Oracle Oracle Cloud Infrastructure 2025 Observability Professional 1z0-1111-25 Exam Dumps: Updated Questions & Answers (December 2025)

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.

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.

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.

Creating an alarm query in OCI Monitoring involves MQL:

Invalid: You must specify a resource group (D): Resource groups (e.g., groupBy(resourceId)) are optional for aggregating metrics across streams; alarms can function without them.

Why A, B, and C are valid:

A: A statistic (e.g., max, avg) is required to process metric data.

B: An interval (e.g., [1m]) defines the time window, mandatory for evaluation.

C: A metric (e.g., CpuUtilization) is the core of the query.

Resource groups enhance, but aren’t required for, alarms.

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.

Stack Monitoring tracks application stack components:

WebLogic Servers (B): Monitors performance and health of WebLogic instances.

Oracle External Databases (C): Tracks on-premises or cloud Oracle databases outside OCI’s native DBaaS.

Why not A or D?

Object Storage Buckets (A): Not supported by Stack Monitoring; use Logging instead.

Virtual Cloud Networks (D): Network monitoring is separate (e.g., VCN Flow Logs).

These align with Stack Monitoring’s focus on application stacks.

To archive logs from OCI Logging Service to Object Storage, an automated data movement solution is needed:

Service Connector (A): Part of Service Connector Hub, this capability moves data between OCI services. A Service Connector can be configured with Logging as the source and Object Storage as the target, automatically transferring logs based on filters (e.g., log level) or schedules.

Why not B, C, or D?

ObjectCollectionRule (B): Used in Logging Analytics to ingest logsfromObject Storage, not archivetoit.

IAM policy (C): Governs permissions but doesn’t perform data movement.

Logging Query (D): Analyzes logs within Logging Service, not for archiving.

Service Connector ensures seamless, scalable log archiving.

An MQL query for an alarm must evaluate a condition:

(CpuUtilization[1m].max() > 80).grouping().sum() (B):

CpuUtilization[1m]: Queries CPU utilization over 1-minute intervals.

.max(): Takes the maximum value per interval.

> 80: Sets a threshold (80%).

.grouping().sum(): Aggregates across metric streams, triggering the alarm if the sum exceeds 80%.This is a complete alarm query.

Why not A, C, or D?

A: Filters by shape but lacks a threshold or alarm condition.

C: Missing condition for alarming.

D: No threshold; case sensitivity doesn’t match OCI convention.

B ensures threshold-based alerting.

In OCI Logging Analytics, a Source defines the origin of log data from an asset on a host.

Source (B): Represents a log-generating asset (e.g., a file, database audit log, or Windows event log), specifying its location, format, and collection frequency. It’s associated with an Entity to enable log ingestion and parsing.

Why not A, C, or D?

Association (A): Links a Source to an Entity, not the asset itself.

Entity (C): A logical representation of a resource (e.g., a host), not the log source.

Parser (D): Extracts fields from logs, not the asset providing data.

Sources are foundational to log collection in Logging Analytics.

The Trace Explorer in OCI Application Performance Monitoring (APM) is a tool for analyzingdistributed traces and spans. Its key functions include:

View the details of specific spans (A): Trace Explorer allows users to drill into individual spans within a trace, displaying details such as duration, status, tags, logs, and errors. This helps identify performance bottlenecks or failures in specific service calls.

Select pre-defined queries for common use cases (B): It provides built-in queries (e.g., slowest traces, error traces, traces by service) to quickly filter and analyze common scenarios, enhancing troubleshooting efficiency.

Why not C or D?

Display status of monitored systems (C): System status is monitored via OCI Monitoring or Stack Monitoring, not Trace Explorer, which focuses on traces.

Define custom metrics for traces (D): Custom metrics are defined in OCI Monitoring, not Trace Explorer, which is for viewing, not creating metrics.

Trace Explorer enhances visibility into distributed application performance.