Two items required to create a rule for the OCI Events Service are:

• Actions. Actions are the tasks that you want to perform when an event matches your rule condition. For example, you can create an action that sends a notification, invokes a function, or streams an event.
• Rule Conditions. Rule Conditions are the criteria that you use to filter events based on their attributes or patterns. For example, you can create a rule condition that matches events related to instance creation or deletion.

A valid Log Category name in OCI Logging Service is Custom Logs. Custom Logs are logs that are generated by your own applications or services that are not part of OCI services. Custom Logs can be collected by Logging Service using various methods, such as Unified Monitoring Agent, SDKs, or APIs. Custom Logs can help you monitor and troubleshoot your custom applications or services.

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.

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.

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.

To archive logging data into OCI Object Storage, you can use Service Connector Hub, which is a cloud message bus platform that offers a single pane of glass for describing, running, and monitoring interactions when moving data between OCI services. You can create a service connector that has Logging as the source service and Object Storage as the target service. This service connector will automatically move your logging data from Logging to Object Storage based on your configuration.

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.

Two actions that can be performed using the Database Management Service in OCI are:

• Compare Database performance across different time periods or perform real-time monitoring of SQL statements. Database Management Service provides various tools and dashboards that let you compare and monitor the performance of your databases and SQL statements. You can use Performance Hub to view real-time and historical performance data of your databases. You can also use SQL Monitor to view real-time and historical execution details of your SQL statements.
• Analyze and Tune SQL performance issues of Oracle Databases on-premises, OCI and Multi-Cloud environment. Database Management Service provides various features and functions that let you analyze and tune SQL performance issues of your databases across different environments. You can use SQL Tuning Advisor to get recommendations for improving SQL performance. You can also use SQL Performance Analyzer to compare the performance of SQL statements before and after a change.

The Management Agent group that allows the agent to upload data to the discovery service is AgentUsersGrp. AgentUsersGrp is a predefined dynamic group that contains all the Management Agents in your tenancy. You need to attach a policy to this group that grants the permission to upload data to the discovery service endpoint.

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.

Two features of OCI that can help you archive Info-level logging data of these instances into the OCI Object Storage are:

• Service Connectors. Service Connectors are components of Service Connector Hub that enable data movement between OCI services. You can create a service connector that has Logging as the source service and Object Storage as thetarget service. You can also specify filters to select only the Info-level logs from your instances.
• 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. For more information, see [Service Connector Hub Overview] and [ObjectCollection Rule].

Two future resource usages that are identified by Exadata Warehouse insights custom analytics under Operations Insights are Memory and CPU. Exadata Warehouse insights custom analytics is a feature of Operations Insights that provides advanced analytics and visualization of Exadata performance data. You can use Exadata Warehouse insights custom analytics to create scenarios based on historical trends, growth rates, and what-if analysis. You can also use Exadata Warehouse insights custom analytics to forecast future resource usages, such as Memory or CPU, and plan capacity for your Exadata systems.

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.

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.

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.

 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.