best practices for reduced latency with vmware nsx

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turbonomic.com REDUCING LATENCY WITH VMWARE NSX BEST PRACTICES TURBONOMIC MICRO-EBOOK

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Page 1: Best Practices for Reduced Latency with VMware NSX

turbonomic.com

REDUCING LATENCY WITH VMWARE NSXBEST PRACTICES

TURBONOMIC MICRO-EBOOK

Page 2: Best Practices for Reduced Latency with VMware NSX

turbonomic.com

ABOUT THE AUTHOR

Matt RaySales Engineer Manager at Turbonomic

Before joining Turbonomic Matt worked as a technology

specialist at Citrix in both the VDI, application delivery controller,

and cloud spaces. He moved over to VMTurbo after coming to

the realization that the key component missing across all these

spaces is a common control platform that allows business

applications to be delivered reliably. At Turbonomic, Matt heads

up the sales engineering team for the Northeast United States

and Canada working across a variety of industries including

retail, pharmaceutical, high tech, and finance among others.

Page 3: Best Practices for Reduced Latency with VMware NSX

turbonomic.com

What is NSX?

Before we go into how to reduce latency with NSX it’s important

to first understand what NSX is. The whole idea behind NSX,

and really SDN in general, is that physical networks shouldn’t

be a barrier to a VM getting access to the network resources it

needs. NSX is great in that it helps to turn the entire datacenter

into a pool of resources without requiring complex network

reconfiguration. Administrators, can easily assign policies to

VMs in order to determine which resources are accessible and

which aren’t

By taking this policy driven approach, as opposed to requiring network reconfiguration, NSX allows for a massively more

flexible network. But, with more flexibility also comes more complexity

Page 4: Best Practices for Reduced Latency with VMware NSX

turbonomic.com

Why is it complex?

While a policy driven approach is great from an administrative standpoint, it also introduces a new set of complexities

under the covers. Even though everything seems to be flat from the administrator’s point of view a physical network still

exists underneath. Furthermore, this physical layer is getting more and more complex as data centers continue to grow

in order to support an increase in application workload demand. This increased complexity is what introduces increased

risk of service degradation.

Page 5: Best Practices for Reduced Latency with VMware NSX

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Why is it complex?

Imagine a scenario where you have a standard two tier application consisting of an application server and a database

server. In common practice today these workloads would be placed close together and the administrative team would do

everything to make sure there is not latency between the application and the database. Now imagine that NSX comes

along and makes it easy for these VMs to exist anywhere in the environment. How do you make sure that you are still

able to minimize latency? Where should these VMs live in order to make the most of the compute resources available to

them while minimizing risk of packet loss?

Increased datacenter flexibility comes at the cost of increased datacenter complexity.

Turbonomic is a control platform designed to assure application performance as the datacenter becomes more

and more complex.

Page 6: Best Practices for Reduced Latency with VMware NSX

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How does Turbonomic help?

By understanding application workload demand and appropriately matching it to infrastructure supply, Turbonomic is able to

make sure that all applications have access to the resources that they need. In the case of NSX, Turbonomic interprets

standard NetFlow data to understand which VMs communicate frequently, and therefore should be physically close, and which

VMs do not communicate, and therefore could live on different switches or even in different datacenters. With this

understanding of VM communication in conjunction with underlying physical infrastructure, Turbonomic is able to make the

best decisions around where to place VMs with an understanding of network utilization.

This information is brought in as one piece of the larger puzzle

around understanding not only demand for network resources,

but also compute, storage, application response time, and any

other resources the VM may demand, all in order to match

demand with supply. And ultimately, assure application

performance.