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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify log data patterns and create visualizations for advanced analytics | 22% | - Distinguish the key concepts of Logging Analytics - Analyze, search, filter and visualize logs - Explore log ingestion methods for Logging Analytics - Present advanced analytics and features for troubleshooting |
| Topic 2: Monitor distributed components of an application stack | 7% | - Analyze discovering resources and monitoring with metrics - Identify the key concepts of Stack Monitoring |
| Topic 3: 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 |
| Topic 4: Centrally manage and visualize log data | 16% | - Distinguish log categories and enable log collection from sources - Explore managing and searching logs from the entire log estate - Create Connectors for Log Transitions |
| Topic 5: Define the pillars of Observability | 7% | - Summarize OCI Observability and Management Services |
| Topic 6: Monitor applications with deep visibility into end-user experience | 20% | - Instrument applications for data collection - Explore the key concepts of Application Performance Monitoring (APM) - Examine visualizing and analyzing performance data |
| Topic 7: Monitor cloud environments with metrics and alarms | 18% | - Configure Alarm Definitions using best practices - Discuss enabling Metrics for monitoring OCI resources - Explain the key concepts of Monitoring Service |
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NEW QUESTION # 44
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: C,D
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 # 45
After creating an APM Domain in OCI Application Performance Monitoring, what is immediately available?
Answer: D
Explanation:
When an APM Domain is created, OCI generates the domain resources required to receive observations, including its data upload endpoint and data keys. The data upload endpoint is the URL to which an APM data source-such as an APM Java Agent, Browser Agent, or supported OpenTelemetry component-sends spans and metrics. Traces are not immediately available because an instrumented application must first collect and upload trace data. Alarm definitions are also not automatically created merely by creating the domain; alarms must be configured separately through OCI Monitoring when required. Consequently, the data upload endpoint is the item available immediately after domain creation and is essential for connecting monitored applications to the APM service. Oracle documentation
NEW QUESTION # 46
Which is the recommended method to continuously monitor and ingest logs from Object Storage buckets?
Answer: C
Explanation:
For continuous log ingestion from Object Storage:
* ObjectCollection Rule (A): A Logging Analytics feature that monitors Object Storage buckets and ingests logs based on defined patterns (e.g., bucket name, object prefix). It's designed for this purpose.
* Why not B, C, or D?
* Object Store (B), Object Storage (C), Object Store Bucket (D): These refer to the storage service or its components, not a method for log ingestion.
ObjectCollection Rule ensures automated, ongoing log collection.
Reference: ObjectCollection Rule
NEW QUESTION # 47
You are part of an organization with thousands of users accessing Oracle Cloud Infrastructure (OCI). An unknown user action was executed, resulting in configuration errors. You are tasked to quickly identify the details of all users who were active in the last six hours along with any REST API calls that were executed.
Which OCI service would you use?
Answer: E
Explanation:
To investigate user activity and REST API calls over the last six hours, the OCI Audit service is the appropriate tool.
* Audit (E): This service automatically records all API operations (including REST API calls) performed on OCI resources. It provides detailed logs with user details, timestamps, and actions, ideal for security and compliance investigations. You can filter audit logs by time range (e.g., last six hours) and user attributes.
* Why not A, B, C, or D?
* Notifications (A): Sends alerts but doesn't store or analyze API call details.
* Service Connectors (B): Moves data between services, not for auditing.
* Management Agent (C): Collects metrics/logs from resources, not API audit data.
* Logging (D): Handles application and system logs, not API activity tracking.
Audit logs are retained for 90 days by default, making this a perfect fit.
Reference: OCI Audit Service
NEW QUESTION # 48
What are the TWO benefits of Observability Lakehouse in Operations Insights? (Choose two.)
Answer: B,D
Explanation:
The Observability Lakehouse in Operations Insights is a data repository for operational analytics:
* Enables custom analytics (B): Supports trending (e.g., usage patterns), forecasting (e.g., resource needs), capacity planning, and workload profiling using advanced analytical tools, enhancing resource optimization.
* Allows Oracle Enterprise Manager's data (D): Integrates operational data from Enterprise Manager (e.
g., database metrics) for use cases like performance analysis and anomaly detection.
* Why not A or C?
* Statistical analysis of AI data (A): Too vague; Lakehouse focuses on operational data, not AI- specific stats.
* Identifies future resource usage (C): Partial benefit of B, but not a standalone feature.
These capabilities improve operational decision-making.
Reference: Operations Insights Observability Lakehouse
NEW QUESTION # 49
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