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Splunk SPLK-4001 Exam - Topic 10 Question 39 Discussion

Actual exam question for Splunk's SPLK-4001 exam
Question #: 39
Topic #: 10
[All SPLK-4001 Questions]

A customer has a large population of servers. They want to identify the servers where utilization has increased the most since last week. Which analytics function is needed to achieve this?

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Suggested Answer: C

The correct answer is C. Timeshift.

According to the Splunk Observability Cloud documentation1, timeshift is an analytic function that allows you to compare the current value of a metric with its value at a previous time interval, such as an hour ago or a week ago. You can use the timeshift function to measure the change in a metric over time and identify trends, anomalies, or patterns. For example, to identify the servers where utilization has increased the most since last week, you can use the following SignalFlow code:

timeshift(1w, counters(''server.utilization''))

This will return the value of the server.utilization counter metric for each server one week ago. You can then subtract this value from the current value of the same metric to get the difference in utilization. You can also use a chart to visualize the results and sort them by the highest difference in utilization.


by Antonio at Mar 06, 2025, 03:19 AM

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Veta
2 months ago
Standard deviation? That seems off for this scenario.
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Izetta
2 months ago
I think Sum transformation could work too, but not sure.
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Dorthy
3 months ago
Tlmeshift is the right choice here, no doubt!
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Gary
3 months ago
Wait, are we really sure about Tlmeshift? Sounds a bit sketchy.
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Renay
3 months ago
Definitely need the Rate function for that!
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Mitsue
3 months ago
Standard deviation seems like it would help identify outliers, but I don’t think it directly answers the question about increased utilization. So I’m leaning away from option D.
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Lorenza
4 months ago
I’m a bit confused. I thought tlmeshift was related to time series data, but I’m not sure if it fits this scenario. It sounds familiar though.
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Ula
4 months ago
I remember practicing a question about analyzing server performance, and I think we used something like a sum transformation to aggregate data. Could that be option B?
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Chauncey
4 months ago
I think we might need to look at the rate of change in utilization, so maybe option A? But I'm not entirely sure how that applies to servers specifically.
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Thaddeus
4 months ago
I'm a little confused on this one. I'm not sure if "Rate" is the right function, or if maybe "Standard deviation" would work better to identify the outliers with the biggest changes. I'll have to think it through a bit more.
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Alyce
4 months ago
Okay, I've got an idea. Since we're looking for the servers with the biggest increase in utilization, the "Rate" function seems like the way to go. That should give us the rate of change, which will highlight the servers with the largest utilization increases.
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Cecilia
5 months ago
Hmm, I'm a bit unsure about this one. I'm trying to think through the different analytics functions and which one would be best for finding the servers with the largest utilization increase. Let me re-read the question carefully.
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Raymon
5 months ago
This seems like a pretty straightforward question. I think the "Rate" function is what we need to identify the servers with the biggest utilization increase.
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Deandrea
11 months ago
D) Standard deviation, all the way! Gotta find out which servers are really breaking the mold and going off the charts. Maybe they're secretly mining crypto on the side, who knows?
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Shasta
11 months ago
Whoa, hold up, is this a trick question? The answer's clearly C) Timeshift - we need to see how things have shifted over time, not just the current snapshot. Duh!
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Carlee
10 months ago
Actually, I agree with the user comment, it's C) Timeshift, we need to analyze how utilization has changed over time.
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Carlton
10 months ago
No, I believe it's D) Standard deviation, we need to measure the variability in server utilization.
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Cristy
11 months ago
I think the answer is A) Rate, we need to calculate the rate of change in server utilization.
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Kathryn
11 months ago
I think D) Standard deviation could also be useful in this scenario.
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Carry
11 months ago
But Tlmeshift can help identify the servers with the most increased utilization.
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Audry
11 months ago
B) Sum transformation? Sounds like we're adding up server usage, but how's that gonna help us find the biggest changes? Weird choice.
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Georgeanna
11 months ago
D) Standard deviation could show us which servers have had the most variability in utilization, indicating potential changes.
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Florencia
11 months ago
C) Tlmeshift could help us compare server utilization at different points in time to see which ones have increased the most.
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Marnie
11 months ago
A) Rate would be more useful for identifying the servers with the most significant increase in utilization over time.
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Kristel
11 months ago
I disagree, I believe it's A) Rate.
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Carry
12 months ago
I think the answer is C) Tlmeshift.
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Jacqueline
12 months ago
Ah, A) Rate is the one that'll show us the growth, like a server on steroids! Gotta love that exponential curve.
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Tandra
11 months ago
Yeah, but D) Standard deviation could help us identify any outliers in server utilization that we need to look into.
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Shenika
11 months ago
I think C) Tlmeshift might also be useful to see how the servers have shifted in terms of utilization.
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Jesus
11 months ago
I agree, A) Rate will show us the servers that are really pumping up their utilization.
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Verlene
11 months ago
A) Rate is definitely the way to go. It'll give us that exponential growth curve we're looking for.
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Corinne
12 months ago
D) Standard deviation, baby! Gonna find out which servers are really going wild with their utilization.
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Kate
12 months ago
Hmm, I'd say C) Timeshift is the way to go. Gotta track those changes over time, am I right?
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Margot
11 months ago
Yeah, I agree. Timeshift is essential for identifying trends in server utilization.
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Genevive
11 months ago
I think C) Timeshift is a good choice. It helps track changes over time.
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