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Fachleute, die in SPLK-4001 zertifiziert sind, können ein solides Verständnis f¨¹r die Überwachung und Fehlerbehebung von Cloud-Umgebungen mit Splunk erwarten. Sie können die leistungsstarken Funktionen von Splunk nutzen, um Metrikendaten effizient zu sammeln, zu analysieren und zu visualisieren. Die Zertifizierung kann Einzelpersonen helfen, sich auf dem wettbewerbsfähigen Arbeitsmarkt abzuheben und ihr Verdienstpotential zu erhöhen. Insgesamt ist die SPLK-4001-Pr¨¹fung eine wertvolle Zertifizierung f¨¹r Fachkräfte, die ihre Fähigkeiten in Bezug auf Beobachtbarkeit verbessern und mit einer der f¨¹hrenden Plattformen der Branche zusammenarbeiten möchten.
Splunk SPLK-4001 Quiz - SPLK-4001 Studienanleitung & SPLK-4001 TrainingsmaterialienWenn Sie sich noch anstrengend um die Splunk SPLK-4001 Zertifizierungspr¨¹fung bem¨¹hen, dann haben Sie einen großen Fehler gemacht. Durch fleißiges Lernen können Sie sicher die Pr¨¹fung bestehen. Aber Sie können vielleicht das erwartete Ziel vielleicht nicht erreichen. Im Zeitalter des Internets gibt es zahlreiche erfolgreiche IT-Zertifizierungen. Die Schulungsunterlagen zur Splunk SPLK-4001 Zertifizierungspr¨¹fung von ExamFragen sind sehr gut. Sie sind zielgerichtet und verprechen Ihnen, die Splunk SPLK-4001 Pr¨¹fung 100% zu bestehen. Diese Schulungsunterlagen sind nicht nur rational, sondern können viel Zeit ersparen. Sie können mit der ersparten Zeit etwas anderes lernen. So können Sie bessere Resultate bei weniger Einsatz erzielen. Splunk O11y Cloud Certified Metrics User SPLK-4001 Pr¨¹fungsfragen mit Lösungen (Q35-Q40):35. Frage
One server in a customer's data center is regularly restarting due to power supply issues. What type of dashboard could be used to view charts and create detectors for this server?
A. Multiple-service dashboard
B. Single-instance dashboard
C. Server dashboard
D. Machine dashboard
Antwort: B
Begr¨¹ndung:
According to the Splunk O11y Cloud Certified Metrics User Track document1, a single-instance dashboard is a type of dashboard that displays charts and information for a single instance of a service or host. You can use a single-instance dashboard to monitor the performance and health of a specific server, such as the one that is restarting due to power supply issues. You can also create detectors for the metrics that are relevant to the server, such as CPU usage, memory usage, disk usage, and uptime. Therefore, option A is correct.
36. Frage
An SRE creates an event feed chart in a dashboard that shows a list of events that meet criteria they specify. Which of the following should they include? (select all that apply)
A. Custom events that have been sent in from an external source.
B. Events created when a detector clears an alert.
C. Events created when a detector triggers an alert.
D. Random alerts from active detectors.
Antwort: A,B,C
Begr¨¹ndung:
According to the web search results1, an event feed chart is a type of chart that shows a list of events that meet criteria you specify. An event feed chart can display one or more event types depending on how you specify the criteria. The event types that you can include in an event feed chart are:
Custom events that have been sent in from an external source: These are events that you have created or received from a third-party service or tool, such as AWS CloudWatch, GitHub, Jenkins, or PagerDuty. You can send custom events to Splunk Observability Cloud using the API or the Event Ingest Service.
Events created when a detector triggers or clears an alert: These are events that are automatically generated by Splunk Observability Cloud when a detector evaluates a metric or dimension and finds that it meets the alert condition or returns to normal. You can create detectors to monitor and alert on various metrics and dimensions using the UI or the API.
Therefore, option A, B, and D are correct.
37. Frage
Which of the following are supported rollup functions in Splunk Observability Cloud?
A. sigma, epsilon, pi, omega, beta, tau
B. std_dev, mean, median, mode, min, max
C. average, latest, lag, min, max, sum, rate
D. 1min, 5min, 10min, 15min, 30min
Antwort: C
Begr¨¹ndung:
Explanation
According to the Splunk O11y Cloud Certified Metrics User Track document1, Observability Cloud has the following rollup functions: Sum: (default for counter metrics): Returns the sum of all data points in the MTS reporting interval. Average (default for gauge metrics): Returns the average value of all data points in the MTS reporting interval. Min: Returns the minimum data point value seen in the MTS reporting interval. Max:
Returns the maximum data point value seen in the MTS reporting interval. Latest: Returns the most recent data point value seen in the MTS reporting interval. Lag: Returns the difference between the most recent and the previous data point values seen in the MTS reporting interval. Rate: Returns the rate of change of data points in the MTS reporting interval. Therefore, option A is correct.
38. Frage
Changes to which type of metadata result in a new metric time series?
A. Properties
B. Sources
C. Tags
D. Dimensions
Antwort: D
Begr¨¹ndung:
The correct answer is A. Dimensions.
Dimensions are metadata in the form of key-value pairs that are sent along with the metrics at the time of ingest. They provide additional information about the metric, such as the name of the host that sent the metric, or the location of the server. Along with the metric name, they uniquely identify a metric time series (MTS)1 Changes to dimensions result in a new MTS, because they create a different combination of metric name and dimensions. For example, if you change the hostname dimension from host1 to host2, you will create a new MTS for the same metric name1 Properties, sources, and tags are other types of metadata that can be applied to existing MTSes after ingest. They do not contribute to uniquely identify an MTS, and they do not create a new MTS when changed2 To learn more about how to use metadata in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observab ... ics.html#Dimensions 2: https://docs.splunk.com/Observab ... dimensions-mts.html
39. Frage
A customer deals with a holiday rush of traffic during November each year, but does not want to be flooded with alerts when this happens. The increase in traffic is expected and consistent each year. Which detector condition should be used when creating a detector for this data?
A. Outlier Detection
B. Calendar Window
C. Historical Anomaly
D. Static Threshold
Antwort: C
Begr¨¹ndung:
historical anomaly is a detector condition that allows you to trigger an alert when a signal deviates from its historical pattern1. Historical anomaly uses machine learning to learn the normal behavior of a signal based on its past data, and then compares the current value of the signal with the expected value based on the learned pattern1. You can use historical anomaly to detect unusual changes in a signal that are not explained by seasonality, trends, or cycles1.
Historical anomaly is suitable for creating a detector for the customer's data, because it can account for the expected and consistent increase in traffic during November each year. Historical anomaly can learn that the traffic pattern has a seasonal component that peaks in November, and then adjust the expected value of the traffic accordingly1. This way, historical anomaly can avoid triggering alerts when the traffic increases in November, as this is not an anomaly, but rather a normal variation. However, historical anomaly can still trigger alerts when the traffic deviates from the historical pattern in other ways, such as if it drops significantly or spikes unexpectedly1.
40. Frage
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