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Oracle Cloud Infrastructure 2025 Observability Professional資格の取得、最新の1Z0-1111-25問題集

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Oracle 1Z0-1111-25 認定試験の出題範囲：

トピック
出題範囲

トピック 1

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.

トピック 2

Monitor Cloud Environments with Metrics and Alarms: This section tests Oracle Cloud Operators' knowledge of configuring OCI Monitoring Service. It includes enabling metrics for resource monitoring, setting up alarms based on best practices, and responding to real-time changes in cloud environments to ensure system reliability.

トピック 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.

トピック 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.

トピック 5

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.

トピック 6

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.

トピック 7

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.

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1Z0-1111-25専門試験、1Z0-1111-25資格取得

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Oracle Cloud Infrastructure 2025 Observability Professional 認定 1Z0-1111-25 試験問題 (Q34-Q39):

質問 # 34
Which pillars of Observability are available as a single view from the Dashboard?

A. Logging Analytics, Database Management, Stack Monitoring
B. Logs, Metrics, and Traces
C. Log data, Query language, Dashboard widgets
D. Compute, Storage, and Network

正解：B

質問 # 35
There are several ways to reduce Logging Analytics noise. Select the TWO options that apply. (Choose two.)

A. Use histogram records
B. Use specific keywords
C. Use time-picker to limit the volume of logs
D. Use parsed logs search

正解：C、D

解説：
Reducing noise in Logging Analytics improves log analysis focus:
Use parsed logs search (C): Searches based on extracted fields (e.g., severity=ERROR) filter out irrelevant logs, targeting specific issues.
Use time-picker to limit the volume of logs (D): Narrows the time range (e.g., last hour), reducing the dataset to relevant periods.
Why not A or B?
Histogram records (A): Visualizes data distribution, not a noise reduction method.
Specific keywords (B): Useful but less precise than parsed fields; raw text search isn't emphasized in Logging Analytics.
These methods enhance signal-to-noise ratio.

質問 # 36
Which answer best defines an Application Performance Monitoring (APM) Domain in Oracle Cloud Infrastructure (OCI)?

A. A resource type containing the systems monitored by APM
B. A set of resources supporting high-availability connectivity to APM
C. A collection of users, roles, and identity data managing access to APM
D. A compartment containing the data collected by APM

正解：A

解説：
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.

質問 # 37
Which is the correct monitoring query that will monitor the CPU utilization threshold including an alarm?

A. (CpuUtilization[1m].max() > 80).grouping().sum()
B. cpuutilization[1m].max().grouping().sum()
C. CpuUtilization[1m](shape "VM.Standard.E4.Flex").max()
D. CpuUtilization[1m].max()

正解：A

解説：
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.

質問 # 38
In Application Performance Monitoring (APM), where is the span context information located during transfer?

A. In the browser and the microservices
B. In HTTP header
C. In HTTP call
D. In the service boundaries

正解：B

解説：
In OCI APM, span context (e.g., Trace ID, Span ID) is propagated across services to track requests.
In HTTP header (B): Span context is embedded in HTTP headers (e.g., X-B3-TraceId) during transfer between services. This allows APM to correlate spans across distributed systems for a single user request.
Why not A, C, or D?
Service boundaries (A): This is a conceptual term, not a location for data.
HTTP call (C): Too vague-"HTTP call" isn't a specific storage location.
Browser and microservices (D): Context originates here but is transferred via headers, not stored locally during transit.
This follows the OpenTracing standard used by OCI APM.

質問 # 39
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