Free Practice Questions for Oracle 1z0-1111-25 Exam

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.

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.

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.

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.

The Log Explorer UI in OCI Logging Analytics includes four key interaction elements: Fields Panel, Time Picker, Scope Filter, and Results Panel. These allow users to search, filter, and analyze logs interactively.

Dashboard (D): This is not part of the Log Explorer UI. Dashboards are separate visualizations in Logging Analytics for summarizing data, not an interactive element of the Log Explorer.

Why A, B, and C are key elements:

Fields Panel (A): Displays log fields for filtering and analysis.

Time Picker (B): Sets the time range for log queries.

Scope Filter (C): Defines the scope (e.g., compartments, log groups) of the log search.

For repeated notifications in OCI Monitoring:

Repeat notification was not enabled while creating the Alarm (B): The “Repeat Notification” option must be enabled in the alarm definition, specifying an interval (e.g., every 5 minutes). If disabled, only one notification is sent when the alarm fires, explaining the subscriber’s issue.

Why not A, C, or D?

A: False; OCI supports repeat notifications if configured.

C: Trigger condition is mandatory for any alarm; this isn’t the issue.

D: Notification frequency isn’t tied to metric streams, only the repeat setting.

Repeat Notification ensures ongoing alerts.

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.

The Observability Lakehouse in Operations Insights is a data repository for operational analytics:

Enables custom analytics (B): Supports trending (e.g., usage patterns), forecasting (e.g., resource needs), capacity planning, and workload profiling using advanced analytical tools, enhancing resource optimization.

Allows Oracle Enterprise Manager’s data (D): Integrates operational data from Enterprise Manager (e.g., database metrics) for use cases like performance analysis and anomaly detection.

Why not A or C?

Statistical analysis of AI data (A): Too vague; Lakehouse focuses on operational data, not AI-specific stats.

Identifies future resource usage (C): Partial benefit of B, but not a standalone feature.

These capabilities improve operational decision-making.

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.