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| Section | Weight | Objectives |
|---|---|---|
| Monitor distributed components of an application stack | 7% | - Analyze infrastructure and application metrics - Discover and monitor distributed application components - Use Stack Monitoring |
| Define the pillars of Observability | 7% | - Summarize OCI Observability and Management Services |
| 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 |
| Centrally manage and visualize log data | 16% | - Manage logs using OCI Logging - Collect, search and analyze log data - Configure logging and log connectors |
| Respond to cloud resource changes in real-time | 10% | - Determine Event Structure, Event Types and Rules - Respond to Events and integration with OCI services - Analyze the key concepts of Events Service |
| Identify log data patterns and create visualizations for advanced analytics | 22% | - Search, filter and visualize log data - Perform advanced log analytics and troubleshooting - Use Logging Analytics for log ingestion and analysis |
| Monitor applications with deep visibility into end-user experience | 20% | - Analyze application performance and end-user experience - Use Application Performance Monitoring - Configure application instrumentation and data collection |
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NEW QUESTION # 87
You are a cloud administrator tasked with creating a dashboard that displays the distribution of a field's values, such as the number of occurrences of each HTTP error code. Which OCI Logging Analytics visualization should you use?
Answer: D
Explanation:
A pie chart is suitable for displaying how the total number of log records is distributed among the distinct values of a selected field. For example, a query can group records by HTTP status code and calculate the count associated with each code. The pie chart displays each status code as a segment, making the relative proportion of errors such as 400, 401, 404, or 500 easy to compare. A single-number tile presents only one aggregated value and cannot communicate the distribution among multiple codes. A table can list the values and counts but provides less immediate visual comparison. Cluster visualization is a machine learning-based capability that groups log records according to their underlying patterns or shapes rather than simply presenting a categorical field distribution. Therefore, the pie chart is the best answer. Oracle documentation
NEW QUESTION # 88
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?
Answer: B,C
Explanation:
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
NEW QUESTION # 89
You are part of a team that manages a set of workload instances running in an on-premises environment. The Architect team is tasked with designing and configuring Oracle Cloud Infrastructure (OCI) Logging service to collect logs from these instances. There is a requirement to archive Info-level logging data of these instances into OCI Object Storage. Which two features of OCI can help you achieve this? (Choose two.)
Answer: B,C
Explanation:
To collect logs from on-premises instances and archive Info-level logs in OCI Object Storage, you need tools for log ingestion and data movement:
* Service Connectors (A): This feature enables data transfer from OCI Logging (source) to Object Storage (target). You can configure a service connector with a filter (e.g., log level = Info) to archive only Info-level logs.
* ObjectCollection Rule (D): Part of Logging Analytics, this rule collects logs from Object Storage buckets into Logging Analytics for analysis. If logs are first written to Object Storage by an agent, this rule ensures continuous ingestion.
* Why not B or C?
* Agent Configuration (B): Used to set up Management Agents but doesn't handle archiving to Object Storage.
* Cloud Agent Plugin Grouping Function (C): This is not a valid OCI feature.
The workflow involves agents sending logs to Logging, Service Connectors filtering and moving them to Object Storage, and ObjectCollection Rules enabling further analysis.
Reference: Service Connector Hub , ObjectCollection Rule
NEW QUESTION # 90
Which two future resource usages are identified by Exadata Warehouse Insights custom analytics under Operations Insights? (Choose two.)
Answer: A,B
Explanation:
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
NEW QUESTION # 91
Which is NOT a valid statement regarding the Oracle Cloud Infrastructure (OCI) Audit logs?
Answer: C
Explanation:
OCI Audit logs track API operations for security and compliance.
* Invalid statement: Audit Logs are disabled by default (B): Audit Logs are enabled by default across all compartments in a tenancy-no manual activation is required. They automatically record all API activities.
* Why A and C are valid:
* Security-related events (A): Audit Logs capture user actions, making them critical for security monitoring.
* Compartment-level display (C): Logs can be filtered and viewed by compartment or tenancy level via the Console or API.
Audit Logs are always active, with a 90-day retention period by default.
Reference: OCI Audit Overview
NEW QUESTION # 92
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