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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?
Suggested Answer: C
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The correct answer is C. Timeshift.
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.
35 comments · newest first
VE
Veta
10 months ago
Standard deviation? That seems off for this scenario.
IZ
Izetta
10 months ago
I think Sum transformation could work too, but not sure.
DO
Dorthy
10 months ago
Tlmeshift is the right choice here, no doubt!
GA
Gary
10 months ago
Wait, are we really sure about Tlmeshift? Sounds a bit sketchy.
RE
Renay
11 months ago
Definitely need the Rate function for that!
MI
Mitsue
11 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.
LO
Lorenza
11 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.
UL
Ula
11 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?
CH
Chauncey
12 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.
TH
Thaddeus
12 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.
AL
Alyce
12 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.
CE
Cecilia
1 year 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.
RA
Raymon
1 year 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.
DE
Deandrea
2 years 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?
SH
Shasta
2 years 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!
CA
Carlee
1 year ago
Actually, I agree with the user comment, it's C) Timeshift, we need to analyze how utilization has changed over time.
CA
Carlton
1 year ago
No, I believe it's D) Standard deviation, we need to measure the variability in server utilization.
CR
Cristy
2 years ago
I think the answer is A) Rate, we need to calculate the rate of change in server utilization.
KA
Kathryn
2 years ago
I think D) Standard deviation could also be useful in this scenario.
CA
Carry
2 years ago
But Tlmeshift can help identify the servers with the most increased utilization.
AU
Audry
2 years 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.
GE
Georgeanna
2 years ago
D) Standard deviation could show us which servers have had the most variability in utilization, indicating potential changes.
FL
Florencia
2 years ago
C) Tlmeshift could help us compare server utilization at different points in time to see which ones have increased the most.
MA
Marnie
2 years ago
A) Rate would be more useful for identifying the servers with the most significant increase in utilization over time.
KR
Kristel
2 years ago
I disagree, I believe it's A) Rate.
CA
Carry
2 years ago
I think the answer is C) Tlmeshift.
JA
Jacqueline
2 years ago
Ah, A) Rate is the one that'll show us the growth, like a server on steroids! Gotta love that exponential curve.
TA
Tandra
2 years ago
Yeah, but D) Standard deviation could help us identify any outliers in server utilization that we need to look into.
SH
Shenika
2 years ago
I think C) Tlmeshift might also be useful to see how the servers have shifted in terms of utilization.
JE
Jesus
2 years ago
I agree, A) Rate will show us the servers that are really pumping up their utilization.
VE
Verlene
2 years ago
A) Rate is definitely the way to go. It'll give us that exponential growth curve we're looking for.
CO
Corinne
2 years ago
D) Standard deviation, baby! Gonna find out which servers are really going wild with their utilization.
KA
Kate
2 years ago
Hmm, I'd say C) Timeshift is the way to go. Gotta track those changes over time, am I right?
MA
Margot
2 years ago
Yeah, I agree. Timeshift is essential for identifying trends in server utilization.
GE
Genevive
2 years ago
I think C) Timeshift is a good choice. It helps track changes over time.