Performance Boost
System optimizations resulted in a 300% improvement in performance, significantly reducing trading times and enabling faster execution of operations.
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.
improvement in performance of trading scripts
reduction in deployment/setup time with Docker
increase in automated trading task throughput
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.
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.
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.
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.
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.
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.
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 were integrated to automate operations such as purchasing, selling, and exchanging crypto assets. Business logic was optimized for calculations, data transformations, and algorithm handling.
An advanced command filtering system was implemented to simplify navigation through multiple CLI commands, improving usability for high-volume trading activities.
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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Schedule a callA 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.
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.
Complete deployment of the CLI tool inside Docker containers, ensuring fast setup, simplified configuration, and easy scaling across different environments.
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.
Responsible for building requests to external trading APIs and managing interactions between CLI commands, Docker instances, and trading bots for seamless automated operations.
System optimizations resulted in a 300% improvement in performance, significantly reducing trading times and enabling faster execution of operations.
The integration of Docker containers simplified deployment and improved system flexibility, allowing for scalable and maintainable infrastructure.
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.
The transition to GitHub Boards streamlined task tracking and project management, increasing team productivity.
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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