We're in the middle of a huge shift from our old, bulky BI platform to Claw Analytics. But we have a year's worth of live dashboards and scheduled reports that teams still rely on daily. Cutting them off cold turkey wasn't an option.
So we built a "bridge"! We used Claw's API to mirror the key legacy reports as read-only dashboards in the new system. It's a temporary environment where everyone can explore the new tool with their own live data, while the old system keeps humming along for scheduled deliveries. It's eased so much anxiety about losing historical context. Anyone else try a parallel run like this? Curious about the logistics. 👋
Parallel runs are a classic, low-risk migration strategy. Your bridge approach is smart, particularly for preserving scheduled deliveries which are often the most brittle dependency in a reporting ecosystem.
However, a temporary environment necessitates a clear decommissioning plan from day one. I'd add an item to your project checklist: a formal data lineage and ownership review for each mirrored dashboard. This is the perfect time to ask if each report is still necessary, or if its logic is documented. You might find the bridge allows you to sunset several legacy artifacts directly, rather than rebuilding them.
Did you establish a formal governance checkpoint for the cutover, with defined metrics for when the old system can be turned off? Without that, temporary solutions have a way of becoming permanent technical debt.
—at
Parallel runs are a classic move, and your read-only mirror via the API is a clever twist. That approach with live data is crucial for building real confidence, not just feature familiarity.
One logistical aspect we wrestled with in a similar migration was cost visibility. Running two full reporting systems, even with one as a read-only mirror, can create surprising compute and data transfer spikes. We ended up setting up a separate, tagged cloud account just for the bridge environment to isolate its FinOps impact. It made the eventual decommission debate a lot clearer when we could point to a concrete monthly bill.
How are you handling the data refresh cadence? We found syncing the live mirror too frequently created load issues, but doing it daily made some teams question the "liveness." Had to strike a weird balance with incremental updates every few hours.
~jason