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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Respond to cloud resource changes in real-time | 10% | - Analyze the key concepts of Events Service - Respond to Events and integration with OCI services - Determine Event Structure, Event Types and Rules |
| Topic 2: Centrally manage and visualize log data | 16% | - Explore managing and searching logs from the entire log estate - Distinguish log categories and enable log collection from sources - Create Connectors for Log Transitions |
| Topic 3: Monitor applications with deep visibility into end-user experience | 20% | - Instrument applications for data collection - Examine visualizing and analyzing performance data - Explore the key concepts of Application Performance Monitoring (APM) |
| Topic 4: Monitor cloud environments with metrics and alarms | 18% | - Discuss enabling Metrics for monitoring OCI resources - Explain the key concepts of Monitoring Service - Configure Alarm Definitions using best practices |
| Topic 5: Identify log data patterns and create visualizations for advanced analytics | 22% | - Present advanced analytics and features for troubleshooting - Distinguish the key concepts of Logging Analytics - Analyze, search, filter and visualize logs - Explore log ingestion methods for Logging Analytics |
| Topic 6: Define the pillars of Observability | 7% | - Summarize OCI Observability and Management Services |
| Topic 7: Monitor distributed components of an application stack | 7% | - Identify the key concepts of Stack Monitoring - Analyze discovering resources and monitoring with metrics |
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NEW QUESTION # 71
There are several ways to reduce Logging Analytics noise. Select the TWO options that apply. (Choose two.)
Answer: A,B
Explanation:
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.
Reference: Logging Analytics Search
NEW QUESTION # 72
What happens in Stack Monitoring after Management Agents are set up and resources are discovered?
Answer: C
NEW QUESTION # 73
Which two are use cases of Oracle Cloud Infrastructure (OCI) Events Service? (Choose two.)
Answer: A,B
Explanation:
The OCI Events Service enables event-driven automation by reacting to changes in OCI resources. Two valid use cases are:
* Process files when they are uploaded in an Object Storage bucket (A): You can create an event rule to trigger an action (e.g., invoking an Oracle Function) when an object is created (com.oraclecloud.
objectstorage.createobject). The function could process the file (e.g., image resizing).
* Perform cleanup tasks when an OCI resource is terminated (B): An event rule can detect resource termination (e.g., com.oraclecloud.computeapi.terminateinstance.end) and trigger a function to clean up associated resources (e.g., delete volumes).
* Why not C or D?
* Migrate Events (C): Events Service doesn't "migrate" events; it triggers actions. Migration is more aligned with Service Connector Hub.
* Configuration management (D): This is handled by services like Resource Manager or Ansible, not Events Service.
These use cases showcase the service's ability to automate workflows based on resource state changes.
Reference: Events Service Use Cases
NEW QUESTION # 74
Which two functions does the Trace Explorer allow you to do in Application Performance Monitoring (APM)? (Choose two.)
Answer: B,D
Explanation:
The Trace Explorer in OCI Application Performance Monitoring (APM) is a tool for analyzing distributed 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.
Reference: APM Trace Explorer
NEW QUESTION # 75
What does Apdex (Application Performance Index) measure in OCI Application Performance Monitoring?
Answer: C
Explanation:
Apdex measures perceived user satisfaction with the response times of applications and services. OCI Application Performance Monitoring compares observed request durations with configured Apdex thresholds and classifies the resulting experience as satisfied, tolerating, or frustrated. These classifications contribute to a decimal score between 0 and 1, where a higher value indicates that a greater proportion of requests delivered an acceptable experience. Apdex thresholds are configured at the APM Domain level and may be applied to spans matching specified patterns. The measurement is not a CPU-utilization percentage, a storage-capacity value, or a simple transaction count. Although those measurements may help diagnose application performance, they do not directly represent user satisfaction. Therefore, user satisfaction based on application response-time thresholds is the correct description. Oracle documentation
NEW QUESTION # 76
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