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| Section | Weight | Objectives |
|---|---|---|
| OCI Monitoring and Metrics | 30% | - Monitoring service concepts and metrics collection - Metric queries, dashboards, and visualization |
| Logging and Log Analytics | 25% | - OCI Logging service and log management - Logging Analytics: ingestion, parsing, and analytics |
| Application Performance Monitoring and Distributed Tracing | 20% | - Distributed tracing, diagnostics, and troubleshooting - APM setup, instrumentation, and end-user monitoring |
| Alarms and Notifications | 25% | - Notifications service and integration patterns - Alarm configuration, thresholds, and status |
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NEW QUESTION # 12
Which two are examples of data telemetry sources of Operations Insights? (Choose two.)
Answer: C,D
Explanation:
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.
Reference: Operations Insights Data Sources
NEW QUESTION # 13
Which statement is NOT valid about creating an alarm query in Oracle Cloud Infrastructure (OCI) Monitoring?
Answer: D
Explanation:
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.
Reference: MQL for Alarms
NEW QUESTION # 14
Which two resources can be monitored by Stack Monitoring? (Choose two.)
Answer: C,D
Explanation:
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.
Reference: Stack Monitoring Resources
NEW QUESTION # 15
Which is the correct Monitoring Query Language expression for determining the total number of hosts whose CPU utilization exceeds a threshold of 80 percent?
Answer: A
Explanation:
The expression first evaluates the maximum CPU utilization for each metric stream over one-minute intervals.
The predicate > 80 converts that result into a Boolean threshold evaluation identifying the streams whose CPU utilization exceeds 80 percent. Parentheses make this threshold query the nested inner expression. The grouping() operation then treats the resulting streams as one group, and sum() calculates the total number of streams satisfying the predicate. Oracle provides this expression as its example for calculating the sum of hosts with CPU utilization greater than 80 percent. Option A reports maximum utilization but applies no threshold. Option B filters by instance shape without counting threshold violations. Option D performs aggregation without first evaluating whether utilization exceeds 80 percent. Oracle documentation
NEW QUESTION # 16
Choose two FluentD scenarios that apply when using continuous log collection with client-side processing.
(Choose two.)
Answer: A,B
Explanation:
FluentD is an open-source data collector used for continuous log collection with client-side processing in OCI Logging. Two applicable scenarios are:
* Managing apps/services which push logs to Object Storage (A): FluentD can be configured to collect logs from applications or services (e.g., Oracle Functions) that write logs to Object Storage buckets. It processes these logs client-side and forwards them to OCI Logging or Logging Analytics.
* Comprehensive monitoring for OKE/Kubernetes (B): FluentD is widely used in Kubernetes environments like Oracle Container Engine for Kubernetes (OKE) to collect logs from pods, containers, and nodes. It processes these logs locally before sending them to OCI services for analysis.
* Why not C or D?
* Monitoring unsupported systems (C): While possible, this is not a primary FluentD scenario in OCI-it's more about extending Management Agent capabilities.
* Log Source (D): This is a component of Logging Analytics, not a FluentD scenario.
FluentD's flexibility makes it ideal for these use cases in OCI's observability ecosystem.
Reference: FluentD with OCI Logging , OKE Logging
NEW QUESTION # 17
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