Tag Archives: Throughput

Full NVMe or not Full NVMe, that is the question

Image result for nvme logo

As you have seen, my recent posts have been around Intel Optane and the performance gains that can be delivered by implementing the technology into a vSAN environment. I have been asked many times about what benefits a full NVMe solution would bring and what such a solution would look like, but before we go into that, let’s talk about NVMe, what exactly is NVMe?

Non-Volatile Memory Express (NVMe) is not a drive type, but more of an interface and protocol solution that looks like is set to replace the SAS/SATA interface. It encompasses a PCIe controller and the whole purpose of NVMe is to exploit the parallelism that flash media provides which in turn reduces the I/O overhead and thus improve performance. As SSDs become faster, protocols like SAS/SATA which were designed for slower hard disks where the delay between the CPU request and data transfer was much higher, the requirement for faster protocols become evident, and this is where NVMe comes into play.

So in a vSAN environment, what does a full NVMe solution look like? Because vSAN is currently a two tier architecture (Cache and Capacity) a full NVMe solution would mean that both tiers have to have NVMe capable drives and this can be done with either all Standard NVMe drives in both cache and capacity, or using a technology like Intel Optane NVMe as the Cache and Standard NVMe as capacity. So from an architecture perspective it is pretty straight forward, but how does performance compare, for this I persuaded my contacts at Intel to provide me some Full NVMe kit in order to perform some benchmark tests, and in order to provide a like for like comparison, I ran the same benchmark tests on an Optane+SATA configuration.

Cluster Specification:
Number of Nodes: 4
Network: 2x 10gbit in LACP configuration
Disk groups per node: 2
Cache Tier both clusters: 2x Intel Optane 375GB P4800X PCIe Add In Card
Capacity Tier Optane/SATA: 8x 3.84TB SATA S4510 2.5″
Capacity Tier Full NVMe: 8x 2.0TB NVMe P4510 2.5″ U.2

Test Plan:
Block Size: 4K, 8K, 16K, 32K, 64K, 128K
I/O Pattern: Random
Read/Write Ratio: 0/100, 30/70, 70/30, 100/0
Number of VMs: 120
Number of VMDKs per VM: 1
Size of VMDK: 50GB
Storage Policy: FTT=1, RAID1

Let’s look at the results:

And if you want the numbers:

So what is clear here that Optane serves really well in the cache tier in both solutions, however in the Full NVMe solution read performance is significantly improved also, in the 128K, 100% read test the 2x10G Links were being pushed to their limits, but not only was we able to push up throughput and IOPS but we also drove down latency, in some cases reducing it by over 50%.

So why would you choose a full NVMe solution? The simple answer here is if you have applications that are latency sensitive then having clusters dedicated to those applications would be adequately provided for from an IOPS, Throughput and Latency perspective with Full NVMe.

Vendors have also recognised this, for example Dell EMC have just launched their Intel Optane Powered Full NVMe vSAN Ready node, based on the R740xd platform and consists of similar drives to what I have used in the tests here being the Optane 375GB and P4510 U.2 NVMe drives, you can see the vSAN ready node details here

So clearly NVMe has major performance benefits over traditional SAS/SATA devices, could this be the end of SAS/SATA in the not so distant future?

Optane Performance

Many times over the past few months I have been asked about the benefits of using Intel Optane NVMe in a vSAN environment, although there was marketing material from Intel that boasted a good performance boost I decided (purely out of curiosity) to do some performance benchmarking and compare Optane as the cache devices versus SAS as the cache devices. The performance benchmark test used exactly the same servers and networking in order to provide a level playing field, the only thing that was changed was the cache devices being used in the disk groups.

Server Specification:

  • 6x Dell PowerEdge R730xd
  • Intel Xeon CPU E5-2630 v3 @ 2.40GHz
  • 128GB RAM
  • 2x Dell PERC H730 Controllers
  • 2x Intel Dual Port 10Gb ethernet adapters (Configured with LACP)

Disk group config for the SAS test:

  • 3x Disk Groups
  • 3x 400GB SAS SSD per disk group
  • 1x 400GB SAS SSD per disk group

Disk group config for the Optane test

  • 2x Disk Groups
  • 3x 400GB SAS SSD per disk group
  • 1x 750GB Optane NVMe P4800X per disk group

Whilst you could say that the configurations are not identical, since the Write Buffer is limited to 600GB per disk group then both configurations have the same amount of write buffer, the SAS config has more backend disks which would serve as an advantage.

For the purpose of the Benchmark, we used HCI Bench to automate the Oracle VDBench workload testing and each test was based on the following, the test was designed to max-out the system hence the high number of VMDKs used here (250)

  • 50 Virtual Machines
  • 5 VMDKs per virtual machine
  • 2 threads per VMDK
  • 20% working set
  • 4k, 8k, 16k, 32k, 64k and 128k block size
  • 0%, 30%, 70%, 100% write workload
  • 900 second test time for each test

So what were the results?

4K Blocksize:

8K Blocksize:

16K Blocksize:

32K Blocksize:

64K Blocksize:

128K Blocksize:

As you can see Optane really did boost the performance even though the server platform wasn’t the ideal platform for the Optane devices (Dell said those cards will not be certified in the 13G platform), however despite the fact that the workload was designed to max-out the system, in some cases latency was reduced to almost a third and throughput was was increased in some cases to 3x.

