Operations | Monitoring | ITSM | DevOps | Cloud

We’ll always remember 2025 as the year AI code assistants went big. Copilot, Cursor, Claude, Windsurf, whatever. Developers went from mistrusting these tools, to being expected to turn over much of their coding labor to them. Even if, according to an extensive Stack Overflow survey, only 3 percent of professional developers say they ‘highly trust’ AI coding tools.

We’ve added three new API endpoints to help you explore and triage individual error occurrences in your applications. These endpoints make it easy to: Whether you’re automating incident workflows, enriching alerts, or powering custom dashboards, these endpoints give you direct access to the data you need.

GraphQL isn’t just another API protocol—it’s a new layer of abstraction. It collapsed dozens of REST endpoints into one flexible interface where clients decide what data to fetch and how deep to go. That freedom is a gift for front-end teams and a headache for anyone tasked with reliability. Traditional monitoring doesn’t work here. A REST endpoint can be pinged for uptime.

When developers try to build realistic mocks and automated tests from production network traffic, the real challenge isn’t just in the capturing—it’s in the data manipulation. Raw traffic is a chaotic sea of patterns, dynamic tokens, environment-specific secrets, and tangled dependencies that seem impossible to untangle by hand. Over my two decades of building these sytems, I learned that solving this problem requires more than brute-force parsing or ad hoc scripts.

There are only a few companies that successfully invest in actively monitoring real user flows in production. I’ve been puzzled by the state of the art for many years, because I’m an anxious developer that always needs to know that production is “all right”. How can it be okay for all of us to wait for error logs, thrown exceptions or customer complains to learn about production issues?

In Part One, we discussed how QA debt builds silently over time — causing slower releases, late-night firefights, and unpredictable test cycles. The next step is understanding how much debt you have and where it hides. This post goes deeper into measuring QA debt — what to track, how to collect data, and how to use those insights to create a sustainable plan for improvement.

Last month, we introduced the StatusGator API v3, a complete overhaul of our API designed to give developers more flexibility, an improved data model, and deeper integration options for monitoring the status of hundreds of services. Today, we’re excited to share three major additions to v3: the Board History API, Custom Monitors API, and Status Page Subscribers API.