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Bruno BELANYI 2021-04-10 20:20:57 +02:00
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@ -38,6 +38,59 @@ systems and related subjects, I was given this internship project to work on.
# Context of the subject
The exchange connectivity layer must route orders as fast possible, to stay
competitive, reduce transaction costs, and lower latencies which could result in
lost opportunities, therefore less profits.
It must also take on other duties, due to it being closer to the exchange than
the rest of the infrastructure. For example, a trading strategy can register
conditional orders with this service: it must monitor the price of product A and
X, if product A's cost rise over X's, then it must start selling product B at
price Y.
A new exchange connectivity service, called the Execution Gateway, is being
built at IMC, the eventual goal being to migrate all trading strategies to using
this gateway to send orders to exchanges. This will allow it to be scaled more
appropriately. However, care must be taken to maintain the current performance
during the entirety of the migration in order to stay competitive, and the only
way to ensure this is to measure it.
With that context, let's review my expected tasks once more, and expand on each
of them:
* Become familiar with the service: before writing the code for the benchmark
I must first understand what goes into the process of a trade at IMC, what is
needed from the gateway and from the clients in order to run them and execute
orders. There is a lot of code at IMC: having different teams working at the
same time on different trading service results in a lot of churn. The
global execution team was created to centralise the work on core services that
must be provided to the rest of the IMC workforce. The global execution
gateway is one such project, aiming to consolidate all trading strategies
under one singular method to send orders to their exchanges.
* Write a dummy load generator: we want to send orders under different
conditions in order to run multiple scenarios which can model varying cases
of execution. Having more data for varying corner cases can make us more
confident of the robustness and efficiency of the service. This is especially
needed becaue of the various roles that the gateway must fulfill: not only
must it act as a bridge for the communication between exchanges and traders,
but also as an order executor. All those cases must be accounted for when
writing the different scenarios.
* Benchmark the system under the load: once we can run those scenarios smoothly
we can start taking multiple measurements. The main one that IMC is interested
in is wall-to-wall latency (abbreviated W2W): the time it takes for a trade to
go from a trading strategy to an exchange. The lower this time, the more
occasions there are to make good trades.
FIXME: probably more context in my notes
* Analyze the measurements: the global execution team has some initial
expectations of the gateway's performance. A divergence on that part could
mean that the measurements are flawed in some way, or that the gateway is not
performing as expected. Further analysis can be done to look at the difference
between mean execution time and the 99th percentile, and analyse the tail of
the timing distribution: the smaller it is the better. Consistent timing is
more important than a lower average, because we must be absolutely confident
that a trade order is going to be executed smoothly, and introducing
inconsistent latency can result in bad trades.
# Internship roadmap
# Engineering practices