Operations | Monitoring | ITSM | DevOps | Cloud

When an error appears in production, the hardest part often isn’t seeing what broke. It’s understanding why. That’s why we built Root Cause Analysis (RCA). It helps connect the dots between an error and its likely cause, so you can spend less time investigating and more time moving forward. Until now, RCA was only available through plans that included AI credits. Starting today, free plan users can purchase an AI credit subscription and use RCA without changing plans.

Every few months a new "we migrated off Spring Boot" post washes across r/java or DZone. The numbers are always impressive. 60% memory reduction, 85% faster startup, cloud bill cut in half. The comments are always full of developers convinced they should be doing the same thing. Is Spring Boot really that bad now? I decided to do my own research. I read every credible public migration case study I could find. I ran benchmarks. I built the internal business case for switching two of our services.

Your version and deploy health data no longer lives on separate pages. Versions and Deploys are now Dashboard cards, visible by default the next time you open Rollbar. Errors, versions, and deploys in one view, no more tab-hopping to piece together release health.

You’re comparing error monitoring tools. You’ve narrowed it down to two or three options. Now you need to know what this actually costs before you bring it to your team. Here’s what Rollbar costs, what’s included at each tier, and how it compares to Sentry and Datadog on pricing. No sales pitch, just the math.

You know the drill. An error fires, you get the stack trace, and then you spend the next 45 minutes tracing it backward through four services, two config files, and a deploy that happened three hours ago. You eventually find the root cause, but the path to get there was manual, slow, and entirely dependent on how well you already knew the codebase. We built AI-powered root cause analysis (RCA) for that kind of slog.

Every app breaks eventually. A button stops working. A checkout flow throws an exception. An API returns a 500 error at 2 AM on a Saturday. The question isn't whether your app will have bugs; it's whether you'll find out before your users do. That's exactly what error tracking is for.

If you've ever fixed a bug only to watch it come back two weeks later, you already understand why root cause analysis matters. Patching symptoms feels productive - it's not. Getting to the actual cause is what prevents the same issue from eating your team's time over and over again. This guide covers everything you need to know about root cause analysis (RCA) in software testing: what it is, how to do it, which tools help, and where AI is taking it next.

Look, if you're starting a new Java web project in 2026, you should probably just use Spring Boot. With 14.7% usage in the 2025 Stack Overflow Developer Survey and a 53.7% admiration score among all web frameworks, it remains the default choice for modern Java web development. It has the largest ecosystem, best documentation, most active community, and strongest cloud-native support—now enhanced with built-in AI capabilities through Spring AI.

The best tool to track, analyze, and manage errors at scale? Rollbar tops our list.

Three frameworks dominate Python backend development in 2026: Django, FastAPI, and Flask. This guide helps you choose between them (plus specialized alternatives like Falcon, Tornado, and Litestar) using a simple decision tree. Answer three questions about your project, understand each framework's strengths, and pick the right tool for your needs.