An explanation of observability that highlights the role observability data play in supporting the active role of SREs as they reduce toil, improve uptime, and judiciously consume the error budget.

Interest in observability is at an all-time high. When we attended KubeCon in Los Angeles in October, observability and security were everywhere—in conversations with attendees and other vendors, during sessions, and in messaging at booths—indicating that there’s still an unmet need. In fact, Gartner declared that observability is at the ‘peak of inflated expectations' in a recent Hype Cycle report.

In 2021, any time that you access any kind of web service, whether it be via a website or app, chances are high that the backend is running on Kubernetes. Hundreds of thousands of organizations rely on Kubernetes to power and manage their mission critical services every day, and the reliability and scalability benefits offered by Kubernetes have been felt across the industry.

Have you ever deep dived into the sea of your tracing data, but wanted additional context around your underlying system? For instance, it may be easy to see when/where certain users are experiencing latency, but what if you needed to know what garbage collection is mucking up the place or which allocated memory is taking a beating? Imagine having a complete visual on how an application is performing when you need it, without having to manually dig through logs and multiple UI screens.