Category Archives: Nutanix

Cost vs Reward for the Nutanix Controller VM (CVM)

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I hear a lot of FUD (Fear Uncertainty and Doubt) getting thrown around about the Nutanix Controller VM (CVM) being a resource (vCPU/vRAM) hog.

So I thought I would address this perceived issue.

For those of you who are car people, you will understand the benefits of a Supercharger increasing performance of an engine.

The supercharger does this by attaching a belt to a pulley connected to the motor which spins the supercharger to force more air into the combustion chambers. This allows more fuel to be added to the mix to produce higher horsepower from the same engine displacement (engine capacity, ie: 2.0 Litres)

What is downside of a Supercharger?

The supercharger belt connected to the pulley can require even hundreds of horsepower to simply drive the supercharger. As such, a 300HP engine may have to use half of its power to just drive the supercharger.

So for example, a 300HP engine less 60HP (25%) to drive the supercharger equates to only 240HP remaining. But, as a result of the supercharger forcing more air into the engine, the engine now produces an additional 200HP.

So the “cost” of running the supercharger is 60HP, but the overall benefit is 200HP, resulting in the engine now producing 440HP.

Let’s now relate this back to the Nutanix Controller VM (CVM).

The CVM provides the storage features,functionality,excellent scalability and performance for the Virtual Machines. For example, reducing the latency thanks to Data Locality keeping data local to the compute node running the VM for faster reads and writes.

The faster the reads and writes, the less time VMs spend in a “CPU wait” state waiting for I/Os to be acknowledged by the storage which means the CPUs are being more efficiently utilized. This is a small part of the value the Nutanix CVM provides.

In Summary, the CVM does use some compute resources from the host (which depend on the node type and performance required) but like a Supercharger to an engine, the Nutanix CVM delivers significantly higher value to the VMs than the resources it uses.

Related Articles:

1. Rule of Thumb: Sizing for Storage Performance in the new world.

2. Is VAAI beneficial with Virtual Storage Appliance (VSA) based solutions ?

3. PART 1 – Problems with RAID and Object Based Storage for data protection

Microsoft Exchange on Nutanix Best Practice Guide

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I am pleased to announce that the Best Practice guide for Microsoft Exchange on Nutanix is released and can be found here.

For me deploying MS Exchange on Nutanix with vSphere combines best of breed application level resiliency (in the form of Exchange Database Availability Groups), infrastructure and hypervisor technologies to provide an infrastructure with not only high performance, but with industry leading scalability, no silos and very high efficiency & resiliency.

All of this leads to overall lower CAPEX/OPEX for customers.

In summary by Virtualizing MS Exchange on Nutanix, customers realize several key benefits including:

  • Ability to use a standard platform for all workloads in the datacenter, thus allowing the removal of legacy silos resulting in lower overall cost, and increased operational efficiencies.
    • An example of this is no disruption to MS Exchange users when performing Nutanix / Hypervisor or HW maintenance
  • A highly resilient , scalable and flexible MS Exchange deployment.
  • Reducing the number of Exchange Mailbox servers required to maintain 4 copies of Exchange data thanks to the combination of NDFS + DAG. (2 copies at NDFS layer / 2 copies at DAG layer)
  • Eliminate the need for large / costly refresh cycles of HW as individual nodes can be added and removed non disruptively.
  • Simplified architecture, no need for complex sizing architecture or risk of over sizing day 1, start small and scale VMs, Compute or storage if/when required.
  • No dependency of specific HW, Exchange VMs can be migrated to/from any Nutanix node and even to non Nutanix nodes.
  • Full support from Nutanix including at the Exchange, Hypervisor and Storage layers with support from Microsoft via Premier Support contracts or via TSANet.
  • Lower CAPEX/OPEX as Exchange can be combined with new or existing Nutanix/Virtualization deployment.
  • Reduced datacenter costs including Power, Cooling , Space (RU)

I hope you enjoy the Best Practice guide and look forward to hearing about your MS Exchange on Nutanix questions & experiences.

PART 2 – Problems with RAID and Object Based Storage for data protection

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Following on from Part 1, this post will discuss hyper-converged Distributed File Systems (i.e,: Nutanix) and compare with traditional SAN/NAS RAID and  hyper-converged solutions using Object storage for data protection.

The below diagram shows a 4 node hyper-converged solution using a Distributed File System with the same 4 x 4TB SATA drives with data protection using replication with 2 copies. (Nutanix calls this Resiliency Factor 2)

HyperconvergedDFSNormal

The first difference you may have noticed, is the data is much more granular than the Hyper-Converged Object store example in Part 1.

The second less obvious difference is the replicated copies of the data (i.e.: The data with Purple letters) on node 1 do not reside on a single other node, but are distributed throughout the cluster.

Now lets look at a drive failure example:

Here we see Node 1 has lost a Drive hosting 8 granular pieces of data 1MB in size each.

HyperconvergedDFSRecovery

Now the Distributed File System detects that the data represented by A,B,C,D,E,I,M,P has only a single copy within the cluster and starts the restoration process.

Lets walk through each step although these steps are completed concurrently.

1. Data “A” is replicated from Node 2 to Node 3
2. Data “B” is replicated from Node 2 to Node 4
3. Data “C” is replicated from Node 3 to Node 2
4. Data “D” is replicated from Node 4 to Node 2
5. Data “E” is replicated from Node 2 to Node 4
6. Data “I” is replicated from Node 3 to Node 2
7. Data “M” is replicated from Node 4 to Node 3
8. Data “P” is replicated from Node 4 to Node 3

Now the cluster has restored resiliency.

So what was the impact on each node?readwriteiorecovery

The above table shows a simplified representation of the workload of restoring resiliency to the cluster. As we can see, the workload (being 8 granular pieces of data being replicated) was distributed across the nodes very evenly.

Next lets look at the advantages of a Hyper-Converged Solution with a Distributed File System (which Nutanix uses).

  1. Highly granular distribution using 1MB extents not large Objects.
  2. The work required to restore resiliency after one drive (or node) failure was distributed across all drives and nodes in the Cluster leveraging all drives/nodes capability. (i.e.: Not constrained to the <100 IOPS of a single drive)
  3. The restoration rebuild is a low impact activity as the workload is distributed across the cluster and not dependant on source/destination pair of drives or nodes
  4. The rebuild has a low impact on the virtual machines running on the distributed file system and consistent performance is maintained.
  5. The larger the cluster the quicker and lower impact the rebuild is as the workload is distributed across a higher number of drives/nodes for the same size (Gb) worth of restoration.
  6. With Nutanix SSDs are used not only for Read/Write cache but as a persistent storage tier, meaning the recovering data will be written to SSD and where the data being recovered is not in cache (Memory or SSD tiers) it is still possible the data will be in the persistent SSD tier which will dramatically improve the performance of the recovery.

Summary:

As discussed in Part 1, Traditional RAID used by SAN/NAS and Hyper-converged solutions using Object based storage both suffer similar issues when recovering from drive or node failure.

Where as Nutanix Hyper-converged solution using the Nutanix Distributed File System (NDFS) can restore resiliency following a drive or node failure faster and with lower impact thanks to its highly granular and distributed architecture, meaning more consistent performance for virtual machines.