According to a recent paper entitled The Cost of Latency in High-Frequency Trading, a 1-millisecond advantage in latency can be worth upwards of $100 million per year. So, if firm A trades with 2 ms of latency and firm B trades with 4 ms of latency, all things being equal, firm A sees a $200 million per year benefit. It seems only logical to combat latency as much as possible, but how can humans detect, let alone reduce latency by such imperceptible amounts? Where would you even begin?

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THE COST OF LATENCY IN THE DATA CENTER
THE 100 MILLION DOLLAR MILLISECOND
TURBONOMIC MICRO-EBOOK

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ABOUT THE AUTHOR
Ryan Strehlke
Sales Engineer at Turbonomic
Ryan graduated from Bates College in Maine in 2012, studied economics
and rhetoric. He began his career at Eze Software Group in Boston as a
Connectivity Consultant. a financial software firm that works with hedge
and mutual funds to implement and manage a diverse investment platform.
Ryan's been a Turbonomic Veteran since December 2014, working as a
pre-sales engineer supporting the Central/Southeast US. I’ve always been
interested in emerging technologies, and was naturally drawn to
Turbonomic’s unique economic approach. Hobbies include: fervent New
England Patriots fan, discovering new music, and struggling to play bogey
golf.

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B A C K GR OU N D
The old adage “time is money” has never been more relevant than in
today’s data centers, especially those of financial institutions and
brokerage firms. Since the mass adoption of virtualization, the lifecycle
of an electronically placed trade has gone from minutes to seconds, and
is now under a millisecond for “ultra-low latency” shops.
According to a recent paper entitled The Cost of Latency in High-
Frequency Trading, a 1-millisecond advantage in latency can be worth
upwards of $100 million per year. So, if firm A trades with 2 ms of
latency and firm B trades with 4 ms of latency, all things being equal,
firm A sees a $200 million per year benefit. It seems only logical to
combat latency as much as possible, but how can humans detect, let
alone reduce latency by such imperceptible amounts? Where would you
even begin?

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Spending to Save is a Costly Approach
Well, in attempt to reduce latency as much as possible, financial firms, and companies across other verticals, have taken
the “spend money to save money” approach. Significant capital is invested in reducing the distance that data has to
travel, both between physical and virtual endpoints. Trading firms will co-locate their datacenters in the same facility as
the exchange they are booking trades with, in attempt to eliminate latency associated with physical distance.
Likewise, converged and hyper-converged infrastructures are gaining popularity, being used to keep even the virtual
distance that data has to travel as minimal as possible. However, as we already know, throwing resources at workloads,
rather than controlling an infrastructure based on application demand, cannot assure application performance. It’s also
certainly not the most cost efficient approach.

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How Do Organizations Approach Latency?
For organizations with a limited IT budget, the spending
approach may not even be a feasible option. That doesn’t
mean that limiting, and even preventing latency isn’t still a
critical requirement. A recent Turbonomic-sponsored survey
of technology professionals across different verticals found a
discrepancy around not only how latency is measured within
organizations, but that some don’t attempt to track latency at
all.

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For those that do measure delay, the attempt to limit latency congestion differs as well. Most are leveraging some sort
of monitoring tool, while a smaller subset have moved towards all-flash storage arrays or software-defined networking.
Whether within storage, network, compute, or the VM itself, latency is a burden at every level of the IT stack. Trying to
combat delay within an isolated IT domain (only compute, storage, or network, etc.) is a futile, and eventually costly,
approach.

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A Real World Scenario
Let’s think about a real world scenario. A large hedge fund that trades
across different global exchanges has just had their IT budget cut for 2016.
Let’s call this firm Green Circle Financial, or GCF for short. GCF has
historically tried to “throw hardware at problems” by over-buying resources
and spinning up the biggest virtual machines they could. After a few years
of overspending, performance actually slightly degraded.
The C-level was not happy. How could GCF have spent so much money on compute, storage, and network, yet
still not see increases in performance? After hundreds of thousands of dollars, and a few wasted years, latency
has remained unchanged. Now, with a slashed IT budget for 2016, what is GCF to do?
This year the challenge is to do more with less…

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Congratulations – You’re Finished!
Blog – Application Latency: Read Now
Blog – Virtualization Management Mistakes: Read Now
Reducing Network Latency: Read Now
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