Oracle Cloud Infrastructure 2024 Observability Professional Practice Tests and PDFs

Option 1: Correct: Oracle Cloud Infrastructure Monitoring provides real-time visibility and monitoring of your cloud resources and applications. It allows you to create alarms and notifications based on defined thresholds and metrics, and also supports custom metrics for in-depth monitoring. Option 2: Incorrect: Oracle Cloud Infrastructure Logging is a service that enables you to collect, search, and analyze log files generated by your resources and services. While logging is important for observability, it does not provide the real-time visibility and monitoring capabilities offered by Oracle Cloud Infrastructure Monitoring. Option 3: Incorrect: Oracle Cloud Infrastructure Health Checks is a feature that performs periodic checks on your resources to ensure they are functioning properly. While health checks are an important aspect of monitoring, they do not provide real-time visibility and monitoring of your cloud resources and applications like Oracle Cloud Infrastructure Monitoring does. Option 4: Incorrect: Oracle Cloud Infrastructure Events is a service that allows you to track and react to changes in your cloud resources through event-driven workflows. While events are an important aspect of observability, they do not provide the real-time visibility and monitoring capabilities offered by Oracle Cloud Infrastructure Monitoring.

Option 1: This option is incorrect because data in log groups can be deleted or modified as per the retention policy. Option 2: This option is incorrect because log retention policies can be defined at the log group level. Option 3: This option is correct. By default, data that is older than the retention period will be automatically deleted. However, log data that is analyzed in solutions such as Oracle Log Analytics will not be deleted, even if it exceeds the retention period set for the log group. Option 4: This option is incorrect because log retention can be easily configured in Oracle Cloud Infrastructure Logging to help you meet your retention requirements.

Option 1: While defining custom log parsers can help analyze log data in OCI Logging Analytics, a query language is specifically designed for ad-hoc log analysis. Option 2: Correct. The query language allowed by OCI Logging Analytics enables users to perform ad-hoc analysis on log data. Option 3: While custom dashboards can display OCI Logging Analytics data, they cannot be created using the query language provided by Logging Analytics. Option 4: While Log sources in OCI Logging Analytics can be defined, they are not managed using the query language provided.

Option 1: Incorrect. A trace span represents a unit of work performed by a service in response to a request, not a message sent from one service to another over a network. Option 2: Correct. In OCI Distributed Tracing, a trace span is a unit of work performed by a service in response to a request. Each trace span captures timing data and metadata related to a specific operation. Option 3: Incorrect. A trace span is not a collection of trace spans that are related to each other. It is a single span that represents a specific operation. Option 4: Incorrect. A trace span is not a measurement of the elapsed time between two trace spans. It is a unit of work performed by a service.

Option 1: Correct. Custom Metrics in Oracle Cloud Infrastructure Monitoring are used to monitor the state of resources within your tenancy. They allow you to collect and analyze metrics that are specific to your application or use case. Option 2: Incorrect. Custom Metrics in Oracle Cloud Infrastructure Monitoring are not pre-defined metrics provided by Oracle. They are metrics that you define

Option 1: This is incorrect. Metric filters are used in OCI Logging to identify and extract metrics data from log entries. Option 2: This is correct. Metric filters are used in OCI Monitoring to extract and transform data from a metric stream based on certain patterns or conditions in order to create custom metrics or alarms. Option 3: This is incorrect. OCI Alarms do not use metric filters to define thresholds, they use alarm rules and actions. Option 4: This is incorrect. While grouping similar metrics together is a feature in OCI Monitoring, metric filters are not used for this purpose.

Option 1: This option is incorrect because OCI Notifications for alert rules with multiple occurrences within a specified timeframe are not limited to the first occurrence. All instances within the specified time frame will trigger an OCI Notification. Option 2: This option is incorrect because the behavior of OCI Notifications for alert rules with multiple occurrences within a specified timeframe is to group all instances of the violation event that occurred within the time frame into a single Notification message. Sending a separate Notification message for each instance would result in potentially large numbers of Notifications, making the feature inefficient. Option 3: This option is the correct answer. When a violation event occurs within the specified time frame and an OCI Notification is sent, the service starts a new time window. Any subsequent instances of the violation event that occur within the new time window will trigger another OCI Notification. This process will repeat until there are no more occurrences of the violation event or the rule evaluation window ends. Option 4: This option is incorrect because OCI Notifications can be used with any alert rules, including those with multiple occurrences within a specified timeframe. This is a valuable feature that allows the user to be notified only once for a series of similar events and avoid notification floods.