OneLake Shortcuts Are Dependencies: Inventory Them Before Scale
Treat every OneLake shortcut as a cross-team dependency: placement, identity, write paths, environment variables and a REST inventory of what points where.
Thoughts on data engineering, cloud architecture, and technology. 2205 articles and counting.
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Treat every OneLake shortcut as a cross-team dependency: placement, identity, write paths, environment variables and a REST inventory of what points where.
Why slow Fabric silver loads often trace back to the raw zone: landing layout, header checks, small files and bronze table maintenance, with PySpark examples.
Set a latency budget per user journey, then let it choose the Azure OpenAI deployment tier, model and reasoning effort you actually pay for.
How to cut an inherited data quality rule set down to the checks that change decisions, using failure history, ownership and an explicit retirement path.
A tool policy nobody tests is a comment. How to assert agent tool lists and approvals in CI, then gate tool use on a golden set of scenarios.
Make retrieval-first a team rule: an owned question set, a side-by-side index comparison on Azure AI Search, and a gate that fails on lost answers.
Most eval sets only ask questions the documents can answer. Add unanswerable, false-premise and stale-context cases, each with an expected behaviour.
Every Foundry model deployment has a version upgrade policy, and the default swaps your model at retirement. How to choose, audit and run model changes safely.
Use KQL baselines, week-over-week comparison and diffpatterns in an Eventhouse to tell a meaningful operational change from ordinary noise, and to explain it.
How to stop metric drift in Fabric by giving every metric one home layer and one named owner, then enforcing both rules with schemas, grants and versions.
How dependency conditions decide a Fabric pipeline's final status, why try-catch hides failures, and how to log, alert and still fail the run honestly.
How to stop Fabric workspace and item sprawl before it starts: lifecycle states, domains, tags, endorsement, retention settings and a weekly hygiene audit.
Why I keep a library of deliberately broken raw files for every Fabric bronze-to-silver transform, and how to run them as plain PySpark tests before release.
Input and output tokens cost and delay answers differently, so split latency into first-token and generation time before trimming anything.
Why every data quality incident should produce two pieces of work, a containment action and a root-cause fix, and how to run both on a Fabric lakehouse.
Agents get confused when workflow state lives in the chat transcript. Four patterns for typed state, fresh context and code-owned transitions.
The semantic ranker only reorders the top 50 results. A with-and-without test on a labelled set shows which RAG queries it rescues and which it just slows.
Treat answer quality like availability: define a good answer, agree a target with the product owner, and let the error budget decide when changes stop.
Foundry Agent Service went GA in mid-March 2026, but monitoring and tracing are still preview. What's governed now, and the controls I'd add first.
How to design Fabric Activator and KQL queryset alerts that fire on transitions, carry an owner and a next step, and stop teams muting the channel.
How I design an analyst-facing schema in Fabric Data Warehouse: views as the contract, permissions scoped to it, and SQL checks that catch breaks first.
How to design Fabric Copy jobs and copy activities so a failed, partial or repeated copy never leaves duplicates, gaps or a watermark that moved too far.
Why adding people as Fabric workspace Contributors is the access shortcut that erodes OneLake boundaries, and a faster pattern that keeps them intact.
A table contract is half the job: assigning owners per layer, collapsing load outcomes to three, and mapping Fabric pipeline failures to runbooks.