Tag Archives: HCI

Predictable & Scalable MS Exchange 2016 Performance on Nutanix with AHV

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I’ve been doing some testing recently with Nutanix latest GA code (AOS 5.8) and I decided to do some quick MS Exchange Jetstress performance tests as part of a larger piece of work.

In short I wanted to check how well Exchange storage performance scaled so I performed three tests. I started with 4 threads, then increased to 8 and finally to 12 threads using Jetress with Exchange 2016 ESE database modules.

For this testing I disabled the Nutanix in memory read cache to ensure all read IO is serviced by the physical SSDs so the result is not artificially improved from cache.

I also disabled Compression, Erasure Coding and Deduplication as these also artificially improve performance due to Jetstress data being highly compressible & dedupable.

The hardware used was a NX-8150 with 6 x SSDs and Intel Broadwell processors. This is why the database size was only 1.7TB as that’s just below the total usable capacity of the node. The performance over larger database sizes remains the same when the metadata cache (in the Nutanix Controller VM) is sized for the desired working set size as shown by our ESRP certification.

The hypervisor is Acropolis Hypervisor (AHV) which is fully certified for Microsoft Windows under the MS SVVP programme as well as MS ESRP certified for MS Exchange.

So here is the result for 4 threads.

Jetstress2016_4Threads

5580 IOPS with just 4 threads is very good performance and is sufficient for at least five thousand mailboxes with hundreds of messages per day which is maximum recommended active users per Exchange MSR server.

The next question is: What’s the latency for the database reads and log writes? (These are two of the critical performance metrics for Jetstress Pass/Fail results)

Jetstress2016_4Threads_Latency

Here we can see log write latency average across all four log drives is below 1ms (0.99ms) and database read latency at 1.16ms.

Next up, here is the result for 8 threads.

Jetstress2016_8Threads

10147 IOPS with 8 threads is excellent performance and shows Nutanix easily has headroom for more than ten-thousand mailboxes with hundreds of messages per day which easily exceeds the requirements for the maximum recommended active users per Exchange MSR server.

Again let’s check out the latency, Here we can see log write latency average across all four log drives is still below 1ms (0.99ms) and database read latency at 1.29ms. That’s just 0.13ms higher latency for reads and exactly the same write latency while achieving almost DOUBLE the IOPS.

Jetstress2016_8Threads_Latency

Lastly here is the result for 12 threads.

Jetstress2016_12Threads

14351 IOPS with 12 threads proves how scalable the Nutanix platform is as this is almost a linear increase in IOPS.

Again let’s check out the latency, Here we can see log write latency average across all four log drives is still below 1ms (0.98ms) and database read latency at 1.42ms. That’s just 0.14ms higher latency for reads and slightly lower write latency while achieving almost linear improvement in IOPS.

Jetstress2016_12Threads_Latency

Summary:

Nutanix provides extremely high, predictable performance for even the most demanding MS Exchange environments.

 

Nutanix Scalability – Part 1 – Storage Capacity

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It never ceases to amaze me that analysts as well as prospective/existing customers frequently are not aware of the storage scalability capabilities of the Nutanix platform.

When I joined back in 2013, a common complaint was that Nutanix had to scale in fixed building blocks of NX-3050 nodes with compute and storage regardless of what the actual requirement was.

Not long after that, Nutanix introduced the NX-1000 and NX-6000 series which had lower and higher CPU/RAM and storage capacity options which gave more flexibility, but still there were some use cases where Nutanix still had significant gaps.

In October 2013 I wrote a post titled “Scaling problems with traditional shared storage” which covers why simply adding shelves of SSD/HDD to a dual controller storage array does not scale an environment linearly, can significantly impact performance and add complexity.

At .NEXT 2015, Nutanix announced the ability to Scale Storage separately to Compute which allowed customers to scale capacity by adding similar to a shelf of drives like they could with their legacy SAN/NAS, but with the added advantage of having a storage controller (the Nutanix CVM) to add additional data services, performance and resiliency.

Storage only nodes are supported with any Hypervisor but the good news in they run on Nutanix’ Acropolis Hypervisor (AHV) which means no additional hypervisor licensing if you run VMware ESXi, and storage only nodes still support all the 1-click rolling upgrades so they add no additional management overhead.

Advantages of Storage Only Nodes:

  1. Ability to scale capacity seperate to CPU/RAM like a traditional disk shelf on a storage array
  2. Ability to start small and scale capacity if/when required, i.e.: No oversizing day 1
  3. No hypervisor licensing or additional management when scaling capacity
  4. Increased data services/resiliency/performance thanks to the Nutanix Controller VM (CVM)
  5. Ability to increase capacity for hot and cold data (i.e.: All Flash and Hybrid/Storage heavy)
  6. True Storage only nodes & the way data is distributed to them is unique to Nutanix

Example use cases for Storage Only Nodes

Example 1: Increasing capacity requirement:

MS Exchange Administrator: I’ve been told by the CEO to increase our mailbox limits from 1GB to 2GB but we don’t have enough capacity.

Nutanix: Let’s start small and add storage only nodes as the Nutanix cluster (storage pool) reaches 80% utilisation.

Example 2: Increasing flash capacity:

MS SQL DBA: We’re growing our mission critical database and now we’re hitting SATA for some day to day operations, we need more flash!

Nutanix: Let’s add some all flash storage only nodes.

Example 3: Increasing resiliency

CEO/CIO: We need to be able to tolerate failures and the infrastructure self heal but we have a secure facility which is difficult and time consuming to get access too, what can we do?

