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

A valid statement for auto-upgrade of Management Agent is that users cannot disable “auto-upgrade”. Auto-upgrade is a feature that automatically updates the Management Agent software to the latest version when it is available. Auto-upgrade is always enabled by default and cannot be disabled by users. Auto-upgrade ensures that the Management Agent software is always up to date and secure.

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.

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.

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.

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.

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.

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.

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.

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 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.

• 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.

Two items that describe the capabilities of the OCI Database Management Service are:

• Perform management tasks across a group of databases. Database Management Service provides a feature called Database Fleet Management that allows you to perform management tasks across a group of databases in yourtenancy. You can use Database Fleet Management to view and compare the configuration, performance, and security of your databases. You can also use Database Fleet Management to execute SQL commands or scripts on multiple databases at once.
• Monitor database performance. Database Management Service also provides various tools and dashboards that let you 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.

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.

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.

To ensure continuous monitoring of both on-premises VMs and OCI compute instances, you need to configure OCI Compute agent on both sources to collect the required resource metrics. The OCI Compute agent is a lightweight process that monitors the host and the processes running on the host. You can use OCI Events service to track the end-to-end deployment process (com.oraclecloud.computeapi.launchinstance.end) and creation of new buckets (com.oraclecloud.objectstorage.createbucket) in your target environment. You can use OCI Notifications and Events services to notify these changes via email or other supported protocols.

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.

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

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.