Shared dashboard performance monitoring for data teams

The moment this becomes urgent: a data team publishes a set of dashboards to 50 internal users, and within a week the complaints start — 'it's slow', 'it won't load', 'the charts take forever'. The data team has no visibility into which dashboards are slow for which users, whether the problem is query time or rendering time, or whether it's getting worse over time. They're doing triage by Slack message.

This gap exists for a structural reason: BI tools are built to let you create and view dashboards, not to help you operate them at scale. Performance observability is an ops concern, and most BI tools are sold to analysts, not ops teams. Nobody inside a BI vendor has the incentive to build the tooling that would let a data team say 'dashboard X is in the 95th percentile for load time and it's getting worse week over week' — because that kind of visibility might lead customers to question whether they need more licenses or better infrastructure.

What's missing specifically: users complain that 'sharing can get really slow at times' and 'the speed of the dashboard display is very slow' — but these complaints go to the data team as vague noise with no attached diagnostic information. There's no tool that aggregates load times per dashboard, per user segment, or per underlying query, and surfaces trends over time in a way a data team can act on.

This is a business because it solves a problem that gets worse as a company grows. A team with 10 dashboard consumers doesn't need this. A team with 200 does, and the need intensifies as dashboards multiply and user expectations rise. The recurring cost without it is either user trust erosion (people stop using the dashboards) or constant reactive firefighting by the data team.

What to build

Build a monitoring agent that instruments Superset and QuickSight dashboards to log per-dashboard, per-query load times, surfaces a weekly digest to the data team showing which dashboards degraded, and links each slow dashboard directly to the underlying query and dataset size that caused it.

Where to start

Launch exclusively for self-hosted Superset deployments, where instrumentation is straightforward, the user base is technically sophisticated enough to self-install, and there is zero existing vendor support for performance observability — making the need acute and the barrier to adoption low.

The hard part

Instrumenting multiple BI tools without requiring code changes or vendor API access that doesn't exist yet is the core technical constraint — Superset's open-source nature makes it tractable, but QuickSight's closed architecture may require workarounds that are fragile and hard to maintain across API version changes.

How it makes money

Per-seat pricing based on the number of dashboard publishers monitored (not viewers), sold as an annual subscription to the data team budget, with a free tier for teams monitoring fewer than ten dashboards.