Splunk SPLK-4001 Exam - Topic 10 Question 39 Discussion

Actual exam question for Splunk's SPLK-4001 exam

Question #: 39
Topic #: 10

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?

ARate

BSum transformation

CTlmeshift

DStandard deviation

Show Suggested Answer

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

4 months ago

Standard deviation? That seems off for this scenario.

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Izetta

4 months ago

I think Sum transformation could work too, but not sure.

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Dorthy

4 months ago

Tlmeshift is the right choice here, no doubt!

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Gary

4 months ago

Wait, are we really sure about Tlmeshift? Sounds a bit sketchy.

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Renay

5 months ago

Definitely need the Rate function for that!

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Mitsue

5 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

5 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

5 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

5 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

6 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

6 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

6 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

6 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

1 year 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

1 year 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

11 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

12 months ago

No, I believe it's D) Standard deviation, we need to measure the variability in server utilization.

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Cristy

1 year ago

I think the answer is A) Rate, we need to calculate the rate of change in server utilization.

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Kathryn

1 year ago

I think D) Standard deviation could also be useful in this scenario.

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Carry

1 year ago

But Tlmeshift can help identify the servers with the most increased utilization.

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Audry

1 year 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

1 year ago

D) Standard deviation could show us which servers have had the most variability in utilization, indicating potential changes.

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Florencia

1 year 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

1 year 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

1 year ago

I disagree, I believe it's A) Rate.

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Carry

1 year ago

I think the answer is C) Tlmeshift.

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Jacqueline

1 year 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

1 year 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

1 year 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

1 year ago

I agree, A) Rate will show us the servers that are really pumping up their utilization.

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Verlene

1 year 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

1 year ago

D) Standard deviation, baby! Gonna find out which servers are really going wild with their utilization.

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Kate

1 year 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

1 year ago

Yeah, I agree. Timeshift is essential for identifying trends in server utilization.

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Genevive

1 year ago

I think C) Timeshift is a good choice. It helps track changes over time.

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