Observability data isn’t typically blended with the data that your Analysts are working with. These data types are typically stored in entirely separate databases, and interrogated through different tools.

But that needn’t be the case. At Grafana Labs we’ve started blending this data together, to answer questions that we or our customers have, such as: - How much revenue did that downtime cost me? - How did latency impact on sales last Black Friday? - Which customers were impacted by that incident, and which ones are the highest priority to follow up with?

The FOSS projects we’re combining to get there are: - The LGTM stack (github.com/grafana) for Observability - Cube core (cube.dev/docs/product/getting-started/core) for Semantic Layer - dbt core (github.com/dbt-labs/dbt-core) for transforming SQL data - Grafana itself to blend, visualise and even alert on the end-result

During this talk I’ll describe how you too can fit these pieces together and use them to answer similar questions for your own context.