Rate limiting is a crucial practice for managing client requests to a system, especially for APIs and consumer-facing applications, to prevent overloading and potential abuse. While APIs primarily use rate limiting to manage server load by restricting the number of requests a client can make, client-facing applications require a different approach due to their human interaction, often relying on IP addresses or session cookies for rate limiting. This helps prevent denial-of-service attacks and abusive behaviors such as credential stuffing or mass account creation, often seen in login or signup endpoints. Two primary algorithms—throttling and fail-to-ban—are employed to enforce rate limits, with throttling setting a cap on actions per time unit and fail-to-ban imposing longer bans after limit breaches. Implementing effective rate limits involves testing policies through historical analysis or dry runs, ensuring they balance security and user experience. The blog post illustrates Felt's use of PlugAttack in Elixir to apply these strategies, highlighting the importance of maintaining service health and security while inviting interested individuals to join their team.