CVM (Cores, Memory, HDD, SSD)

CVM Cores

Sizer will first compute the number of cores needed for the workloads.  The sum of all the workload cores is called TotalCores in this equation.

Each workload type  has its own number of cores

  • NumVDICores
  • NumDBCores (SQL Server)
  • NumServVirtCores
  • NumRawCores.   Note: coreCVMOverhead is a user input for RAW workload to set CVM Cores with default being 4 cores
  • NumServerComputingCores
  • NumSplunkCores
  • NumXenAppCores
  • NumFileServicesCores
  • Oracle cores is set to 6

What sizer then does is places a weighted average of CVM cores for these workloads with a range of 4 to 6 cores per node depending on workload mix

CVM  cores per node = (NumVDICores / TotalCores) * 4 + (NumDBCores / TotalCores) * 6 + (NumExchgCores / TotalCores) * 6   + (NumServVirtCores / TotalCores) * 4 + (NumRawCores / TotalCores) * coreCVMOverhead  + (NumServerComputingCores / TotalCores) * 4 + (NumSplunkCores / TotalCores) * 6 + (NumXenAppCores / TotalCores) * 4 + (NumFileServicesCores / TotalCores) * 4 + (number of Oracle cores/TotalCores) * 6;

For example, if only VDI is in a scenario than the NumVDICores / TotalCores ratio is 1 and then 4 cores are assigned for each node for CVM

The workload equations will come to a CVM core count per node for entire configuration that depends on the workload balance but is between 4 to 6 cores for CVM per node.

 

CVM Memory

 

CVM memory will vary by Platform type

 

 

Platform Default Memory (GB)
VDI, server virtualization 20
Storage only 28
Light Compute 28
Large server, high-performance, all-flash 32

 

Feature Addon CVM Memory

 

Sizer adds on the following amount of memory for features as noted below

 

 

Features Memory (GB)
Capacity tier deduplication (includes performance tier deduplication) 16
Redundancy factor 3 8
Performance tier deduplication 8
Cold-tier nodes + capacity tier deduplication 4
Capacity tier deduplication + redundancy factor 3 16
Self-service portal (AHV only)

 

  • With Asterix.1 no need to add memory beyond what is allocated for Platform CVM memory
 

Sizer approach to calculate CVM Memory

  • First determine Platform type CVM Memory from the tables.  As we do a sizing for a given model determine what type of model it is (it should be a table to allow updates) and assign appropriate CVM memory per node (20, 28, or 32 GB per node).
  •  Next we add memory for addons which can not go higher than 32 GB
    • Add CVM memory for extras.  Total CVM Memory = Min (Platform CVM Memory + Addon memory, 32)  where addon memory =
    • If RF3 = 8 GB
    • Dedupe only =  16GB
    • Both RF3 and Dedupe = 16 GB
    • No addons = 0GB
    • Compression  = 0 GB
  • If EPIC workload take MAX(32GB, result found in step 2).   Here should at least be 32 but may be more. If not EPIC go to step 4
  • Add memory for Hypervisor.  Looking at best practices for AHV, ESX and HyperV can assume 8GB needed for the hypervisor.  Though not a CVM memory requirement per-se it is a per node requirement and so good place to add it (versus a new line item in the Sizing details).
    • Total CVM Memory = Total CVM Memory + 8Gb

Examples.

  • Either manual or automatic sizing is sizing 3060-G5.  RF3 is turned on for one workload. User wants SSP. Not EPIC workload

CVM memory per node

·        Platform CVM Memory for 3060-G5 = 20GB

·        Add on feature  CVM requirement = 8 GB

·   ·        Hypervisor = 8 GB

CVM Memory per node = 28GB.  Will show 36GB with hypervisor

  •  Either manual or automatic sizing is sizing 1065-G5.  RF3 and Dedupe are OFF. Not EPIC workload

CVM memory per node

·        Platform CVM Memory for 3060-G5 = 20GB

·        Add on feature  CVM requirement = 0 GB

·        Hypervisor = 8 GB

CVM Memory per node = 20GB.  Will show 28GB with hypervisor

  • Either manual or automatic sizing is sizing 8035-G5.  Dedupe is turned on for one workload and want SSP. Not EPIC workload

CVM memory per node

·        Platform CVM Memory for 8035-G5 = 28GB

·        Add on feature  CVM requirement = 16 GB

·      ·        Hypervisor = 8 GB

CVM Memory per node = 32GB.  Though the addon requires 16GB we reached the maximum of 32 for the platform and addons together.  Will show 40GB with hypervisor

CVM HDD

Below is how the CVM HDD overhead is calculated.

Ext4 5% of all HDD in TiB
Genesis 5% of all HDD in TiB after Ext4 is discounted
Curator Max (2% * HDD in TiB, 60 GiB) for Curator 1st HDD
+
Max (2% * HDD in TiB, 20 GiB) for Curator for all remaining HDDs
Let us take an example and see how this calculation works
HDD Capacity per node in TB 32
Number of Nodes in Cluster 3
Cluster total HDD Capacity in TB 96
Cluster total HDD Capacity in TiB 87.31

The example assumes each node has 4 x 8TB HDDs

Capacity of 1st HDD in TB 8
Capacity of 1st HDD in TiB 7.28
Capacity of all remaining HDDs in TB 88
Capacity of all remaining HDDs in TiB 80.04

Let us take the above numbers in the example and derive the HDD CVM overhead

Ext4 5% of all HDD in TiB 4.37
Genesis 5% of all HDD in TiB after Ext4 is discounted 4.15
Curator Max (2% * HDD in TiB, 60 GiB) for Curator 1st HDD
+
Max (2% * HDD in TiB, 20 GiB) for Curator for all remaining HDDs
1.75
Total CVM Overhead   10.26

CVM SSD

CVM SSD per node:

Nutanix Home 60 GiB for first 2 SSDs.  Assuming all nodes have at least 2 SSDs.

 

  • If just one SSD like for the 6035c then just 60GiB.
Ext 4 5% of of each SSD after downstroke  in GiB after Nutanix Home capacity taken.
Genesis 5% of of each SSD in GiB after Ext 4 taken
Cassandra Homogeneous clusters

 

This is for all nodes

Max(30 GiB per node, 3% of HDD raw capacity + 3% of SSD raw capacity)

For heterogenous clusters

Find the largest node and then apply above equation for all nodes

Oplog Oplog reservation per node = MIN(0.25 *(SSD space left after cassandra, cache, curator reservation), 400GiB)
Content cache 20GB per node converted to GiB

 

What are the details on CVM overheads

  • HDD numbers can be seen by clicking the “I” button
  • SSD numbers can be seen by clicking the “I” button
  • In case of AF all the CVM components are applied to SSD CVM as shown below

 

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