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The B Series VM Looks Good on Paper, But...

By Rob Waggoner

I talk to a number of customers that see the pricing of the Azure B series VMs and immediately want to leverage them in their MyCloudIT deployments to save on cost. I agree that the pricing on the B series VMs is compelling but let’s peel back a few layers and understand what the B series “is” and “isn’t” so you can make the right decision for your business. What makes the B series VMs look good on paper? The price of course. When we compare the price of a B2MS VM with 2 vCPUs and 8 GB RAM to a D2_v3 VM, which also has 2 vCPUs and 8 GM RAM, the B2MS is almost half the cost of the D2_v3. Both VMs have the same amount of vCPU’s and RAM, so what’s the difference?  

Check out this chart comparing the prices of the B series VMs and the comparable Dv3 VMs. My suggestion is to not resize your RDSGW or your RDSMGMT servers to the B series VMs.  

VM size 

733 hrs 

B2MS 2 vCPU, 8 GB RAM 

$78.84 

B4MS 4 vCPU, 16 GB RAM 

$157.68 

B8MS 8 vCPU, 32 GB RAM 

$314.63 

 

VM size 

733 hrs 

D2_v3 2 vCPU, 8 GB RAM 

$154.03 

D4_v3 4 vCPU, 16 GB RAM 

$308.06 

D8_v3 8 vCPU, 32 GB RAM 

$616.85 

                                                          Pricing in S. Central US 8/20/2019 

The B Series VMs are “Burstable”, which means you do not get the full vCPU capability 100% of the time. I agree that the B series VMs are very compelling when you consider that most workloads do not saturate your vCPUs all the time, but there is more than price and vCPU performance that needs to be considered. This Microsoft Azure article on B series VMs provides a good breakdown on the typical CPU performance you can expect to receive as well as the storage IOPS performance. These are important numbers because if you slow down the disk IO, you slow down everything.  

The other item that this chart does not call out is the Network bandwidth available to the B series VM. When you review the Dv3 series VMs here, you can see that Network Bandwidth is called out, but again it was not called out for the B series VMs. In an RDS environment, vCPU performance, disk IO, and Network Bandwidth all need to be considered since the RDSMGMT Server and the RDSGW server both require consistent disk IO and network bandwidth. In my opinion, I would not recommend the B series VMs for the RDSGW server, or the RDSMGMT server. The D2_v3, in my opinion, is the most consistent VM size for the RDSGW and RDSMGMT servers. And if you need help resizing your deployments to the new D_v3 sizes, make sure to check out my recent blog on how to resize your deployments.

Notice that I did not call out the RDS Session Host servers. Honestly, you may be able to leverage the B series VMs for your session host servers, if they provide enough consistent vCPU performance to satisfy your users. Let’s consider the B8MS VM size, it is almost half the cost of the D8_v3 and provides a base performance of 135% of the vCPU capacity. If your typical users are not CPU hungry, maybe they have typical office user type demands, then the B series VMs may be worth evaluating. But please evaluate them over a number of days since the B8MS, for example, comes with 3 hours of burstable capacity to start with, so the first day may feel normal but the second day may be more CPU starved.  

If you would describe your user base as power users, I doubt the B series will satisfy their demands, but if you describe your users as typical office users, the B series may be worth considering. If you feel you have a mix of power users and typical office users, you could deploy two separate RDS Collections, one for your power users and the second for your office users, thus you could adjust the VM sizes as well as the load balancing and auto-scaling to meet the needs of both categories of users. Bottom line, you can always resize your session host VMs to the B series to see if the users see a difference, but remember that the B series VMs will not provide an overall consistent user experience 24x7. 


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Tags: MyCloudIT Best Practices, Best Practices

azure cost optimization

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