Operations | Monitoring | ITSM | DevOps | Cloud

Over the past three decades, Ruby has assumed a pivotal role in the modern web stack and become a fixture in the tool kits of countless DevOps and platform teams. Today, it is a driving force in contemporary application development, testing, automation, and CI/CD. For this blog post, we used data from our always-on continuous profiling of more than 3,000 real-world services from hundreds of organizations to track trends in Ruby usage and performance.

Most teams picture incident response as a linear sprint from alert to resolution. A notification appears, an analyst pivots across screens, a decision gets made, and the workflow moves on. It works, but it is mechanical, tiring, and fragile. Graylog 7.0 aims for something more impactful. Guided remediation gives analysts clarity during the moments when pressure rises and context usually scatters. It takes raw detection data and turns it into a clear path forward. No theatrics.

Introducing Kentik AI Advisor, a powerful new AI designed to deeply understand your network, reason through complex issues, and deliver clear, actionable guidance for designing, operating, and protecting your networks. By autonomously querying Kentik’s rich telemetry and tools, it explains what’s happening, why it matters, and what to do next — from troubleshooting and capacity planning to cost optimization and risk mitigation.

‍ 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.

Production errors can feel overwhelming. Your Rollbar dashboard is filling up with alerts, your team is scrambling to understand what needs immediate attention, and critical revenue-impacting issues might be buried among less urgent problems. Sound familiar? In this post, I'll walk you through a workflow that transforms production error chaos into organized, prioritized action items. We'll cover everything from analyzing Rollbar errors to creating properly linked Linear tickets.

Another day, another massive Internet disruption, and this time it’s Cloudflare taking huge parts of the Internet offline. This incident is not an anomaly. It is part of a recurring pattern that has become standard in digital infrastructure. We have reached an inflection point in digital operations. Outages at major cloud and content delivery network (CDN) providers are now expected. The only real uncertainty is when it will happen next.

Developers don’t need another “run this tool, stare at a number, and feel bad about it” website. So we built something different. WebVitals helps you analyze, optimize, and ship faster websites, all in one place. Built by the same folks who obsess over stack traces and slow queries, it connects the dots between performance metrics and what’s actually slowing your users down. In one place, you can.

Dashboards and alerts can tell you something’s wrong, but they don’t immediately tell you why. A red indicator or synthetic test failure prompts detective work. You flip between dashboards, timestamps, and logs, trying to line up what the check saw with what the system did. Now imagine your monitoring could explain itself by sending traces directly into your OpenTelemetry (OTel) backend.

Distributed tracing tracks how a single request moves across multiple microservices, helping teams see the entire execution path end to end. In modern architectures where dozens of services interact, it becomes difficult to understand where latency starts, why bottlenecks appear, and which component breaks under load. Traditional monitoring only shows isolated metrics. Distributed tracing connects those dots.