Conclusion: Optane really does live up to expectations, and it isn’t just marketing, I have yet to test a full NVMe system to see how much it can really be pushed, but I hope the numbers above go someway to convice you why you should consider optane as the cache tier in vSAN.

Day-2 Operations – Performance Monitoring in the vSAN UI

Performance reporting or Performance Monitoring is something of a must in any storage environment today, I remember many times when I was in VMware Support when facing a customer storage performance issue that metrics were not there to capture the event, and most storage performance tools required enabling, obviously this meant that the issue had to be occurring at the time of the performance metrics grab, vSAN in the early days was no different, vSAN Observer whilst being a detailed tool and provided a lot of information, was not a historical tool, it was enabled to troubleshoot a performance issue that was happening at that particular time.

In the later releases of vSAN the UI came equipped with more performance metrics than you could shake a stick at, which from a performance troubleshooting and monitoring perspective is the dogs danglies, but what does this mean from an every day perspective?  Before we take a look at the UI, there are three areas where vSAN Performance metrics can be displayed

  • Cluster level – This is the performance metrics aggregated for the whole cluster and allow you to have the high level view of how your cluster is performing as a whole
  • Host Level – This allows you to look at how vSAN is performing on a host by host perspective and contains further information drilling down through things like Disk Groups, Physical Disks, Network Controllers, VMkernel interfaces.
  • VM Level – This focuses on a specific virtual machine and the objects associated with it.

So what information do we have exactly for a given observation level?  Well let’s first of all take a look at the cluster level performance information, there are three options under the performance tab for vSAN

  • vSAN – Virtual Machine Consumption
  • vSAN – Backend
  • vSAN – iSCSI

I have met many customers that immediately notice there is a big difference between the Virtual Machine Consumption and the Backend graphs, so before we go any further let’s talk about what each of these specific areas mean.

Virtual Machine Consumption
These graphs represent the values that objects residing on the vSAN Datastore are seeing, now remember everything that exists on vSAN is an object, so consumers that are counted in these graphs are Virtual Machines, Stats Objects etc

Backend
These graphs represent the backend disks associated with vSAN, cache and capacity

Both sets of graphs cover the statistics for:

  • IOPS
  • Throughput
  • Latency
  • Congestion
  • Outstanding I/O

iSCSI
The iSCSI Performance graphs contain all the graphs above with the exception of Congestion, these graphs are in relation to each iSCSI Target/LUN created and each one is selected in turn to review the performance graphs associated.

If we move our focus to a host level, in here we have a number of options in addition to the three we also see at a cluster level, however there is some additional metrics we get at a host level for Virtual Machine Consumption and Backend, in the Virtual Machine Consumption graph we have Local Client Cache Hit IOPS and Local Client Cache Hit Rate

And under Backend we also have some additional graphs for Resync IOPS, Resync Throughput and Resync LatencyThe resync metrics are extremely important if vSAN is recovering from a failure of some sort and performing a resync of degraded components, it is also important if you are performing a pro-active rebalance, policy change or a full data migration during host or disk/diskgroup evacuation.

The other options listed under host vSAN performance are:

  • Disk Group – Shows the performance graphs for the disk groups, I will cover this below as this is one of the most interesting set of metrics with a lot of detail.
  • Disk – Shows the physical disks in the host reporting on IOPS, Throughput and  Latency
  • Physical Adapters – Shows the network stats for each vmnic associated with vSAN, stats include Packet Loss Rate which is good for troubleshooting networking issues
  • VMkernel Adapters – Shows the statistics for each VMkernel configured for vSAN, this also includes a Packet Loss Rate which you can then use to troubleshoot the software network stack
  • VMkernel Adapters Aggregation – This is an aggregation of all VMkernel interfaces being used for vSAN on the host

Now let’s go back to the Disk Group performance graphs, as I said earlier this is a very interesting group of metrics to explore, so what do we have in this group?  The first section is all about Frontend (Guest) IOPS, Throughput and Latency

The frontend statistics are maybe as you have guessed already, they are related to vSAN Object I/O being generated from guests running within the vSAN cluster.  If we scroll down a little further we can see statistics relating to Overhead IO,  Read Cache Hit Rate (for hybrid) and Evictions:

Further down we have statistics relating to the vSAN Write Buffer and De-stage rate clearly showing how much of the write buffer is free and also how quickly data is being de-staged from cache to capacity, now we also have resync metrics under disk groups, however this differs slightly against the Cluster Wide Backend statistics, in the disk group graphs we actually have values that represent various aspects of the Resync Operations, the graph differentiates between:

  • Policy Changes
  • Repairs
  • Rebalance

So you can easily distinguish what resync operations are happening by the statistics within the disk group stats.

Collection Interval
The vSAN Performance metrics collect the sample every five minutes, and this is an average over that five minute period, if your cluster is hardly doing anything (like my cluster for the screenshots) then this can throw out some of the latency numbers, in my own cluster I have noticed it shows higher latency when doing practically nothing than it does when I start putting load on the cluster.  I have spoken to many customers about this, it is no concern, it just means that during the collection sample maybe a few “Large” IO operations returned a larger Latency and because of the low number of samples, this skews the average, so no cause for alarm on that one.

Up next will be Day-2 Operations, Performance Monitoring with vROPS, I just have to write it first 🙂