I’m uncertain about the best way to integrate Mailgun with my Rails project. Should I rely on background processing via Active Job or opt for a simpler, controller-driven method?
im leaning toward using active job since it helps prevent delays when sending mails, especially if your app scales up. a controller solution is simpler but can bottleneck on mail sending for busy endpoints. pick based on your app size, id say 
Based on my experience integrating Mailgun with a Rails application, I found that using ActiveJob and a background processor like Sidekiq is the most sustainable approach in the long run. While the initial setup may seem more complex compared to a controller-based method, it separates concerns properly and prevents the main thread from being blocked during mail processing. This distinction becomes particularly important as the app scales, reducing the risk of slow response times and improving error handling in asynchronous tasks.
Based on my own experience, I prefer to integrate Mailgun using background processing. I remember when I first tried a controller-driven approach, I ran into performance issues when the email volume increased unexpectedly, and response times suffered. Implementing Active Job with a background processor helped me separate the email sending from the user request cycle, which resulted in a smoother and more scalable system. The initial setup required some additional effort, but the long-term benefits in terms of maintenance and user experience were definitely worth it.
i got a similar question and i fnd that if your app is light and traffic isnt alot, a simple controller solution can be enough. but when scaling and heavy loads hit, background jobs smooth things out. try a load test to see whats best for you.
My experience has shown that setting up Mailgun integration through asynchronous processing yields long-term benefits. I implemented this by establishing dedicated mailers that enqueue jobs designed to handle email delivery, a choice that dampens the risk of response delays and failed attempts, especially during peak loads. This setup allowed for more robust error management and retry mechanisms. Despite an initially steeper learning curve and configuration effort, the eventual scalability and stability improvements outweighed the upfront complexities.