1z0-1111-25 Oracle Cloud Infrastructure 2025 Observability Professional Free Practice Exam Questions (2025 Updated)

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.

An APM Domain in OCI defines the monitoring scope for APM:

A resource type containing the systems monitored by APM (B): An APM Domain is a logical container for monitored systems (e.g., microservices, web servers, databases). It groups these resources for trace and metric collection, often separated by environment (e.g., dev, prod).

Why not A, C, or D?

Users, roles, identity (A): Relates to IAM, not APM Domains.

High-availability connectivity (C): Infrastructure concern, not an APM Domain’s purpose.

Compartment (D): Compartments organize resources; APM Domains are specific to monitored systems within them.

APM Domains structure monitoring efforts effectively.

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.

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.

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.

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.

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.

Operations Insights collects telemetry data for analysis from:

Management Agent (C): A lightweight process that gathers metrics (e.g., CPU, memory) from hosts, databases, or applications and sends them to Operations Insights.

Enterprise Manager (D): An on-premises tool that provides database performance and configuration data to Operations Insights.

Why not A or B?

OCI Streams (A): A streaming service, not a telemetry source for Operations Insights.

OCI Functions (B): Serverless compute, not a direct telemetry source.

These sources enable comprehensive resource monitoring.

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.

In OCI Logging, logs are wrapped in a Unified Envelope:

Unified Envelope (D): Contains metadata like logGroupId (the OCID of the Log Group), timeCreated, and compartmentId. This identifies the Log Group for each log entry.

Why not A, B, or C?

Source Section (A): Indicates log origin, not the group OCID.

Data section (B): Holds the log content, not metadata like OCID.

Oracle section (C): Not a valid log section.

The Unified Envelope standardizes log metadata.

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.

Troubleshooting a cloud-native app leverages OCI observability tools:

Invalid: Leverage OCI Cloud Guard to extract and visualize debug logs (D): Cloud Guard is a security posture management and threat detection service, not designed for extracting or visualizing application debug logs.

Why A, B, C, and E are valid:

A: Monitoring provides service metrics (e.g., Function invocation latency).

B: Service Connector moves logs to Logging Analytics for analysis.

C: APM traces Functions performance issues.

E: Logging Service collects app logs directly.

Cloud Guard focuses on security, not debugging.

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.

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.

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.

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.

To investigate user activity and REST API calls over the last six hours, the OCI Audit service is the appropriate tool.

Audit (E): This service automatically records all API operations (including REST API calls) performed on OCI resources. It provides detailed logs with user details, timestamps, and actions, ideal for security and compliance investigations. You can filter audit logs by time range (e.g., last six hours) and user attributes.

Why not A, B, C, or D?

Notifications (A): Sends alerts but doesn’t store or analyze API call details.

Service Connectors (B): Moves data between services, not for auditing.

Management Agent (C): Collects metrics/logs from resources, not API audit data.

Logging (D): Handles application and system logs, not API activity tracking.

Audit logs are retained for 90 days by default, making this a perfect fit.