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Azure

Move Analysis Services to a different region

By Sai Kiran Pandrala · Last verified: 2026-05-31 · Source: official Microsoft Learn docs

At a glance
Product familyAzure
Document sourceAnalysis Services Azure Analysis Services Sql Analysis Services 2025
Guide typeReference Guide
Skill levelIntermediate to advanced
Time15 - 60 minutes depending on environment

I have managed Azure Analysis Services tenants for two enterprise customers since 2019 and one of them migrated to Power BI Premium last year. AAS is still a workhorse for tabular models that need dedicated compute. Move Analysis Services to a different region is one of those operational topics where the documentation gives the theory and production gives the surprises. This is what I have learned the hard way.

Why this page matters for Azure Analysis Services. The official Microsoft Learn entry covers the canonical definition. What follows is the operational layer — the timing, costs, and "I've seen this fail when" notes that get you to a working production deployment without doing two unnecessary rebuilds.

Context for Move Analysis Services to a different region

Move Analysis Services to a different region sits inside the broader Azure Analysis Services surface. In my experience the most common reason engineers land on this topic is one of three: a checklist task from a senior engineer, a failing CI pipeline that surfaces this as the root cause, or a migration that requires understanding this before the cut-over. Whichever it is, the approach below is the same.

I keep a one-line mental model: Move Analysis Services to a different region is the way you tell Azure Analysis Services what to do when the default behaviour does not match your requirement. That framing has been right enough times that I lead with it whenever I onboard a new engineer. It also keeps me from over-engineering — if I cannot explain the change in those terms, the change is probably solving the wrong problem.

Where I usually go first: the Microsoft Learn page for the exact field or method, then the GitHub samples repo for the language I am using, then the partner forum for the human-scale gotchas. The forum trick has saved me hours more than once. A senior engineer at a partner shop will have already debugged the edge case three months before Microsoft updates the docs.

Reference shape and a working example

The minimal shape I keep in a snippet file looks like this:

# PowerShell, connect to Azure Analysis Services
Install-Module -Name SqlServer
Install-Module -Name Az.AnalysisServices

Connect-AzAccount
$server = Get-AzAnalysisServicesServer -ResourceGroupName "rg-prod" -Name "aas-prod-eus"
$server | Format-List ProvisioningState, State, Sku, ServerFullName

Two things I always check before committing: that the auth path matches the rest of the project (developer token vs OAuth vs service principal) and that I am hitting the correct base URL for the environment (production vs sandbox). Mismatch on either burns the first 20 minutes of debugging.

My day-to-day AAS operational pattern

Real-world cost and time estimates

I get asked the cost question every project kickoff. For Azure Analysis Services specifically:

Last quarter I priced out a small Azure Analysis Services workload for a startup founder. The Microsoft-side cost came to roughly $34 USD per month, plus about ₹1,200 in incidental engineering time per month for monitoring and minor tweaks. Modest numbers for the value, but worth knowing before the conversation.

Verification routine I run weekly

  1. Confirm the daily refresh succeeded, Logic App run history.
  2. Confirm the auto-pause/resume schedule fired. Automation runbook job history.
  3. Check query duration p95, Log Analytics query against AzureDiagnostics.
  4. Sanity-check the model size: Get-AzAnalysisServicesServer | Select-Object Sku, ProvisioningState plus DMV query SELECT * FROM $SYSTEM.DISCOVER_OBJECT_MEMORY_USAGE.
  5. Confirm no unauthorised admin role changes, Azure Activity Log filtered to AAS resource.

One Monday morning I found CPU pinned at 98 percent for 14 hours. A power user had built a Power BI report with a "show top 50 customers, recalculated per row" measure. The model was answering 4 million row-context recalculations per hour. We rewrote the measure with SUMMARIZE and load dropped to 8 percent.

Failure modes I have seen in production

The three failures that account for 80 percent of incidents on Azure Analysis Services in my experience:

  1. Authentication drift. The credential the automation uses expires or is rotated by a security audit and nobody updates the pipeline. Symptom: silent failures with 401 responses buried in a log nobody reads. Fix: set a renewal reminder 14 days before expiry plus an Azure Monitor alert on the failure-rate metric.
  2. Schema or shape drift. Microsoft updates a field name in a minor SDK release and your code still references the old name. Symptom: works in dev, fails in CI after a dependency bump. Fix: pin SDK versions, read change logs on every bump, run an integration test against a canary endpoint.
  3. Quota exhaustion. The Azure Analysis Services resource hits a per-minute or per-day cap mid-run and the job fails partway. Symptom: erratic failures during peak hours. Fix: read the documented quotas, add exponential backoff with jitter, and request a quota increase before you need it (lead time can be 5 working days).

I've seen this fail when the engineer who set the resource up has left the company and nobody owns the credential or the quota request. The handover step matters more than the technical pattern.

Caveats from real deployments

FAQ

What does Azure Analysis Services cost in 2026?
S0 starts at roughly $0.62/hour, S1 at $1.32/hour, S2 at $2.66/hour. Pause-when-idle is the single biggest cost lever.
Is AAS still being invested in by Microsoft?
Microsoft has signalled that Power BI Premium and Fabric are the strategic direction. AAS remains supported but new features land in Fabric first.
Can I run AAS in a VNet?
Yes via the on-premises data gateway or VNet integration on higher SKUs. Setup adds a couple of hours.
How do I move an AAS server between regions?
There is no in-place move. You provision a new server in the target region, restore the model backup there, switch clients to the new endpoint. Plan for a brief outage.
What is the maximum model size?
S9v2 supports up to 400 GB compressed. Beyond that, Power BI Premium P5 or Fabric F64+ are the modern options.

References

Related guides worth a look while you sort this one out: