 When we look at observability before that, we used to talk about, you know, of course, monitoring, logging, phrasing. How have you seen the scope of observability grown beyond the original idea, as you said? I'm not really sure whether I know the original idea of observability, but in my interpretation of observability, I think the progress from making something observable to humans to making systems systematically accessible and observable by other systems is another step in the evolution of automation. I think that's a key takeaway, is you need to think about what are the pieces of information a system needs to provide, you know, in order to automate its operation for example. So look at, let's say you have a Kubernetes cluster, you use that Kubernetes cluster to run databases. So you have several operators and application developers in their application clusters can create a resource, a Postgres resource, and that operator talks to the Kubernetes cluster where the actual database runs and creates a Postgres cluster there, which is basically the NNS data services for Kubernetes that we built. So in that scenario, at some point, the Kubernetes cluster needs to add nodes in order to host new data service instances. So you need an order scaler to do that, otherwise you'd be running out of Kubernetes nodes. So if you think about that, it means the Kubernetes cluster needs to run a piece of software that observes the utilization of the Kubernetes cluster and then also has the authority to create further Kubernetes nodes in order to make room for a pod that has been recently requested. So it's something that comes from within the cluster that then modifies the cluster itself. And that's only possible of observability is there. So I would say that's the kind of second generation of observability that is just a logical next step.