Operations | Monitoring | ITSM | DevOps | Cloud

Today, we are taking a break from your regularly scheduled technical programming to talk about support. Here at Scout, we consider support one of our differentiators, and even as we adopt AI as a human multiplier behind the scenes, we are committed to keeping it real on the human-interaction side. It will be a long time, if ever, that you reach out to us and get a response from an AI agent. Would it be cheaper? Sure, but it isn’t up to our standards, and we won’t compromise on that.

Most teams triage errors the same way. Check the error tracker in the morning, skim the stack traces, pick the ones that look urgent, start investigating. The rest pile up. By the time anyone gets to the long tail of production errors, the context is stale and the motivation is gone. What if that first pass happened automatically? We’ve been experimenting with a workflow that connects Scout’s error data to AI assistants through our MCP server.

If you’ve spent any time in developer tooling lately, you’ve probably noticed a pattern: every product is rushing to add a chatbot, an AI summary, or some kind of “magic” button. We get it — it’s tempting. But at Scout, we’ve been deliberately taking a different approach. Instead of building AI into our product first, we’ve focused on making Scout’s data accessible to the AI tools you’re already using.

Elixir’s “let it crash” philosophy is one of the best ideas in modern software design. Supervisors restart failed processes, the system self-heals, and life goes on. It’s like having a really good immune system. The problem is that a really good immune system can also hide chronic conditions. A GenServer crashing and restarting is working as designed.

Phoenix LiveView is one of those technologies that feels like cheating. You get rich, interactive UIs without writing JavaScript, and the server handles the state. It’s elegant. But that elegance comes with a trade-off that’s easy to forget: all that interactivity runs on your server.

Rails applications have a specific set of performance challenges that make monitoring genuinely useful rather than just box-checking. ActiveRecord is convenient to use and also convenient to accidentally write N+1 queries with. Memory bloat in long-running processes, particularly when Sidekiq or Action Cable is involved, is a recurring production problem for a lot of teams. Background job performance tends to degrade quietly until it becomes noticeable.

Last updated: March 2026 Python applications built on Django, Flask, FastAPI, and other frameworks have the same monitoring needs as applications built in any other language: you want to know which endpoints are slow, why the database is getting hammered, what errors are firing in production, and ideally all of that in a form that does not require three separate tools to reconstruct a single incident.

The error monitoring scene has changed a ton over the past few years. We've gone from basic exception tracking to fully integrated platforms that correlate errors with performance metrics and logs. We’ve even got AI-powered debugging! But in the midst of the AI explosion, some things remain unchanged and most teams are still drowning in data with little actionability.

With modern tooling and agentic coding assistants, straightforward bugs are almost a relief. If a test can catch it, or a user can reproduce it, chances are you can squash it quickly. The harder category — and the one worth writing about — are the bugs where everything looks correct. Your code runs, no exceptions are thrown, your debug statements confirm the right functions fire at the right times, and yet nothing works.

A repository for this article can be found here.‍ When most developers think about request tracing, they picture instrumentation hooks inside familiar libraries. This allows us to track familiar metrics we see in application performance monitoring (APM) tools such as the duration of an HTTP call or how long a database query takes. But what if you could go deeper and instrument your own Ruby code automatically, without sprinkling timing calls everywhere?