Operations | Monitoring | ITSM | DevOps | Cloud

Throughput is one of the most foundational metrics in application performance monitoring. It tells you how many requests your app is handling over time and offers a direct look at system load, responsiveness, and scalability. But throughput rarely speaks for itself. The key is knowing how to interpret it, and when to act. In this post, we’ll look at how throughput works in the real world: what healthy looks like, what broken looks like, and what lives in between.

Your app feels slow, users complain… but your dashboard says response time is totally fine! But the real pain is revealed when looking at percentiles. In this post, we’ll break down why the 95th percentile response time metric is useful, plus how to work with it in practice. ‍

‍ Like many developers, I’ve spent the last year adjusting to a world where I’m spending more keystrokes arguing, or, “explaining” to an agent the code I’d like to be written. No longer must we toil, writing every line code by hand like our great grandparents probably did.

Once, when I was a very junior developer, I was discussing a bug with a very senior developer (let's call him Burt). Satisfied with the fix, I said something like "oh, that was a great bug". He looked at me as if his eyes were going to fall out of his head. Clearly, this enraged him. He briefly went off about how there are no great bugs, there are only bugs to squash – and that’s all.

Rechain is a SaaS Product Lifecycle Management (PLM) platform built with Ruby on Rails for fashion brands which helps modern apparel teams manage design, production, and supply chain workflows from one intuitive, cloud-based solution. ‍

We’re excited to introduce the Scout Monitoring MCP Server — a new way to bring AI-native monitoring directly into your coding assistant. Instead of flipping between dashboards and logs, the MCP (Model Context Protocol) server surfaces performance data, errors, and slow endpoints right where you work. Ask plain-language questions like “show me the latest five errors” and get answers grounded in live telemetry. You can even let your coding assistant propose and push fixes!

Before we talk about AI-native monitoring, let’s take a quick step back to make sure everyone is on the same page. In software engineering, monitoring is the continuous collection and analysis of data about a system’s health, performance, and behavior. Tools like Scout Monitoring, Datadog, and New Relic traditionally track server uptime, request latency, error rates, and database performance.

You’ve built something, it’s live, and users are starting to show up. Maybe you programmed it from scratch, used a tool, or vibe-coded it into existence. No matter how it came to be, the fact that you’ve got users is great! But here’s a question every new developer must eventually ask: how do I know when my site is actually failing? ‍ The thing is, these failures aren’t always obvious.

If you just want the gist without all the scroll.

For more than a decade, Cookpad, a global platform for recipe sharing and search, has relied on APM tools to monitor critical application performance metrics, like server response times and resource usage. When their previous APM tool became too expensive after price increases, they needed to find a new solution that could check all of their boxes.