 61
Which of the following features of Logging Analytics is used for identifying and tagging problem logs during ingestion time?

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

Answer: D

Explanation:
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.

NEW QUESTION # 62
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TEST 1Z0-1111-25 TOPICS PDF & 1Z0-1111-25 FREE TEST QUESTIONS

Test 1Z0-1111-25 Topics Pdf & 1Z0-1111-25 Free Test Questions