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Cryptocurrency Trading Process Optimization

Azati team helped the customer develop a reliable business utility to optimize the cryptocurrency trading process. The customer had previously created a utility to handle crypto trading but faced challenges with performance and scalability. Azati’s task was to optimize the trading scripts, improve the performance, revamp the features, and release a new version of the CLI tool.

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250-300%

improvement in performance of trading scripts

80-90%

reduction in deployment/setup time with Docker

60-75%

increase in automated trading task throughput

All Technologies Used

Ruby
Ruby
Docker
Docker
PostgreSQL
PostgreSQL
Redis
Redis
ElasticSearch
ElasticSearch

Motivation

The customer needed to optimize the performance of their existing cryptocurrency trading utility and revamp its features. The solution required improving the CLI tool, which lacked a visual interface and scalability, and developing new features to enhance the overall trading process.

Main Challenges

Challenge 01
Minimizing External Dependencies

The customer wanted the Ruby-based utility to use as few third-party libraries as possible, requiring Azati to recreate open-source modules internally while maintaining high quality and reliability.

#1
Challenge 02
Performance and Scalability

The existing CLI tool struggled with fast-paced trading operations and could not efficiently handle multiple requests or integrate trading bots. Azati needed to optimize scripts, revamp business logic, and ensure robust Docker deployment for scalability.

#2
Challenge 03
Complex CLI Interaction

Since the tool had no visual interface, managing numerous commands efficiently was challenging. Azati had to implement an advanced filtering system and TCP server support to handle requests remotely and improve usability.

#3

Our Approach

Code Optimization
Azati engineers streamlined the Ruby codebase, minimized dependencies, and refactored trading scripts to boost performance while preserving compatibility with the customer’s existing trading workflows.
Docker Deployment
The entire CLI tool was containerized in Docker, simplifying deployment, scalability, and maintenance. Users can now launch the tool and its dependencies in under a minute.
Enhanced CLI and TCP Server
The CLI was enhanced with a TCP server handling requests remotely. This allows the CLI client to send commands to Docker instances, improving execution efficiency and freeing local resources.
Trading Bots Integration
Trading bots were integrated to automate operations such as purchasing, selling, and exchanging crypto assets. Business logic was optimized for calculations, data transformations, and algorithm handling.
Advanced Filtering System
An advanced command filtering system was implemented to simplify navigation through multiple CLI commands, improving usability for high-volume trading activities.
Project Management Improvement
The team migrated from Trello to GitHub Boards, streamlining task tracking, bug reporting, and feature assignment, which improved overall development efficiency and collaboration.

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Solution

01

Optimized CLI Tool

A high-performance command-line interface enhanced with a TCP server that forwards user commands to Docker containers, minimizing local processing and improving execution speed. Includes advanced filtering for easier command navigation.
Key capabilities:
  • Remote command handling via TCP server
  • Advanced filtering system for CLI commands
  • Improved execution speed and reliability
02

Trading Bots Integration

Integration of automated trading bots capable of handling multiple exchanges and executing trading strategies with high efficiency. Bots interact seamlessly with the optimized business logic and database connectors.
Key capabilities:
  • Automation of trading strategies
  • Real-time interaction with multiple exchanges
  • Optimized algorithms for price calculations and data transformations
03

Docker Containerization

Complete deployment of the CLI tool inside Docker containers, ensuring fast setup, simplified configuration, and easy scaling across different environments.
Key capabilities:
  • Rapid deployment of the CLI utility
  • Scalable and maintainable infrastructure
  • Isolation of dependencies and system processes
04

Database & Request Handling Modules

Modules responsible for processing incoming requests, connecting to PostgreSQL and Redis databases, parsing CLI strings into machine-readable formats, and executing core business logic for trading operations.
Key capabilities:
  • Efficient database connection and query handling
  • Reliable parsing of CLI commands
  • Execution of optimized business logic
05

Requests Builder & Trading API Connector

Responsible for building requests to external trading APIs and managing interactions between CLI commands, Docker instances, and trading bots for seamless automated operations.
Key capabilities:
  • Simplified API request creation
  • Seamless integration with external trading platforms
  • Reliable execution of trading operations via bots

Business Value

Performance Boost: System optimizations resulted in a 300% improvement in performance, significantly reducing trading times and enabling faster execution of operations.

Enhanced Deployment and Scalability: The integration of Docker containers simplified deployment and improved system flexibility, allowing for scalable and maintainable infrastructure.

Automation and Efficiency: The implementation of an advanced filtering system and integration with trading bots reduced the need for manual intervention, making the trading process more automated and efficient.

Improved Project Management: The transition to GitHub Boards streamlined task tracking and project management, increasing team productivity.

Usability and Future Scalability: The newly released CLI tool with advanced features enhanced usability, while future plans include introducing a web interface for even more accessible user interaction.

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