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We detail critical parts of the architecture: relationships between main\ncomponents, strategy life-cycle and integration examples for both testing and production.

\n

--- excerpt ---

\n

This post is part of a 3-subseries in which we design the high-level architecture for Cryptomate.

\n
\n
    \n
  1. Modules and components.
    2. \n
  2. Exploring patterns.
    3. \n
  3. Critical points (this post).
    4. \n
\n
\n

In this post, we detail critical parts of the architecture: relationships between main\ncomponents, strategy life-cycle and integration examples for both testing and production.

\n

Component relations

\n

Market – strategy

\n

In the modules post, we determined that:

\n\n

In order to encapsulate the complexity of dealing with multiple market adapters, we will break\nit down into several components:

\n\n

We can now refine the relationship between the strategy and market modules, as a\nport/adapter-relationship using a simplified interface that the Market Engine implements.\nThis clean separation will make it easy to replace the component with a proxy when the\nmarket module is deployed as a micro-service.

\n
\"Detailed
Detailed market – strategy evaluator relationship. Teal trapezoids are ports.
\n

Other noteworthy points:

\n\n

Trading – strategy

\n

As for the market adapters, multiple trading adapters can coexist. Unlike market adapters\nhowever, multiple uses of a trading adapter cannot be merged, as they are likely to use\ndifferent accounts on the trading platform.

\n\n
\"Detailed
Detailed trading module – strategy evaluator relationship. Teal trapezoids are ports.
\n

Noteworthy points:

\n\n

Strategy life-cycle

\n

The strategy evaluator module is at the core of the system. It revolves around running\nuser-supplied business logic in a controlled environment.\nIn turn, that user-supplied business logic and its configuration determine what components\nshould be instantiated and destroyed in other parts of the system.

\n

In order to abstract out the layout and complexity of Cryptomate, and control strategy's\nenvironment, we introduce a strategy host module as the single interlocutor for\nthe strategy.

\n

Also, we identified the necessity of a strategy builder module\nto encapsulate the complexity of setting up a trading strategy. Here is an overview of the\nrequired steps:

\n\n

Lastly, as the unique interlocutor of a strategy, its host can track allocated components\nand ensure they are disposed of when the strategy is shut down.

\n

Composition roots

\n
\n

In all software, components form a graph of interconnections as they are composed to\nbuild the system. Most often, this graph has a single component that stands at the root\nof the graph. Hence, “composition root”.

\n
\n

As Cryptomate is modular and flexible composition was part of our requirements, we\nhave multiple composition graphs, with different roots.

\n

To ensure we do not forget important use cases, we will define a few reference scenarios\nto check against while we implement the system.

\n

Custom use as API

\n

In this scenario, Cryptomate is loaded as a library by a third-party program. That is,\nthe composition root is external. In that case, it offers a set of APIs for the\nthird-party developer to use, namely:

\n\n

In addition, all ports are exposed to the third party, so it can provide custom adapters.\nFor adapters that are loaded automatically by Cryptomate, an adapter registry is exposed\nso custom adapters can be added.

\n

Integrated service

\n

In this scenario, Cryptomate runs as a standalone, integrated service. This is the typical\nsetup for an end-user that runs it on his desktop, or a server dedicated to Cryptomate, for\na single user.

\n
\"Cryptomate
Cryptomate example deployment: lightweight integrated service. Teal elements are external to Cryptomate.
\n

The (external) user interface can connect and disconnect to the control endpoint to query\nthe state and start/stop strategies.

\n

All components run within Cryptomate, making deployment and administration easy. This means,\nhowever, that market history recording, if enabled, stops when the system is shut down.

\n

Split market recorder

\n

In this scenario, we split market recording, so it can keep recording while the core of the\nsystem is updated or restarted. This is a typical setup for a power user that needs consistent\nhistory to run back-tests on detailed historical data (ticks). Such a setup would normally\ndeploy Cryptomate alongside the market service.

\n
\"Cryptomate
Cryptomate example deployment: with standalone market service.
\n

Since such a setup puts a special focus on recording market history, it would probably use\nspecialized high-volume NoSQL database such as HBase™.

\n

Full cluster deployment

\n

In this scenario, Cryptomate is deployed on a larger scale, handling hundreds or thousands\nof concurrent strategies for many users. The typical use is to provide a hosted trading\nautomation platform.

\n
\"Cryptomate
Cryptomate example deployment: clustered service for multi-user webapp.
\n

The user interface is replaced with a full-blown web application, and most adapters are\nconnected to other infrastructure. For instance, notifications are forwarded to third party\nnotification systems, possibly sending text messages or emails to users, or simply\nupdating their web-page through websockets.

\n

The key point here is horizontal scaling and redundancy at those levels:

\n\n

Note that Cryptomate itself does not cover service supervision. Still, it must be\nsupervisable, so we will be mindful of how it can be run under standard supervision.

\n

Conclusion

\n

This concludes our upfront architecture series. We will do a short recap in the\nnext post.

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