How exchanges turn order books into distributed logs
quant.engineering
How exchanges turn order books into distributed logs
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Re: How exchanges turn order books into distributed logs
#2First, it is of course possible to apply horizontal scaling through sharding. My order on Tesla doesn't affect your order on Apple, so it's possible to run each product on its own matching engine, its own set of gateways, etc. Most exchanges don't go this far: they might have one cluster for stocks starting A-E, etc. So they don't even exhaust the benefits available from horizontal scaling, partly because this would be expensive.
On the other hand, it's not just the sequencer that has to process all these events in strict order - which might make you think it's just a matter of returning a single increasing sequence number for every request. The matching engine which sits downstream of the sequencer also has to consume all the events and apply a much more complicated algorithm: the matching algorithm described in the article as "a pure function of the log".
Components outside of that can generally be scaled more easily: for example, a gateway cares only about activity on the orders it originally received.
The article is largely correct that separating the sequencer from the matching engine allows you to recover if the latter crashes. But this may only be a theoretical benefit. Replaying and reprocessing a day's worth of messages takes a substantial fraction of the day, because the system is already operating close to its capacity. And after it crashed, you still need to figure out which customers think they got their orders executed, and allow them to cancel outstanding orders.
Re: How exchanges turn order books into distributed logs
#3Re: How exchanges turn order books into distributed logs
#4A couple of quants had built a random forest regression model that could take inputs like time of day, exchange, order volume etc and spit out an interval of what latency had historically been in that range.
If the latency moved outside that range, an alert would fire and then I would co-ordinate a response with the a variety of teams e.g. trading, networking, Linux etc
If we excluded changes on our side as the culprit, we would reach out to the exchange and talk to our sales rep there would might also pull in networking etc.
Some exchanges, EUREX comes to mind, were phenomenal at helping us identify issues. e.g. they once swapped out a cable that was a few feet longer than the older cable and that's why the latency increased.
One day, it's IEX, of Flash Boys fame, that triggers an alert. Nothing changed on our side so we call them. We are going back and forth with the networking engineer and then the sales rep says, in almost hushed tones:
"Look, I've worked at other exchange so I get where you are coming from in asking these questions. Problem is, b/c of our founding ethos, we are actually not allowed to track our own internal latency so we really can't help you identify the root cause. I REALLY wish it was different."
I love this story b/c HN, as a technology focused site, often thinks all problems have technical solutions but sometimes it's actually a people or process solution.
Also, incentives and "philosophy of the founders" matter a lot too.
Re: How exchanges turn order books into distributed logs
#5A notable edge case here is that if EVERYTHING (e.g. market data AND orders) goes through the sequencer then you can, essentially, Denial of Service to key parts of the trading flow.
e.g. one of the first exchanges to switch to a sequencer model was famous for having big market data bursts and then huge order entry delays b/c each order got stuck in the sequencer queue. In other words, the queue would be 99.99% market data with orders sprinkled in randomly.
Re: How exchanges turn order books into distributed logs
#6At a past job (hedge fund), my role was to co-ordinate investigations into why latency may have changed when sending orders. A couple of quants had built a random forest regression model that could take inputs like time of day, exchange, order volume etc and spit out an interval of what latency had historically been in that range. If the latency moved outside that range, an alert would fire and then I would co-ordina…
Re: How exchanges turn order books into distributed logs
#7At a past job (hedge fund), my role was to co-ordinate investigations into why latency may have changed when sending orders. A couple of quants had built a random forest regression model that could take inputs like time of day, exchange, order volume etc and spit out an interval of what latency had historically been in that range. If the latency moved outside that range, an alert would fire and then I would co-ordina…
Curious what your actual role was -- sounds very interesting! Project manager? Dev? Operations specialist? E.g. were you hired into this role, and what were the requisites?
Many firms have them and they are a hybrid of:
- DevOps (e.g. we help, or own, deployments to production)
- SRE (e.g. we own the dashboards that monitored trading and would manage outages etc)
- Trading Operations (e.g. we would work with exchanges to set up connections, cancel orders etc)
My background is:
- CompSci/Economics BA
- MBA
- ~20 years of basically doing the above roles. I started supporting an in house Order Management System at a large bank and then went from there.
For more detail, here is my LinkedIn: https://www.linkedin.com/in/alex-elliott-3210352/
I also have a thread about the types of outages you see in this line of work here: https://x.com/alexpotato/status/1215876962809339904?s=20
(I have a lot of other trading/SRE related threads here: https://x.com/alexpotato/status/1212223167944478720?s=20)
Re: How exchanges turn order books into distributed logs
#8The title is obviously the wrong way around, exchanges turn distributed logs into order books. The distributed part is a resilience decision but not essential to the design (technically writing to a disk would give persistence with less ability to recover, or with some potential gaps in the case of failure (remember there is a sequence published on the other end too, the market data feed)). As noted in the article, t…
Re: How exchanges turn order books into distributed logs
#9This article both undersells and oversells the technical challenge exchanges solve. First, it is of course possible to apply horizontal scaling through sharding. My order on Tesla doesn't affect your order on Apple, so it's possible to run each product on its own matching engine, its own set of gateways, etc. Most exchanges don't go this far: they might have one cluster for stocks starting A-E, etc. So they don't eve…
For example, Order A and order B might interact with eachother... but they also might not. If we assume they do not, we can have them processed totally independently and in parallel, and then only if we later determine they should have interacted with each other then we throw away the results and reprocess.
It is very similar to the way speculative execution happens in CPU's. Assume something then throw away the results if your assumption was wrong.
Re: How exchanges turn order books into distributed logs
#10The title is obviously the wrong way around, exchanges turn distributed logs into order books. The distributed part is a resilience decision but not essential to the design (technically writing to a disk would give persistence with less ability to recover, or with some potential gaps in the case of failure (remember there is a sequence published on the other end too, the market data feed)). As noted in the article, t…
It would not surprise me at all if the sequencing step was done via FPGA processing many network inputs at line rate with a shared monotonic clock. This would give it some amount of parallelism.