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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitor applications with deep visibility into end-user experience | 20% | - Explore the key concepts of Application Performance Monitoring (APM) - Examine visualizing and analyzing performance data - Instrument applications for data collection |
| Topic 2: 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 3: 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 |
| Topic 4: Define the pillars of Observability | 7% | - Summarize OCI Observability and Management Services |
| Topic 5: 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 6: 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 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 # 83
From the following, select the different metric namespaces used for APM.
Answer: D
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 # 84
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: D
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 # 85
To better manage resource utilization in your environment, you decide to notify your team whenever a new compute instance is created. What should you create to accomplish this task?
Answer: B
Explanation:
OCI Events is designed to detect resource-state changes and trigger defined actions. An Events rule can match the Compute service's Instance - Launch End event, represented by com.oraclecloud.computeapi.
launchinstance.end, and deliver the event to a Notifications topic. The topic then forwards a message to its confirmed subscriptions, such as email or HTTPS endpoints. An autoscaling policy creates or removes instances according to performance criteria, but it does not satisfy the requirement to notify the team about every newly created instance. A Monitoring query evaluates metric data emitted by existing resources and is not the appropriate mechanism for detecting completion of a resource-creation API operation. Therefore, an Events rule using the Launch End event and a Notifications action is the correct solution. Oracle Events documentation
NEW QUESTION # 86
As a solutions architect for an Oracle Cloud Infrastructure tenancy, you have been asked to give members of the CloudOps group permission to view and retrieve monitoring metrics, but only for monitoring-enabled compute instances. Which policy statement grants this access?
Answer: C
Explanation:
OCI Monitoring supports the target.metrics.namespace policy variable for restricting access to metrics belonging to a particular service or resource category. Monitoring-enabled compute instances publish their standard instance metrics under the oci_computeagent namespace. Accordingly, the policy grants the CloudOps group read access to metrics throughout the tenancy while limiting permitted queries to that namespace. Option B uses the unsupported variable target.metrics.monitoring. Option C uses compute- metrics, which is not the Monitoring IAM resource type required by this policy. Option A is incorrect because namespace-based access restrictions are explicitly supported. This policy permits members to inspect and retrieve compute-agent metrics without granting equivalent access to metrics from unrelated namespaces such as Object Storage, load balancers, or databases. Oracle documentation
NEW QUESTION # 87
What are the TWO benefits of Observability Lakehouse in Operations Insights? (Choose two.)
Answer: A,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 # 88
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