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Splunk SPLK-4001 (Splunk O11y Cloud Certified Metrics User) Certification Exam is a highly sought after certification for IT professionals who work with Splunk software. Splunk is a leading provider of operational intelligence software that allows organizations to monitor, analyze, and visualize machine data in real-time. The SPLK-4001 certification exam is designed to test the knowledge and skills of IT professionals in using Splunk software to monitor and analyze metrics in a cloud environment.
Achieving the Splunk SPLK-4001 certification can be a valuable asset for IT professionals, demonstrating their knowledge and expertise in using Splunk for cloud monitoring and analysis. Splunk O11y Cloud Certified Metrics User certification can help you stand out in a competitive job market and can be a valuable addition to your resume or LinkedIn profile.
Splunk SPLK-4001 (Splunk O11y Cloud Certified Metrics User) Certification Exam is a comprehensive certification exam that focuses on validating the skills and knowledge of candidates in using Splunk to collect, analyze, and monitor metrics data in a cloud environment. Splunk O11y Cloud Certified Metrics User certification exam is designed for IT professionals who work with Splunk in a cloud environment and who are responsible for managing and monitoring metrics data to ensure the optimal performance of their organization's IT infrastructure.
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Which component of the OpenTelemetry Collector allows for the modification of metadata?
A. Processors
B. Receivers
C. Pipelines
D. Exporters
Answer: A
Explanation:
Explanation
The component of the OpenTelemetry Collector that allows for the modification of metadata is A. Processors.
Processors are components that can modify the telemetry data before sending it to exporters or other components. Processors can perform various transformations on metrics, traces, and logs, such as filtering, adding, deleting, or updating attributes, labels, or resources. Processors can also enrich the telemetry data with additional metadata from various sources, such as Kubernetes, environment variables, or system information1 For example, one of the processors that can modify metadata is the attributes processor. This processor can update, insert, delete, or replace existing attributes on metrics or traces. Attributes are key-value pairs that provide additional information about the telemetry data, such as the service name, the host name, or the span kind2 Another example is the resource processor. This processor can modify resource attributes on metrics or traces.
Resource attributes are key-value pairs that describe the entity that produced the telemetry data, such as the cloud provider, the region, or the instance type3 To learn more about how to use processors in the OpenTelemetry Collector, you can refer to this documentation1.
1: https://opentelemetry.io/docs/collector/configuration/#processors 2: https://github.com/open-telemetr ... attributesprocessor 3: https://github.com/open-telemetr ... r/resourceprocessor
NEW QUESTION # 43
Which of the following statements are true about local data links? (select all that apply)
A. Local data links can only have a Splunk Observability Cloud internal destination.
B. Local data links are available on only one dashboard.
C. Only Splunk Observability Cloud administrators can create local links.
D. Anyone with write permission for a dashboard can add local data links that appear on that dashboard.
Answer: B,D
Explanation:
The correct answers are A and D.
According to the Get started with Splunk Observability Cloud document1, one of the topics that is covered in the Getting Data into Splunk Observability Cloud course is global and local data links. Data links are shortcuts that provide convenient access to related resources, such as Splunk Observability Cloud dashboards, Splunk Cloud Platform and Splunk Enterprise, custom URLs, and Kibana logs.
The document explains that there are two types of data links: global and local. Global data links are available on all dashboards and charts, while local data links are available on only one dashboard. The document also provides the following information about local data links:
Anyone with write permission for a dashboard can add local data links that appear on that dashboard.
Local data links can have either a Splunk Observability Cloud internal destination or an external destination, such as a custom URL or a Kibana log.
Only Splunk Observability Cloud administrators can delete local data links.
Therefore, based on this document, we can conclude that A and D are true statements about local data links. B and C are false statements because:
B is false because local data links can have an external destination as well as an internal one.
C is false because anyone with write permission for a dashboard can create local data links, not just administrators.
NEW QUESTION # 44
With exceptions for transformations or timeshifts, at what resolution do detectors operate?
A. The resolution of the chart
B. Native resolution
C. The resolution of the dashboard
D. 10 seconds
Answer: B
Explanation:
According to the Splunk Observability Cloud documentation1, detectors operate at the native resolution of the metric or dimension that they monitor, with some exceptions for transformations or timeshifts. The native resolution is the frequency at which the data points are reported by the source. For example, if a metric is reported every 10 seconds, the detector will evaluate the metric every 10 seconds. The native resolution ensures that the detector uses the most granular and accurate data available for alerting.
NEW QUESTION # 45
For which types of charts can individual plot visualization be set?
A. Line, Bar, Column
B. Line, Area, Column
C. Bar, Area, Column
D. Histogram, Line, Column
Answer: B
Explanation:
Explanation
The correct answer is C. Line, Area, Column.
For line, area, and column charts, you can set the individual plot visualization to change the appearance of each plot in the chart. For example, you can change the color, shape, size, or style of the lines, areas, or columns. You can also change the rollup function, data resolution, or y-axis scale for each plot1 To set the individual plot visualization for line, area, and column charts, you need to select the chart from the Metric Finder, then click on Plot Chart Options and choose Individual Plot Visualization from the list of options. You can then customize each plot according to your preferences2 To learn more about how to use individual plot visualization in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observab ... -plot-visualization 2: https://docs.splunk.com/Observab ... -plot-visualization
NEW QUESTION # 46
A customer operates a caching web proxy. They want to calculate the cache hit rate for their service. What is the best way to achieve this?
A. Chart Options and metadata
B. Timeshift and Top N
C. Percentages and ratios
D. Timeshift and Bottom N
Answer: C
Explanation:
According to the Splunk O11y Cloud Certified Metrics User Track document1, percentages and ratios are useful for calculating the proportion of one metric to another, such as cache hits to cache misses, or successful requests to failed requests. You can use the percentage() or ratio() functions in SignalFlow to compute these values and display them in charts. For example, to calculate the cache hit rate for a service, you can use the following SignalFlow code:
percentage(counters("cache.hits"), counters("cache.misses"))
This will return the percentage of cache hits out of the total number of cache attempts. You can also use the ratio() function to get the same result, but as a decimal value instead of a percentage.
ratio(counters("cache.hits"), counters("cache.misses"))
NEW QUESTION # 47
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