Infrastructure
Company features > Infrastructure
Overview:
Flowdesk provides a cutting-edge trading infrastructure that handles billions of data points and millions executed orders every day, with more than 100 exchange platforms onboarded.
With a focus on scalability, our infrastructure supports a highly effective quantitative trading model, offering:
Quick deployment of market-making feeds across multiple exchanges
Automated collateral management
Robust monitoring and risk control with comprehensive reporting
Efficient access to liquidity through a single, unified trading model.
As a technology provider, we bring together traders and developers to create an advanced algo trading infrastructure. Our setup is built on trusted technologies such as Google Cloud, NATS, and Kubernetes, and managed with Terraform. To ensure business continuity, each virtual machine is duplicated multiple times. We also have a multi-cluster infrastructure spanning Europe, Japan, and the US, which reduces latency with exchanges by bringing clusters closer to the exchange locations.
Key Features:
Multi-Cluster Infrastructure
The Multi-Cluster Infrastructure is a key aspect of Flowdesk's trading setup. It refers to the deployment of multiple clusters, or groups of computing resources, in different geographic locations. In the case of Flowdesk, these clusters are located in Europe, Japan, and the US.
The primary purpose of the Multi-Cluster Infrastructure is to reduce latency, or the delay in the transmission of data, with the exchanges. By bringing the clusters closer to the exchange locations, Flowdesk is able to minimize the time it takes for data to travel between the trading infrastructure and the exchanges. This results in faster, more reliable market making and can have a significant impact on the performance and profitability of algorithmic trading strategies.
In addition to reducing latency, the Multi-Cluster Infrastructure also provides other benefits. For example, it can help improve reliability and resilience by allowing data to be automatically routed to different clusters in the event of a failure or disruption. It also enables more flexible and efficient resource utilization, as different clusters can be sized and configured to meet specific needs and requirements.
Technologies
Flowdesk uses a range of technologies to build its trading infrastructure. These technologies are designed to provide scalability, reliability, and efficiency, and to support the development and execution of algorithmic trading strategies. Some of the key technologies used by Flowdesk include Redis, NATS, Golang and Node.js for the backend, Typescript and React JS for the frontend, along with Terraform, Kubernetes, and Google Cloud for Infrastructure.
By leveraging these technologies, Flowdesk is able to provide a scalable, flexible, and highly effective trading infrastructure that is optimized for trading success. The use of cloud computing platforms, in particular, enables Flowdesk to quickly and easily deploy and scale its infrastructure to meet the needs of its clients.
Backend | Frontend | Devops | |||
Redis | TypeScript | Terraform | |||
Node.js | React JS | Kubernetes | |||
NATS | FluxCD | ||||
Python | Google Cloud Platform | ||||
Go | GitHub | ||||
Docker |
Business continuity
Business continuity is an important aspect of Flowdesk's trading infrastructure. It refers to the ability of the infrastructure to continue functioning even in the event of an unexpected interruption or failure.
To ensure business continuity, Flowdesk has implemented several good practices and measures including high-availability of the critical systems, automated backups, wide monitoring and alerting coverage, chaos engineering, and auto-remediation.
This approach helps to minimize the risk of downtime and ensures that algorithmic trading strategies can continue to execute even in the event of a failure.
These measures, combined with the Multi-Cluster Infrastructure and the use of cloud computing technologies, help to ensure that Flowdesk's trading infrastructure is highly reliable and resilient.
Table of key features
Feature | Description |
Trading Infrastructure | Scalable and effective, handling billions of data points and millions of executed orders per day with 100+ exchange platforms onboarded |
Scalable Quantitative Trading Model | Quick deployment of market-making feeds, automated collateral management, monitoring and risk control, and efficient access to liquidity |
Technologies | Built on Google Cloud, IBM, Kubernetes, and managed with Terraform |
Business Continuity | Virtual machines are duplicated multiple times to ensure the activity can still go on if one is down |
Multi-Cluster Infrastructure | Reduces latency with exchanges by bringing clusters closer to the exchange locations |
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