Since its early startup beginnings in Amsterdam, Booking.com has redefined the travel industry, establishing itself as a premier platform for millions of travelers worldwide. With over 28 million accommodation listings and a staggering 1.5 million room nights booked every day, Booking.com operates on a scale that demands a robust and constantly monitored infrastructure.

This week, security researchers at Wiz published a report about an internal database at DeepSeek being exposed to the internet. This kind of security risk is surprisingly common and can affect any company. The only way to prevent it is through continuous monitoring. But in modern infrastructures, services can be exposed in many different ways, making detection tricky. At Coroot, we realized that the telemetry data we already collect can help identify these risks — without requiring any extra setup.

Transform your organization's observability strategy with open standards and simplified data collection Modern organizations face an unprecedented observability challenge. As systems grow more complex and distributed, traditional monitoring approaches are struggling to keep pace. With data volumes doubling every two years and systems spanning multiple clouds and technologies, organizations need a new approach to maintain visibility into their operations.

For years, Fender Musical Instruments has been synonymous with iconic guitars and amplifiers. But in recent years, the company has expanded its legacy into the digital realm, offering tools like Fender Play, an innovative learning platform for aspiring musicians. Behind this digital evolution lies a focus on delivering exceptional user experiences for its consumer-facing applications—a mission supported by Honeycomb for Frontend Observability.

AI is now a go-to tool for everything from writing to coding. Modern LLMs are so powerful that, with the right prompt and a few adjustments, they can handle tasks almost effortlessly. At Coroot, we’ve been experimenting with AI for observability. Our goal is to make it useful in the final stage of troubleshooting—when we’ve already identified which service is causing issues, like Postgres, but finding the exact root cause is still tricky due to the many possible scenarios.

In today's digital landscape, security and observability teams face an unprecedented challenge: managing massive volumes of data while maintaining both performance and cost-effectiveness. As organizations generate more data than ever before, the traditional approach of storing everything in high-performance, expensive systems is becoming unsustainable. How will your team evolve how it manages and uses telemetry data across the enterprise?

We recently worked on an RFP for a customer whose primary driver was compliance with the new Digital Operational Resilience Act (DORA) regulations. The project aimed to make financial services more reliable and secure, protecting both consumers and the technology provider. Helping with this RFP was a rewarding learning experience due to this effort’s high priority and the key challenges faced by this organization.

In the realm of modern software development practices, observability is no longer an optional add-on. It is a mission-critical capability. Like how control theory revolutionized industrial systems, and quality assurance redefined manufacturing processes, observability transforms the software systems and their development processes in many ways inspired by the brick-and-mortar industries. This post explores the best practices in modern observability to help you leverage its full potential.

Back in Alerts Are Fundamentally Messy, I made the point that the events we monitor are often fuzzy and uncertain. To make a distinction between what is valid or invalid as an event, context is needed, and since context doesn’t tend to exist within a metric, humans go around and validate alerts to add it. As such, humans are part of the alerting loop, and alerts can be framed as devices used to redirect our attention. In this post, I want to drive this concept a bit further.

There are a limited number of investments that a team can make in any given year and it can be daunting to choose the “right” ones. In R&D, there is always more to do. There is always more to research, design, build, fix, maintain, and improve. Spread across multiple domains, the possibilities multiply: we’re spoiled for choice—and, while inspiring, the breadth of possible investment areas can be overwhelming.