Nutanix has updated most of their appliances to G6 hardware using Intel Skylake processor family. Previous G5 Nutanix appliances were using Intel Broadwell processor family. This has caused some confusion when it comes to processor performance, the newer processors typically run at lower clock speed, so quick conclusion would be that the newer processor would be slower.
One of the improvements that came along with Nutanix AOS 5.5 was IO path optimization feature called “AHV Turbo”.
While the marketing department at Nutanix might have fallen asleep and woken up in 1990s with god-awful name like this, it is actually a GOOD feature. Every time I hear word “Turbo” in IT related matters, it just reminds me of my first ever PC, a 286 with a “Turbo” button, which supposedly boosted performance by increasing frequency from 8 Mhz to 12 Mhz, but did actually do diddly-squat 🙂
There is a famous quote by Mark Twain “The reports of my death have been greatly exaggerated”, and despite claims made by All Flash disk array manufactures, this quote still holds true for 10 k SAS drives when comparing only cost per gigabyte. SSD drives have been and are still more costly per gigabyte than their spinning ancestors 10k SAS drives.
This is the second part of this series, the first part can be found from here.
- Starting point is very similar as with Scale Up sizing exercise
- Collect some performance data from existing system in order to estimate growth rate
- Select over how many years solutions should be amortized
- Typically three to five years
- With Scale Out you don’t initially size / buy solution for the whole three to five years, but it is good to know your upper limit, especially if there are limits in Scale Out cluster size
- Based on collected data, plot required scaling over years
- You might also want to plot different scenarios at different growth rates
In this two part series I will study different ways to scale resources in data centers and how chosen model impacts costs.
In Virtualized Data Centers performance is one of the most common factors limiting scaling.
Compute layer has a Scale Out model for performance:
- If you need more compute power just add servers to a shared resource pool
- Balance load by live migrating VMs to new servers
- Keep using one management point
- No additional silos
- Nearly linear scaling
- Problem solved