When talking about performance, it’s easy to get caught up in comparing unrealistic speed and feeds such as 4k I/O benchmarks. But, as any real datacenter technology expert knows, IOPS are just a small piece of the puzzle which, in my opinion, get far too much attention as I discussed in my article Peak Performance vs Real World Performance.

When I talk about performance, I am referring to all the components within the datacenter including the Management components, Applications/VMs, Analytics, Data Resiliency and everything in between.

Let’s look at a few examples of how Nutanix XCP running Acropolis Hypervisor (AHV) ensures consistent high performance for all components:

Management Performance:

The Acropolis management layer includes the Acropolis Operating System (formally NOS), Prism (HTML 5 GUI) and Acropolis Hypervisor (AHV) management stack made up of “Master” and “Slave” instances.

This architecture ensures all CVMs actively and equally contribute to ensuring all areas of the platform continue running smoothly. This means there is no central application, database or component which can cause a bottleneck, being fully distributed is key to delivering a web-scale platform.

Each Controller VM (CVM) runs the components required to manage the local node and contribute to the distributed storage fabric and management tasks.

For example: While there is a single Acropolis “Master” it is not a single point of failure nor is it a performance bottleneck.

The Acropolis Master is responsible for the following tasks:

1. Scheduler for HA
2. Network Controller
3. Task Executors
4. Collector/Publisher of local stats from Hypervisor
5. VNC Proxy for VM Console connections
6. IP address management

Each Acropolis Slave  is responsible for the following tasks:

1. Collector/Publisher of local stats from Hypervisor
2. VNC Proxy for VM Console connections

Regardless of being a Master or Slave, each CVM performs the two heaviest tasks: The Collection & Publishing of Hypervisor stats and, when in use, the VM console connections.

The distributed nature of the XCP platform allows it too achieve consistently high performance. Sending stats to a central location such as a central management VM and associated database server not only can become a bottleneck, but without introducing some form of application level HA (e.g.: SQL Always On Availability Group) it also could be a single point of failure which is for most customers unacceptable.

The roles which are performed by the Acropolis Master are all lightweight tasks such as the HA scheduler, Network Controller, IP address management and Task Executor.

The HA scheduler task is only active in the event of a node failure which makes it a very low overhead for the Master. The Network Controller task is only active when tasks such as new VLANs are being configured and Task Execution is simply keeping track of all tasks and distributing them for execution across all CVMs. IP address management is essentially a DHCP service, which is also an extremely low overhead.

In part 8, we will discuss more about Acropolis Analytics.

Data Locality

Data locality is a unique feature of XCP where new I/O writes to the local node where the VM is running as well as replicated to other node/s within the cluster. Data locality eliminates the requirement for servicing subsequent Read I/O by traversing the network and utilizing a remote controller.

As VMs migrate around a cluster, Write I/O is always written locally and remote reads will only occur if remote data is accessed. If data is remote and never accessed, no remote I/O will occur. As a result, it is typical for >90% of I/O to be serviced locally.

Currently bandwidth and latency across a well designed 10Gb network may not be an issue for some customers, however as flash performance exponentially increases the network could quite easily become a major bottleneck without moving to expensive 40Gb (or higher) networking. Data locality helps minimize the dependency on the network by servicing the majority of Read I/O locally and by writing one copy locally it reduces the overheads on the network for Write I/O. Therefore Data Locality allows customers to run lower cost networking without compromising performance.

While data locality works across all supported hypervisors,  AHV is unique as it supports data-aware virtual machine placement:  Virtual Machines are powered onto the node with the highest percentage of local data for that VM which minimizes the chance of remote I/O and reduces the overheads involved in servicing I/O for each VM following failures or maintenance.

In addition, Data Locality also applies to the collection of back end data for Analysis such as hypervisor and virtual machine statistics. As a result, statistics are written locally and a second (or third for environments configured with RF3) written remotely. This means stats data which can be a significant amount of data has the lowest possible impact on the Distributed File System and cluster as a whole.

Summary:

1. Management components scale with the cluster to ensure consistent performance
2. Data locality ensures data is as close to the Compute (VM) as possible
3. Intelligent VM placement based on Data location
4. All Nutanix Controller VMs work as a team (not in pairs) to ensure optimal performance of all components and workloads (VMs) in the cluster

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