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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Logging and Log Analytics | 25% | - OCI Logging service and log management - Logging Analytics: ingestion, parsing, and analytics |
| Topic 2: OCI Monitoring and Metrics | 30% | - Metric queries, dashboards, and visualization - Monitoring service concepts and metrics collection |
| Topic 3: Alarms and Notifications | 25% | - Notifications service and integration patterns - Alarm configuration, thresholds, and status |
| Topic 4: Application Performance Monitoring and Distributed Tracing | 20% | - APM setup, instrumentation, and end-user monitoring - Distributed tracing, diagnostics, and troubleshooting |
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質問 # 45
Which two future resource usages are identified by Exadata Warehouse Insights custom analytics under Operations Insights? (Choose two.)
正解：B、C
解説：
Exadata Warehouse Insights in OCI Operations Insights provides advanced analytics to forecast resource usage for Exadata systems.
* Memory (A): Tracks and predicts memory utilization based on historical trends, aiding capacity planning.
* CPU (D): Forecasts CPU usage, helping identify potential bottlenecks or over-provisioning.
* Why not B or C?
* Network usage (B): While monitored, it's not a primary focus of Exadata Warehouse Insights' future usage predictions.
* AIOps (C): This is a methodology, not a resource usage metric.
These forecasts leverage historical data and what-if analysis for proactive management.
Reference: Exadata Warehouse Insights
質問 # 46
In OCI Log Analytics, which attribute is used to select parsers for logs collected from OCI services?
正解：A
解説：
An entity type identifies the category of resource that produces the logs, such as an OCI Compute Instance, APM Domain, Load Balancer, Object Storage bucket, or Events service rule. When defining a Log Analytics source, the selected entity type establishes the resource context and helps determine which entities and relevant processing definitions can be associated with that source. The source then includes one or more parsers appropriate for the expected log format. Lookups enrich fields by mapping existing values to additional information, while labels tag records-often to identify problem conditions-during processing.
Fields are the individual values extracted from log entries by a parser. They do not determine which parser should process an OCI service's logs. Among the provided choices, Entity Type is therefore the correct selection attribute. Oracle documentation
質問 # 47
What is the Apdex score range in OCI Application Performance Monitoring, and what does a higher score indicate?
正解：B
解説：
Apdex, or Application Performance Index, is an industry-standard measurement of application performance and user satisfaction. OCI Application Performance Monitoring represents it as a decimal value between 0 and 1. A value closer to 1 indicates that a larger proportion of observed requests met the configured satisfied- response-time threshold and therefore reflects a better user experience. Lower values indicate that more requests were classified as tolerating or frustrated. Apdex is calculated using response-time thresholds configured at the APM Domain level, but the score itself is not a duration measured in milliseconds. It is also not expressed as a percentage from 0 to 100 or on a scale containing negative values. Thus, option A correctly describes both its range and interpretation. Oracle documentation
質問 # 48
A cloud operations team is using LoganAI to analyze large volumes of log data ingested into OCI Log Analytics. Which two LoganAI capabilities support this analysis?
正解：A、B
解説：
LoganAI is the artificial intelligence capability integrated with Oracle Log Analytics. Its Explain features generate concise summaries and interpretations for individual log records, multiple records, clusters, issues, outliers, and supported charts. This helps administrators understand large datasets without manually reading every log entry. LoganAI also generates relevant, context-aware follow-up questions and permits users to ask their own questions, supporting an interactive investigation of patterns, anomalies, and potential problems.
The capability can explain complex log information in accessible language and accelerate troubleshooting, although Oracle recommends validating AI-generated conclusions before making operational decisions.
LoganAI does not migrate logs between regions and does not automatically provision sources for log ingestion. Those are separate administrative and data-management activities. Therefore, summaries and interactive follow-up questions are the two valid capabilities. Oracle documentation
質問 # 49
Which is the correct monitoring query that will monitor the CPU utilization threshold including an alarm?
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.
Reference: Creating Alarms with MQL
質問 # 50
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