OMG Elixir

As developers, we often face scenarios where we need to push the boundaries of performance and efficiency. One such case is decoding complex WebSocket messages in real-time financial applications. In this blog post, we'll explore how to leverage Rust's performance within an Elixir application to decode WebSocket messages from Zerodha's Kite Connect API. Why Integrate Elixir with Rust? Elixir is known for its concurrency and fault-tolerance, making it an excellent choice for building scalable applications. However, Rust offers unmatched performance and memory safety, making it ideal for CPU-intensive tasks like decoding binary WebSocket messages. By integrating Rust with Elixir, we can achieve the best of both worlds. The Challenge: Decoding Kite Connect WebSocket Messages Zerodha's Kite Connect API provides market data via WebSocket in binary format. These messages need to be decoded efficiently to be useful. While Elixir is powerful, decoding binary data is an area whe...

For advanced Elixir developers, handling massive concurrency involves not just understanding the basics of GenServers, Tasks, and Supervisors, but also effectively utilizing more complex patterns and strategies to optimize performance and ensure fault tolerance. In this blog post, we'll dive deeper into advanced techniques and provide a practical example involving a distributed, fault-tolerant system. Practical Example: Distributed Web Crawler We'll build a distributed web crawler that can handle massive concurrency by distributing tasks across multiple nodes, dynamically supervising crawling processes, and implementing rate limiting to control the crawling rate. In this example, we will build a distributed web crawler that simulates handling massive concurrency and backpressure. To achieve this, we will: Generate 100 unique API URLs that will be processed by our system. Create an API within the application that simulates slow responses using :timer.sleep to introduce artificia...