1z0-1111-23 Sample Questions Answers

Two components that the Management Agent solution includes in the Cloud service are:

• Management Agent. Management Agent is a lightweight process that collects and sends operational data from your resources to OCI services, such as Monitoring, Logging, or Stack Monitoring. Management Agent can collect data from various sources, such as databases, hosts, or applications.
• Management Gateway. Management Gateway is a component that enables secure communication between Management Agents and OCI services. Management Gateway acts as a proxy that encrypts and forwards data from Management Agents to OCI services.

An invalid option for troubleshooting issues in OCI is to leverage OCI Cloud Guard to extract and visualize debug logs generated by your application. OCI Cloud Guard is a service that provides security posture management and threat detection for your OCI resources. Cloud Guard does not extract or visualize debug logs generated by your application. To troubleshoot issues using debug logs, you can use OCI Logging or Logging Analytics services.

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.

 One of the primary use cases for the OCI Observability and Management (O&M) Logging Analytics service is to monitor, aggregate, index, and analyze log data. Logging Analytics is a feature of O&M that provides a unified platform for managing and analyzing log data from various sources, such as OCI services, on-premises systems, or custom applications. Logging Analytics can help you reduce noise, identify patterns, detect anomalies, and troubleshoot issues from your log data.

Two APM agents that Application Performance Monitoring can use to collect data are Browser Agent and Java Agent. Browser Agent is a JavaScript snippet that can be embedded in web pages to collect Real User Monitoring (RUM) data, such as page load time, network latency, or user interactions. Java Agent is a Java library that can be attached to Java applications to collect Application Performance Monitoring (APM) data, such as traces, spans, metrics, or errors.

The SQL Warehouse application within Operations Insights enables insights into the SQL performance. SQL Warehouse is a feature of Operations Insights that provides a centralized repository of SQL performance data from your databases. You can use SQL Warehouse to analyze, compare, and optimize the SQL performance across your database fleet. You can also use SQL Warehouse to identify and troubleshoot SQL performance issues, such as high resource consumption, long execution time, or plan changes.

Dashboard is not a key interaction element in Log Explorer UI of Logging Analytics. The Log Explorer UI consists of four key interaction elements: Time Picker, Fields Panel, Scope Filter, and Results Panel. These elements allow you to search, filter, analyze, and visualize your log data.

 Log Sources in Logging Analytics are predefined parsers that can extract fields from various types of log data, such as Windows Events, Syslog Listener, and Database SQL parsers. Log Sources also provide predefined labels, extended fields, and log origin information for each log type.

Two use cases of OCI Events Service are:

• Perform cleanup tasks when an OCI resource is terminated. For example, you can create an event rule that triggers a function when an instance is terminated (com.oraclecloud.computeapi.terminateinstance.end). The function can perform some cleanup tasks, such as deleting associated resources or sending notifications.
• Process files when they are uploaded in an Object Storage bucket. For example, you can create an event rule that triggers a function when an object is created in a bucket (com.oraclecloud.objectstorage.createobject). The function can process the file, such as resizing an image or converting a document format. For more information, see Events Overview.

In Application Performance Monitoring (APM), the span context information is located in the HTTP header during transfer. Span context is a set of information that identifies a span within a trace, such as Trace ID and Span ID. Span context is propagated across different services and components using HTTP headers. This allows APM to track and correlate the spans for a single user request or transaction.

Two ways to reduce Logging Analytics noise are:

• Use time-picker to limit the volume of logs. Time-picker is a tool that lets you select a specific time range for your log search and analysis. By using time-picker, you can reduce the volume of logs and focus on the relevant time period for your use case.
• Use parsed logs search. Parsed logs search is a feature that lets you search for log records based on the extracted fields and values from the log data. By using parsed logs search, you can filter out the noise and find the log records that match your criteria.

The pillars of Observability are Logs, Metrics, and Traces. Logs are records of events that occur in your system or application. Metrics are numerical measurements that describe the behavior and performance of your system or application. Traces are collections of spans that represent a single user request or transaction across different services and components. You can use Dashboard to create a single view that shows logs, metrics, and traces from various sources in one place.

The data sources from where the APM Java agent can collect spans and metrics data are Jaeger or Zipkin. Jaeger and Zipkin are open source distributed tracing systems that provide end-to-end visibility into complex transactions across multiple services and components. The APM Java agent can collect spans and metrics data from Jaeger or Zipkin compatible applications and send them to APM for analysis and visualization.

The different metric namespaces used for APM are oracle_apm_rum, oracle_apm_synthetics, and oracle_apm_monitoring. A metric namespace is a unique name that identifies the source of the metrics. For APM, there are three metric namespaces that correspond to the three features of APM: Real User Monitoring (oracle_apm_rum), Synthetic Monitoring (oracle_apm_synthetics), and Application Performance Monitoring (oracle_apm_monitoring). You can use these metric namespaces to query and analyze metrics from APM. For more information, see APM Metrics.

To create a corresponding OCI object storage bucket bearing the same name as that of the compute instance, you can use Oracle Functions and Service Connector Hub. Oracle Functions is a serverless platform that lets you create and run functions that respond to events. Service Connector Hub is a cloud message bus platform that lets you move data between OCI services. You can create a service connector that has Events as the source service and Functions as the target service. You can also specify a filter to select only the events related to compute instance creation (com.oraclecloud.computeapi.launchinstance.end). The function can then create an object storage bucket with the same name as the compute instance.

The purpose of using Resolution in a Monitoring Query Language expression is to control the total length of each time window. Resolution is a parameter that specifies how often the query is evaluated and how the metric data is aggregated. For example, a resolution of 1m means that the query is evaluated every minute and the metric data is aggregated into one-minute intervals. Resolution affects the granularity and accuracy of the query results and the alarm condition.

Enterprise Manager is a service that provides comprehensive monitoring and administration capabilities for Oracle Database and Engineered Systems1. Management Agent enables Enterprise Manager to discover, monitor, and manage targets on Oracle Cloud Infrastructure, on-premises, or on other public clouds2.

Logging Analytics is a service that enables devops teams to monitor and troubleshoot issues faster by analyzing data from any source using interactive, intuitive dashboards1. Management Agent collects log data from various sources and sends it to Logging Analytics for parsing and indexing2.