Oracle 1z0-1111-23 Dumps

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.

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.

 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 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.

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.

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 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].

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.

After Management agents are set up and resources are discovered, metric data is immediately collected. Management agents are lightweight processes that collect and send metric data from your resources to OCI services, such as Monitoring, Logging, or Stack Monitoring. Once the resources are discovered by the discovery service, the metric data is immediately collected and available for monitoring and analysis.

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.

The section within a Log that contains the Log Group’s OCID is Unified Envelope. Unified Envelope is a standard format that wraps around any log record collected by Logging Service. Unified Envelope contains metadata about the log record, such as timeCreated, compartmentId, logGroupId, or source. The logGroupId field contains the OCID of the Log Group that the log record belongs to.

A valid statement regarding the OCI Audit logs is that Audit Logs are enabled by default and do not need to be manually enabled for each compartment in your tenancy. Audit Logs are records of the API operations performed on your OCI resources. Audit Logs provide security, compliance, and governance information about your OCI resources. You can view Audit Logs at the compartment level or at the tenancy level.

 Two benefits of Observability Lakehouse in Operations Insights are:

• Allows Oracle Enterprise Manager’s operations data for various use-cases. Observability Lakehouse is a data lake that stores and analyzes operational data from different sources, such as Oracle Enterprise Manager, Oracle Cloud Infrastructure, and Autonomous Database. You can use Observability Lakehouse to access and query your operations data for various use-cases, such as performance analysis, capacity planning, anomaly detection, and root cause analysis.
• Enables custom analytics such as trending, forecasting, capacity planning, workload characterizations. Observability Lakehouse provides a rich set of analytical functions and tools that let you perform custom analytics on your operations data. You can use Observability Lakehouse to create trends, forecasts, capacity plans, workload profiles, and other insights that can help you optimize your operations and performance.

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 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 resend notifications at specified intervals if the alarm continues to be in the firing state, you need to enable repeat notification while creating the alarm. Repeat notification is an optional feature that allows you to specify how often you want to receive notifications for an alarm that remains in the firing state. For more information, see Creating Alarms.

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.

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.

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.

Application Performance Monitoring tracks all related spans for a single user request using Trace ID. A trace is a collection of spans that represent a single user request or transaction. A span is a unit of work within a trace, such as an HTTP request or a database query. Each trace has a unique Trace ID that identifies it across different services and components. You can use Trace ID to search and analyze traces in Application Performance Monitoring. For more information, see Traces and Spans.