These days, customers expect applications to feel instant. It doesn’t matter whether they’re working with thousands of records or millions. They expect graphs to load quickly, chat to feel real-time, and attachments to appear without hesitation. Ruby on Rails is fast out of the box, but as an application grows, small design decisions start to compound. A few extra queries here, an unbounded background job there, and before you know it, the app slows down.
BigBinary has been working with Ruby on Rails for over 14 years, and performance work has been a constant theme. Sometimes it’s a classic N+1 query. Sometimes Sidekiq is configured in a way that creates bottlenecks instead of throughput. Sometimes Redis caching is doing more harm than good—causing thundering herds, stale data problems, or wasted memory without improving real-world speed.
We’ve also seen many teams try to “buy” their way out of performance problems by throwing more compute at them. That can mask symptoms for a while, but it usually turns into an expensive habit. You end up paying more each month while the underlying inefficiencies continue to grow— and eventually the same problems show up again at a higher scale.
Our approach starts with measurement, not guesswork. We profile the application in production-like conditions, look at real request traces, and identify what’s actually slow: database queries, view rendering, external API calls, background jobs, or asset delivery. From there, we focus on changes that move the needle for end users, not micro-optimizations that only look good on paper.
A lot of performance wins come from improving data access patterns. We tune queries, add the right indexes, remove unnecessary joins, and reduce repeated work through eager loading and smarter caching. We also pay attention to how data flows through the system—because the fastest query is the one you never run.
Background processing is another common source of “why is the app slow?” pain. We help teams make jobs predictable and safe: right-sized concurrency, sensible queues, idempotent retries, and visibility into failures and latency. Done well, Sidekiq becomes a lever for speed and reliability rather than a mysterious box that occasionally catches fire.
We also look beyond code. Caching strategy, CDN configuration, file storage patterns, and observability setup can make or break performance at scale. The goal is to create a system that stays fast as the product evolves—where you can spot regressions early, understand what changed, and fix issues before customers feel them.
Performance work shouldn’t be a one-time rescue mission. We aim to leave you with a faster application and a clearer toolkit: dashboards, alerts, and practical guidelines so future features don’t quietly undo the gains. The result is an app that feels snappy to users, costs less to run, and gives your team confidence as you grow.
Please checkout our scaling Rails series of blogs where we have discussed in depth all the parameters that can be tuned to make an application perform and scale.