A development environment for managing algorithmic trading operations across a distributed Elixir cluster.
Workbench is a development environment for managing algorithmic trading operations across a distributed cluster. It provides tools for real-time order streaming, portfolio tracking, cluster control, and observability specifically designed for quantitative trading workflows. The project brings the productivity benefits of the Elixir and Phoenix ecosystem to financial technology applications.
Quantitative developers, algorithmic traders, and financial technology teams building real-time trading systems who need distributed cluster management and observability tools.
Developers choose Workbench because it provides a specialized, integrated environment for trading operations with the reliability and concurrency benefits of Elixir's BEAM VM. It offers comprehensive observability and control features specifically tailored for algorithmic trading workflows.
From Idea to Execution - Manage your trading operation across a distributed cluster
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Provides live monitoring and management of orders with visual dashboards, as shown in the documentation screenshots for streaming real-time orders.
Enables remote control of trade instances across clusters, supporting scalable trading operations with features like remote control interfaces.
Includes built-in Grafana dashboards for monitoring system health, balances, and operations, offering comprehensive cluster-wide insights.
Leverages Elixir's BEAM VM for high concurrency and reliability, specifically designed for real-time, fault-tolerant trading systems as per the project philosophy.
At version 0.0.18, the project is in early stages, which may lead to instability, breaking changes, and incomplete features as it evolves.
Heavily tied to Elixir and Phoenix, limiting usability for teams not already invested in this tech stack or familiar with functional programming.
Requires generating migrations, configuring multiple endpoints, and potentially using proxies like master_proxy, adding overhead compared to simpler tools.