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Most Recent Oracle 1Z0-1111-23 Exam Dumps
Prepare for the Oracle Cloud Infrastructure 2023 Observability Professional exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Oracle 1Z0-1111-23 exam and achieve success.
The questions for 1Z0-1111-23 were last updated on May 2, 2025.
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Choose two FluentD scenarios that apply when using continuous Log Collection with cli-ent-side processing.? (Choose two.)
Two FluentD scenarios that apply when using continuous Log Collection with client-side processing are:
Managing apps/services which push logs to Object Storage. FluentD is an open source data collector that can collect and process log data from various sources. You can use FluentD to manage apps/services that push logs to Object Storage, such as Oracle Functions or Kubernetes. You can configure FluentD to read logs from Object Storage buckets and send them to Logging Service or Logging Analytics for analysis.
Comprehensive monitoring for OKE/Kubernetes. FluentD is also a popular choice for monitoring Kubernetes clusters, such as Oracle Container Engine for Kubernetes (OKE). You can use FluentD to collect and process logs from Kubernetes pods, containers, and nodes, and send them to Logging Service or Logging Analytics for analysis.
Which TWO functions does the Trace Explorer allow you to do in Application Performance Monitoring (APM)? (Choose two.)
Two functions that the Trace Explorer allows you to do in APM are:
View the details of specific spans. Trace Explorer is a tool that lets you view and analyze the traces and spans collected by APM. You can use Trace Explorer to drill down into the details of specific spans, such as duration, status, tags, logs, and errors.
Select pre-defined queries for common use cases. Trace Explorer also provides a set of pre-defined queries that can help you find traces and spans based on common use cases, such as slowest traces, error traces, or traces by service name.
You are part of an organization with thousands of users accessing Oracle Cloud Infra-structure (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?
To identify the details of all users who were active in the last six hours along with any REST API calls that were executed, you can use OCI Audit service. Audit service is a service that records all the API operations performed on your OCI resources. Audit service provides security, compliance, and governance information about your OCI resources. You can use Audit service to view and search audit events based on various criteria, such as user name, resource type, or time range.
What step must be performed to enable Operations Insights for an Autonomous Database?
To enable Operations Insights for an Autonomous Database, you need to enable Operations Insights for the database in the Autonomous Database details page. This will allow you to monitor and analyze the performance, resource utilization, and SQL activity of your Autonomous Database.
Which statement is NOT valid about creating an alarm query in Oracle Cloud Infrastructure (OCI) Monitoring?
A valid statement about creating an alarm query in OCI Monitoring is that you must specify a resource group. A resource group is an optional feature that allows you to group metrics by certain attributes or tags. By specifying a resource group in your alarm query, you can filter out the metrics that belong to different resource groups and focus on the ones that are relevant for your alarm condition.
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