Keep the lesson for the next incident
Document decision and widget dependencies
List the first useful decision, required widgets, optional context, filters, time range, dataset shape, and readiness definition. Explain which widget or shared interval dominated cost. Include empty, partial, and error behavior so a performance change cannot redefine a complete dashboard silently.
Keep a widget-focused review case
Preserve a repeatable dashboard journey that measures first decision, widget completion, refresh, filter changes, and larger data. Define which values, labels, ranges, and links must remain correct. Assign an owner to review the case when a widget or aggregation changes.
Recheck after dashboard growth
Run the representative cases after adding widgets, filters, time ranges, queries, shared reads, or client transformations. Compare per-widget and shared cost again. Add a separate state when a new dashboard supports a different decision, rather than hiding unrelated dependencies in one total.
What to carry forward
The learning record should retain decision dependencies, widget boundaries, data assumptions, refresh contract, and recurrence trigger. It is complete when future work can measure the first useful context, recognize optional cost, and verify that faster loading still supports the dashboard's actual decision.
Keep the decision with the work.
Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.
Create an account See the product workflow