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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitor distributed components of an application stack | 7% | - Use Stack Monitoring - Discover and monitor distributed application components - Analyze infrastructure and application metrics |
| Topic 2: Define the pillars of Observability | 7% | - Summarize OCI Observability and Management Services |
| Topic 3: 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 |
| Topic 4: Respond to cloud resource changes in real-time | 10% | - Respond to Events and integration with OCI services - Analyze the key concepts of Events Service - Determine Event Structure, Event Types and Rules |
| Topic 5: Identify log data patterns and create visualizations for advanced analytics | 22% | - Use Logging Analytics for log ingestion and analysis - Perform advanced log analytics and troubleshooting - Search, filter and visualize log data |
| Topic 6: Centrally manage and visualize log data | 16% | - Manage logs using OCI Logging - Collect, search and analyze log data - Configure logging and log connectors |
| Topic 7: 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 |
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NEW QUESTION # 18
Choose two FluentD scenarios that apply when using continuous log collection with client-side processing.
(Choose two.)
Answer: C,D
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 # 19
Which of the following TWO are stored in a Log Source of Logging Analytics? (Choose two.)
Answer: B,D
Explanation:
A Log Source in Logging Analytics defines how logs are collected and processed:
* Which Parsers to use (A): Specifies the parsers (e.g., Syslog, JSON) that extract fields from logs, enabling structured analysis.
* Where to find Logs (C): Defines the log location (e.g., file path /var/log/messages, database connection string), directing the collection process.
* Why not B or D?
* Where to store Log data (B): Storage is managed by Logging Analytics, not defined in the Source.
* Which Management Agents to use (D): Agents are associated with Entities, not specified in the Source.
These elements configure log ingestion effectively.
Reference: Logging Analytics Log Sources
NEW QUESTION # 20
Which TWO items describe the capabilities of the Oracle Cloud Infrastructure (OCI) Database Management Service? (Choose two.)
Answer: B,C
Explanation:
The Database Management Service enhances database oversight:
* Monitor database performance (B): Provides tools like Performance Hub to track real-time and historical metrics (e.g., CPU, I/O).
* Perform management tasks across a group of databases (C): Database Fleet Management enables bulk operations (e.g., configuration checks, SQL execution) across multiple databases.
* Why not A or D?
* A: Log viewing is via Logging Service, not a core DM feature.
* D: SQL analysis is in Operations Insights, not DM directly.
These capabilities streamline database administration.
Reference: Database Management
NEW QUESTION # 21
Which statement is valid for auto-upgrade of Management Agent?
Answer: D
Explanation:
The auto-upgrade feature for Management Agents ensures they stay current:
* Users cannot disable "auto-upgrade" (B): Auto-upgrade is mandatory and enabled by default, automatically updating agents to the latest version for security and functionality. Users lack an opt-out mechanism.
* Why not A, C, or D?
* A: Incorrect; it's not configurable at the tenancy level.
* C: True that it's enabled by default, but B is more precise about the lack of disable option.
* D: False; auto-upgrade exists.
This ensures consistent agent reliability.
Reference: Management Agent Auto-Upgrade
NEW QUESTION # 22
Which are the different data sources from where the Application Performance Monitoring (APM) Java agent can collect spans and metrics data?
Answer: C
Explanation:
The APM Java Agent collects telemetry from Java applications:
* Jaeger or Zipkin (C): These are open-source distributed tracing systems. The Java Agent can integrate with Jaeger- or Zipkin-compatible applications, collecting spans and metrics for APM analysis.
* Why not A, B, or D?
* NginX (A): A web server; APM uses other agents (e.g., Browser Agent) for such systems.
* WebLogic, etc. (B): Application servers, but not direct data sources; the agent collects from the app, not the server type.
* VMware ESXi (D): A hypervisor, unrelated to Java tracing.
Jaeger and Zipkin compatibility extends APM's reach.
Reference: APM Java Agent
NEW QUESTION # 23
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