Nutanix: Let’s add some storage only nodes to ensure you have enough capacity (All Flash and/or Hybrid) to ensure sufficient capacity to tolerate “n” number of failures and rebuild the environment back to a fully resilient and performant state.

Example 4: Implementing Backup / Long Term Retention

CEO/CIO: We need to be able to keep 7 years of data for regulatory requirements and we need to be able to access it within 1hr.

Nutanix: We can either add storage only nodes to one or more existing clusters OR create a dedicated Backup/Retention cluster. Let’s start with enough capacity for Year 1, and then as capacity is required, add more storage only nodes as the cost per GB drops over time. Nutanix allows mixing of hardware generations so you’ll never be in a situation where you need to rip & replace.

Example 5: Supporting one or more Monster VMs

Server Administrator: We have one or more VMs with storage capacity requirements of 100TB each, but the largest Nutanix node we have only supports 20TB. What do we do?

Nutanix: The Distributed Storage Fabric (ADSF) allows a VMs data set to be distributed throughout a Nutanix cluster ensuring any storage requirement can be met. Adding storage only nodes will ensure sufficient capacity while adding resiliency/performance to all other VMs in the cluster. Cold data will be distributed throughout the cluster while frequently accessed data will remain local where possible within the local storage capacity on the node where the VM runs.

For more information on this use case see: What if my VMs storage exceeds the capacity of a Nutanix node?

Example 6: Performance for infrequently accessed data (cold data).

Server Administrator: We have always stored our cold data on SATA drives attached to our SAN because we have a lot of data and flash is expensive. One or twice a year we need to do a bulk read of our data for auditing/accounting purposes but it’s always been so slow. How can we solve this problem and give good performance while keeping costs down?

Nutanix: Hybrid Storage only nodes are a cost effective way to store cold data and combined with ADSF, Nutanix is able to deliver optimum read performance from SATA by reading from the replica (copy of data) with the lowest latency.

This means if a HDD or even a node is experiencing heavy load, ADSF will dynamically redirect Read I/O throughout the cluster to Deliver Increased Read Performance from SATA. This capability was released in 2015 and storage only nodes adding more spindles to a cluster is very complimentary to this capability.

Frequently asked questions (FAQ):

  1. How many storage only nodes can a single cluster support?
    1. There is no hard limit, typically cluster sizes are less than 64 nodes as it’s important to consider limiting the size of a single failure domain.
  2. How many Compute+Storage nodes are required to use Storage Only nodes?
    1. Two. This also allows N+1 failover for the nodes running VMs in the event a compute+storage node failed so VMs can be restarted. Technically, you can create a cluster with only storage only nodes.
  3. How does adding storage only node increase capacity for my monster VM?
    1. By distributing replicas of data throughout the cluster, thus freeing up local capacity for the running VM/s on the local node. Where a VMs storage requirement exceeds the local nodes capacity, storage only nodes add capacity and performance to the storage pool. Note: One VM even with only one monster vDisk can use the entire capacity of a Nutanix cluster without any special configuration.

Summary:

For many years Nutanix has supported and recommended the use of Storage only nodes to add capacity, performance and resiliency to Nutanix clusters.

Back to the Scalability, Resiliency and Performance Index.

Nutanix X-Ray Benchmarking tool – Snapshot Impact Scenario

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In the first part of this series, I introduced Nutanix X-Ray benchmarking tool which has been designed very differently to traditional benchmarking tools as the performance of the app is the control and the variable is the platform,not the other way around.

This is done by generating realistic IO patterns (e.g.: Not 100% 4k read) and then performing functions against the platform to see how the control (the VM application performance) is impacted by the underlying platforms functionality.

A great example of this is performing snapshots as the first step in a space efficient backup solution.

X-Ray has a built in test which generates an OLTP workload which is ran for 8 hours which for an all flash platform generates 6000 IOPS across the database and 400 IOPS for the logs. The scenario is detailed in the X-Ray report shown below.

XraySnapshotImpactDescription

The Snapshot impact scenario is then ran against multiple platforms and using the Analysis functionality within X-ray. we can generate a report which overlays the results from multiple platforms.

The below example is GA Acropolis Hypervisor (AHV) on AOS 5.1.1 verses a leading hypervisor and SDS platform showing the snapshot impact scenario.

XraySnapshotImpact

Each of the red lines indicate a snapshot and what we observe is the performance of both platforms remains consistent until the 10th snapshot (shown below) where the Nutanix platform continues without impact and the leading hypervisor and SDS platform starts degrading significantly.

XraySnapshotImpactSnap10

In the real world, customers use the intelligent features of storage, SDS or hyper-converged platforms but rarely test how this functionality works prior to purchasing. This is because it’s difficult and time consuming to do so.

Nutanix X-Ray tool makes the process of validating a platforms performance under real world scenarios a quick and easy process and provides automatically generated reports where accurate comparisons can be made.

What this example shows is that while both platforms could achieve the required performance without snapshots, only Nutanix AHV & AOS could maintain the performance while utilising snapshots to achieve the type of recovery point objective (RPO) that is expected in production environments, especially with business critical workloads.

As part of the Nutanix Solutions and Performance engineering organisation, I can tell you that the focus for Nutanix is real world performance, using data reduction, leveraging snapshots, mixing workloads and testing a large scale.

In upcoming posts I will show more examples of X-Ray test scenarios as well as comparisons between GA Acropolis Hypervisor (AHV) & AOS 5.1.1 verses a leading hypervisor and SDS platform.

Related Articles:

Nutanix X-Ray Benchmarking tool Part 1 – Introduction

Nutanix X-Ray Benchmarking tool Part 3 – Extended Node Failure Scenario