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Case Studies

Deep dives into real deployments, architecture choices, and measurable outcomes.

ArchitectureDeploymentsOutcomes16 posts

Answer-shaped entry points

Prefer a short decision card before the long note? Start on the Answers hub, then return here for the full case-study path. Cards only cover claims the posts actually make.

What you will find here

  • Topology and control-plane writeups from systems that had to survive CI/CD, private networking, and real entitlement models.
  • Architecture tradeoffs with the decision criteria that mattered after the pilot, not the workshop slide.
  • Migration and parity contracts: NULL versus zero, float pennies, and the checks that kept finance from rejecting the cutover.
  • Platform-scale patterns for Fabric lakehouses, agent apps, and canvas surfaces, including the failure modes that showed up in production.

Posts tagged Case Studies, including newer lakehouse, Direct Lake, and agent-shell writeups from the publishing backlog.

POC public vs MVP private: networking as architecture for agent apps

How to stage agent webapps from a public POC to a private MVP without pretending env files are a network design.

Signing in is not authorization: app access is not agent access

Why enterprise agent webapps need separate control planes for shell sign-in, agent catalog access, and knowledge corpus entitlements, and how Entra app roles on the API make that enforceable.

Canvas apps at platform scale: push work to Dataverse

How to keep canvas apps maintainable at scale by following Microsoft reference guidance: fewer mega-screens, less chatty data access, more Dataverse-side work.

Legacy to lakehouse: semantic parity is the real migration

Why lakehouse migrations fail on NULL versus zero, float pennies, and type rebase settings, and how to treat parity as a contract.

SCD2 is a product question: point-in-time deployed state with MLVs

Explain why location and classification history for measuring points should be SCD2 Materialized Lake Views before anyone builds devices as of reports.

One Fabric lakehouse with schemas vs many lakehouses

How to choose between multiple Fabric lakehouses and a schema-enabled lakehouse for bronze, silver, and gold, including CI/CD and naming fallout.

MLV migration is a program: bronze to silver to gold with gates

Frame hundreds of T-SQL warehouse views moving to MLVs as a phased program with schema-enabled lakehouses, shortcut layouts, and POC gates before bulk conversion.

Refresh drift is a contract break, not a flaky pipeline

Diagnose sales-line style refresh drift as mismatched incremental contracts between notebooks, watermarks, and semantic consumers.

Foundry webapps deploy as identity and egress, not as Node hostnames

Walk through a VNet-integrated container App Service pattern with secretless OBO, managed identity, and private egress to Foundry, Search, and storage.

Pivot once in gold: measurable controls as a flat fact

Replace OUTER APPLY Import-mode checklist pivots with a pre-pivoted gold fact built in PySpark for Direct Lake.

IoT events are facts: model them like service, not like logs

Show why telemetry events belong in gold with contract and service-item enrichment and Direct Lake storage mode for volume.

Shortcuts-only bronze: stop copying what OneLake already holds

Argue that bronze should be a contract of OneLake shortcuts and clean views, not a second physical copy of upstream gold and silver.

When Fabric regressions force literal OneLake URLs, document the workaround

Reframe literal URL required failures as service regressions with validators, promotion playbooks, and support cases - not as eternal architecture dogma.

Bridge keys before dashboards: remodel the device fact

Show why service-device relationships need an explicit bridge/fact remodel before report pages can be trusted.

Gold without a semantic contract is just another table

Argue that device gold tables only become platform assets when unmatched keys, captions, and relationships are explicit in the semantic model.

Automate Your Microsoft Fabric Workloads with Apache Airflow

Why Fabric workloads need an explicit orchestration plane, how to keep Airflow thin while Fabric owns the data work, and which failure modes show up when teams collapse both into one tool.