Oracle 1z0-1111-23 Oracle Cloud Infrastructure 2023 Observability Professional Exam Practice Test

 You would use a vantage point in Synthetic Monitoring. Synthetic Monitoring is a feature of APM that allows you to create synthetic tests to monitor the availability and performance of your web applications or APIs from different locations around the world. A vantage point is a location from where you can run synthetic tests against your target applications or APIs. A vantage point can be public or dedicated depending on your needs.

Two examples of data telemetry sources of Operations Insights are:

• Enterprise Manager. Enterprise Manager is an on-premises tool that provides comprehensive management and monitoring of Oracle databases and applications. Enterprise Manager can send operational data, such as performance metrics, configuration data, and SQL data, to Operations Insights for analysis and optimization.
• 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 Operations Insights. Management Agent can collect data from various sources, such as databases, hosts, or applications.

Two things that are stored in a Log Source of Logging Analytics are:

• Which parsers to use. A parser is a component that extracts fields and values from log data. A log source can have one or more parsers associated with it to enable Logging Analytics to parse and analyze the log data.
• Where to find logs. A log source defines the location, format, and frequency of the log data. A log source can specify a file path, a database connection string, or a Windows event log name to indicate where to find logs.

The Machine Learning based visualization that is helpful in analyzing extremely large volumes of log records by grouping them based on their shape is Cluster. Cluster is a feature of Logging Analytics that uses machine learning algorithms to group log records into clusters based on their similarity or dissimilarity. Cluster can help you reduce noise, identify patterns, detect anomalies, and troubleshoot issues from your log data.

Database Audit Logs contain rich information to process for analytics, such as user actions, database operations, and security events. Logging Analytics can ingest and analyze these logs to provide insights into the health and performance of your databases.

An Application Performance Monitoring (APM) Domain in OCI is a resource type containing the systems monitored by APM. An APM Domain defines the scope and boundaries of the systems that you want to monitor with APM, such as microservices applications, web servers, databases, or functions. You can create multiple APM Domains for different purposes or environments, such as development, testing, or production.

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, you can use Audit Analysis Dashboard. Audit Analysis Dashboard is a feature of Audit service that provides a graphical representation of audit events and trends. You can use Audit Analysis Dashboard to view charts and tables that show various metrics and dimensions of audit events, such as user activity, resource activity, operation types, or error codes.

 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.

The correct logging CLI syntax for the log search with a query for REST call responses having status code 400, within the web Log Group and the application Log is oci logging-search search-logs --search-query ‘search “ocidl.compartment.ocl…aaaaaaaawqegmjifhni77bqm625cxioavoq775jckfn2syxqtmglabcccdxyz/web/application” I where data.statusCode = 400’–time-start 2022-02-06T00:00:002 --time-end 2022-02-07T00:00:002. This syntax will search for log records that match the following criteria:

• The log records belong to the compartment with OCID ocidl.compartment.ocl…aaaaaaaawqegmjifhni77bqm625cxioavoq775jckfn2syxqtmglabcccdxyz
• The log records belong to the web Log Group and the application Log
• The log records have a field called data.statusCode with a value of 400
• The log records are within the time range from 2022-02-06T00:00:002 to 2022-02-07T00:00:002

Two SQL Warehouse categories to analyze SQL Performance in Operations Insights are:

• Plan changes. Plan changes are SQL statements that have experienced a change in their execution plan over time. Plan changes can affect the performance and resource consumption of SQL statements.
• Degraded. Degraded are SQL statements that have experienced a decrease in their performance over time. Degraded SQL statements can cause performance issues and resource contention in your databases.

The correct monitoring query that will monitor the CPU utilization threshold including an alarm is (CpuUtilization[1m] .max()> 80).grouping().sum (). This query will return the sum of the maximum CPU utilization values for each metric stream in a one-minute interval, and compare it with the threshold value of 80%. If the sum is greater than 80%, the alarm condition is met and an alarm is triggered.

Two reasons why dedicated Vantage points matter are:

• Test internal customer applications. Dedicated Vantage points are private Vantage points that you can deploy in your own network or cloud environment. Dedicated Vantage points allow you to test internal customer applications that are not accessible from the public internet, such as intranet applications or applications behind a firewall.
• Applications on-premise or on secured network cannot be tested from a public Vantage Point. Public Vantage points are Vantage points that are hosted and managed by Oracle in various regions around the world. Public Vantage points allow you to test external customer applications that are accessible from the public internet, such as web applications or APIs. However, public Vantage points cannot test applications that are on-premise or on secured network, as they do not have access to those environments.

 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.

The performance management feature of Database Management Services offers the capability to visualize and perform trend analysis from AWR data to detect issues using AWR explorer. AWR explorer is a tool that lets you view and analyze the Automatic Workload Repository (AWR) data from your databases. You can use AWR explorer to compare performance across different time periods, identify performance bottlenecks, and troubleshoot issues.

A source represents an asset on your host that could provide log data, such as a log file, a database audit log, or a Windows event log. A source defines the location, format, and frequency of the log data. You can associate a source with an entity type to enable Logging Analytics to parse and analyze the log data. For more information, see Sources.

The recommended method to continuously monitor and ingest logs from Object Storage buckets is ObjectCollection Rule. ObjectCollection Rule is a feature of Logging Analytics that allows you to collect log data from objects stored in Object Storage buckets. You can create an ObjectCollection Rule that specifies the bucket name, object name pattern, entity type, and log source for your log data.

Labels are a feature of Logging Analytics that allow you to identify and tag the problem logs during ingestion time. Labels are predefined tags that can be applied to log records based on certain conditions or patterns. For example, you can create a label called “Error” that is applied to any log record that contains the word “error” or “exception”. Labels can help you filter, search, and analyze your log data more efficiently.

A valid statement regarding Management Agent Cloud Service is that Management Agent Cloud Service allows OCI services to collect data from on-premises and cloud assets, and transport data into OCI services, such as Logging Analytics, OCI Monitoring, or even a custom endpoint hosted in OCI. Management Agent Cloud Service does not support transporting data into AWS or GCS.

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.

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.