Kubernetes has changed the way organizations build, ship, and scale applications. It offers flexibility and speed, allowing teams to iterate quickly and respond to demand. But that speed introduces complexity. As environments scale and shift constantly, it gets harder to understand what’s running, why it matters, and what it costs. In fact, Gartner forecasts worldwide public cloud end-user spending to total $723 billion in 2025.

 

Teams collect mountains of telemetry. According to Splunk’s The New Rules of Data Management report, 91% of organizations surveyed say their overall spend on data management has increased compared to the previous year. They track system health and uptime, and collect observability data from every corner of the environment But without context, all that data becomes expensive noise. That context is often missing in Kubernetes environments, where resources are short-lived and scaling happens automatically. As a result, teams are left guessing about resource usage, performance bottlenecks, and cost drivers instead of taking action.