DevOps Observability

There are different ways of approaching these, but we typically think of them as data quality, data kind of ingestion. And then the kind of freshness, the kind of like does a stream happen. Does a stream happen at the moment in production because your system might be down. Each of these have different requirements around operational aspects. So if you were talking about data freshness, people want to know immediately. You take the extreme of DevOps and you are you detected you alert customer right away. Another one is outliers. We see a lot of use cases where people deploy new model architecture and then the latency increases or sometimes the data upstream changes. Then the destination for this at the moment