IOPS, Throughput & Latency Explained
Вставка
- Опубліковано 30 чер 2024
- A look at IOPS, throughput and latency and what they are and when we may care.
This week's bag of Microsoft Azure updates and new features.
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▬▬▬▬▬▬ C H A P T E R S ⏰ ▬▬▬▬▬▬
0:00 - Introduction
0:47 - Capacity
1:54 - IOPS
3:32 - Throughput
6:45 - Latency
11:20 - Summary and close
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⚠ P L E A S E N O T E ⚠
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excellent analogy and that formula is more valuable than gold! Thank you..IRON MAN!
What a simple and clear analogy! Thank you.
Had to watch the first few minutes twice because I was laughing too hard at that t-shirt lmao. Excellent video John!
Great analogy! - Wish this sort of example was given in the the Official Azure Docs!
Very much needed explanation, John! Thanks as always.
Another beautifully simple explanation. Thanks once again John and well done.
I just realized this was published less than 24 hours ago. How timely!
Thank you! It was easy to understand. Very insightful!
Thanks John, love the t shirt!! Bless you for all all your efforts!
You are rocking as always..!!
What an analogy and way of explanation..!!
A great analogy and very clear explanation of the concepts.
It's probably worth mentioning that devices usually have different IOPS depending on the block size (size operation).
The lower the size operation, the higher the IOPS, but it's not linear.
The throughput is still better for high block/operation sizes, despite IOPS dropping.
Keep in mind that throughput is not always the limiting factor, though.
Excellent tutorial! Incredibly clear and to the point.
Best explanation on UA-cam. Huge Congrats!
John has mastered that art of explaining complex topics with simple examples...thats his strength...those biceps are just a facade 😉
Lol
Very Helpful, as always - Thank you John!!
Paul Nielsen used to think of IOPS as how many birds can co currently peck on or drink from the fountain (random I/o) as opposed to throughput which is most likely realized from large data warehouse sequential reads......which is how many big concurrent gulps can be taken from the fountain .
Fantastic analogy! Very clear explanation
hi John, I really liked your videos and this one is awesome, kudos to you.
Awesome explanation.. loved content presentation
Lovely analogy! Thanks
Awesome explanation. Thanks for sharing.. Really loved all your content😀
I am in South Africa and I love your explanation my Guy
Thanks!
Excellent explanation, thank you
Great as always. Thank you.
Wonderful explanations.
Great explanation and analogy 👍🏻
Fantastic, once more!
Awesome content! Very much needed! BTW, no the most cumbersome whiteboard ever ... 😀😊
Unique way of explanation
simple explanation, thankyou sir
Thank you
Thanks a ton
This video is only 720p, contrary to all your other videos. Just something I noticed :)
Otherwise, great explanation - you're very talented in explaining things in a simple way.
Opps, messed up the render settings from something I was playing around with. oh well :D
Excellent video but more importantly well done on those arms dude. They're like tree trunks with hands on the end.
LOL
Samsung Magician software benchmark just showed my 970 evo 250gb go from 168457 IOPS Random Read down to 24902 simply by changing from a B450 board that was running at Gen2 4x to a x570 board that is full Gen4 4x capable. My random writes went from 295166 IOPS to 125976 IOPS on x570. The only results that improved is the sequential read doubled from 1620mb to 3218mb. Any reason why a faster x570 running the drive at full Gen3 speeds shows much much lower IOPS then it did on a B450 board but running at Gen2 connection on PCIe 2nd slot?
Sequential Reads doubled but Random Read/Writes dropped easily 2x on write and 6x on read. What am I missing here. Thought full speed x570 board would help my NVMe speeds not hurt it. All else is exactly the same just a motherboard swap today.
Does anybody know why IOPS depend on volume size? I'm not sure about Azure, but AWS and Oracle both offer block storage IOPS that scale with volume size, that is a 10 GB volume has twice IOPS of a 5GB volume
Because you are taking a slice of underlying resource which itself has iops and throughout capabilities. The bigger slice you take (capacity) the bigger the slice of the other attributes like iops and throughout you get. Scale linearly typically.
For a second i could've sware i saw Tom Cruise givinging awesome lessons about storage. Why you stole that from me?😭
ROFL