Refresh, ingestion, and runtime performance notes.
View All Tags
Canvas is wonderful until one screen becomes a distributed system: nested galleries, OnStart fan-out, and business rules living in Power Fx because it was faster.
Microsoft's own performance reference architectures push a clear direction. Move heavy work toward Dataverse and keep screens focused.
Figure 1. Optimize canvas apps with platform-aligned architecture. Source: Microsoft Learn: optimize canvas app performance.
Materialized Lake View runs paste warning floods that mention native execution engine fallbacks. Teams panic-rewrite Spark SQL to chase every line. Meanwhile the DAG's wall-clock still hides in one slow node nobody measured.
Measure first. Pasted warnings include Delta and MLV metadata internals you cannot and need not remove. Wall-clock attribution beats fear-driven rewrites. Fix the few fallbacks that move latency. Ignore the rest deliberately. Document accepted warnings so on-call does not thrash. Pair with per-view notebooks so slow nodes are isolatable.
Figure 1. Attribute MLV time with job details and DAG reality. Do not treat every NEE warning as a rewrite mandate. Source: Microsoft Learn: Spark detail monitoring.
Nine warehouse views timing out usually means two trunks and seven dependents. Teams that rewrite every leaf, or jump straight to a new platform, often miss the cheap win: materialize the consolidations everything else hangs from.
Use a layered playbook. Drop orphans. Apply cheap predicate and join rewrites. Then materialize the two or three heavy consolidations. Measure with the same harness before and after. Document what is a view versus a managed table so CI/CD stays honest.
Figure 1. When dependents time out, materialize the trunk consolidations first instead of rewriting every leaf view. Source: Microsoft Learn: data warehousing in Fabric.
Figure 2. Measure with the same harness before and after. Document view versus managed table so CI/CD stays honest. Source: Microsoft Learn: data warehousing in Fabric.