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| Section | Weight | Objectives |
|---|---|---|
| Define the pillars of Observability | 7% | - Summarize OCI Observability and Management Services |
| Monitor applications with deep visibility into end-user experience | 20% | - Configure application instrumentation and data collection - Analyze application performance and end-user experience - Use Application Performance Monitoring |
| Respond to cloud resource changes in real-time | 10% | - Analyze the key concepts of Events Service - Determine Event Structure, Event Types and Rules - Respond to Events and integration with OCI services |
| Identify log data patterns and create visualizations for advanced analytics | 22% | - Perform advanced log analytics and troubleshooting - Search, filter and visualize log data - Use Logging Analytics for log ingestion and analysis |
| Centrally manage and visualize log data | 16% | - Manage logs using OCI Logging - Configure logging and log connectors - Collect, search and analyze log data |
| Monitor cloud environments with metrics and alarms | 18% | - Discuss enabling Metrics for monitoring OCI resources - Configure Alarm Definitions using best practices - Explain the key concepts of Monitoring Service |
| Monitor distributed components of an application stack | 7% | - Analyze infrastructure and application metrics - Discover and monitor distributed application components - Use Stack Monitoring |
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NEW QUESTION # 11
What are the TWO SQL Warehouse categories to analyze SQL Performance in Operations Insights? (Choose two.)
Answer: A,B
Explanation:
SQL Warehouse in Operations Insights categorizes SQL performance:
* Degraded (A): SQL statements with declining performance over time (e.g., increased latency), indicating potential issues.
* Plan changes (C): SQL statements with altered execution plans, impacting performance or resource use.
* Why not B or D?
* Climbing (B): Not a standard category; possibly a misnomer.
* Efficient (D): Positive performance isn't a focus category.
These help identify and resolve SQL issues.
Reference: SQL Warehouse Categories
NEW QUESTION # 12
Which two components are optional while creating the Monitoring Query Language (MQL) expressions in the Oracle Cloud Infrastructure (OCI) Monitoring service? (Choose two.)
Answer: B,D
Explanation:
MQL expressions in OCI Monitoring retrieve and process metric data. Optional components include:
* Statistic (B): Specifies how to summarize data (e.g., avg, max). If omitted, raw data is returned.
* Grouping Function (D): Aggregates data across metric streams (e.g., by resourceId). It's optional if no grouping is needed.
* Why not A, C, E, or F?
* Interval (A): Defines the time window; defaults apply if omitted, but it's typically required for meaningful queries.
* Previous (C): Not a standard MQL component (possibly a typo).
* Metric (E): Mandatory to specify what's being queried.
* Dimensions (F): Filters data; required if specific streams are targeted, though optional in basic queries.
Statistic and Grouping Function enhance flexibility but aren't mandatory.
Reference: MQL Reference
NEW QUESTION # 13
From the following, select the different metric namespaces used for APM.
Answer: C
Explanation:
APM uses specific metric namespaces to categorize its telemetry data:
* oracle_apm_rum, oracle_apm_synthetics, and oracle_apm_monitoring (D):
* oracle_apm_rum: Metrics from Real User Monitoring (e.g., page load times).
* oracle_apm_synthetics: Metrics from Synthetic Monitoring (e.g., test response times).
* oracle_apm_monitoring: Metrics from distributed tracing (e.g., span counts). These namespaces align with APM's three core features.
* Why not A, B, or C?
* A: Individual metric names, not namespaces.
* B: Incomplete and incorrect namespace naming.
* C: Mixes metric types with partial namespace names.
These namespaces enable targeted metric queries in OCI Monitoring.
Reference: APM Metrics
NEW QUESTION # 14
Which of the following is not a key interaction element in the Log Explorer UI of Logging Analytics?
Answer: D
Explanation:
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.
Reference: Log Explorer UI
NEW QUESTION # 15
Which of the following is required to enable Stack Monitoring?
Answer: A
Explanation:
To enable Stack Monitoring:
* Dynamic group for discovery service (A): A dynamic group defines resources (e.g., compute instances) that Stack Monitoring can discover and monitor. A policy granting permissions to this group is also required.
* Why not B or C?
* Machine Learning group (B): Not a valid OCI concept for Stack Monitoring.
* User group for VCN collection (C): User groups manage human access, not service discovery.
This setup ensures Stack Monitoring can access and monitor resources.
Reference: Stack Monitoring Setup
NEW QUESTION # 16
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