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

An essential step while building a reliable log monitoring environment is noise baseline determination. Noise baseline is the level of noise or irrelevant log data that is present in your environment. By determining the noise baseline, you can filter out the noise and focus on the signal or meaningful log data that can help you monitor and troubleshoot your environment. For more information, see Reducing Noise.

 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 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.

To grant the CloudOps group the ability to view and retrieve monitoring metrics only for all monitoring-enabled compute instances, you need to use a policy statement with a condition that filters by the metric namespace. The metric namespace is a unique name that identifies the source of the metrics. For compute instances, the metric namespace is oci_computeagent. Therefore, the policy statement should be: Allow group cloudops to read metrics in tenancy where target.metrics.namespace=‘oci_computeagent’

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.

 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.

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.

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.

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.

• Exadata Insights. Exadata Insights is a feature of Operations Insights that provides comprehensive monitoring and analysis of your Exadata systems, both on-premises and in the cloud. You can use Exadata Insights to view performance, utilization, availability, and configuration metrics of your Exadata systems and components. You can also use Exadata Insights to troubleshoot issues, optimize performance, and plan capacity for your Exadata systems.
• Capacity Planning. Capacity Planning is a feature of Operations Insights that helps you forecast the future resource consumption and capacity needs of your databases. You can use Capacity Planning to create scenarios based on historical trends, growth rates, and what-if analysis. You can also use Capacity Planning to compare different scenarios and identify potential risks and opportunities for your database capacity.

The details stored in the External Database service’s database connection resource that are required to connect to an external database are DNS hostname, database name, connection type and management agent OCID, user credentials, and role. These details specify the information needed to establish a secure connection to the external database using amanagement agent. The DNS hostname is the fully qualified domain name of the host where the external database is running. The database name is the unique name of the external database. The connection type is the protocol used to connect to the external database, such as JDBC or OCI. The management agent OCID is the unique identifier of the management agent that is installed on the host where the external database is running. The user credentials are the username and password of the user who has access to the external database. The role is the privilege level of the user, such as normal or sysdba.

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 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.

In APM, a distributed tracing user initiates a request through a browser. The first span is called the root span. A root span is the span that represents the entry point of a trace, such as an HTTP request from a browser or a message from a queue. A root span has no parent span and can have zero or more child spans.

Two components that are optional while creating MQL expressions in OCI Monitoring service are Grouping Function and Statistic. MQL expressions are queries that specify how to retrieve and process metric data from OCI Monitoring service. MQL expressions consist of various components, such as metric name, dimensions, filters, functions, operators, or constants. Some components are mandatory while others are optional depending on your use case. Grouping Function is an optional component that specifies how to aggregate metric data across different metric streams based on certain attributes or tags. Statistic is an optional component that specifies how to summarize metric data within each time window based on certain calculations or methods.

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.