Microsoft introduced Azure canvases for GitHub Copilot on September 29, 2026, followed by an Azure Updates announcement on September 30. They bring interactive Azure workspaces alongside Copilot conversations, with initial canvases for resource discovery, cost analysis, and Azure Functions hosted skills. Microsoft's introduction and Azure update.
The practical idea is straightforward: keep the controls and results for an Azure task visible while discussing the work with an agent.
My recommendation is to evaluate each canvas against one bounded engineering task. A convenient interface should make the scope of the work easier to inspect, not make that scope implicit.
Three Canvases, Three Different Responsibilities
The official marketplace describes Azure Resources Query as a read-only Resource Graph interface with explicit subscription selection. That makes resource discovery a sensible starting point for an evaluation. Azure Resources Query.
Azure Cost Health Check provides read-only analysis of costs, forecasts, budget alerts, Advisor recommendations, and AI billing. Azure Cost Health Check.
Azure Functions Hosted Skills supports local building, running, and debugging, plus invoking supported functions in an existing Function App. That is a different operational boundary from reading an inventory. Azure Functions Hosted Skills.
I would record that distinction in the team's evaluation notes. Do not assume that every canvas has the same permissions, consequences, or review requirements just because the interfaces appear in the same application.
Start with an Explicit Identity and Scope
Microsoft's setup guidance uses the Azure CLI and an Azure sign-in, then installation through the Awesome Copilot marketplace and a new Copilot session. The announcement describes the GitHub Copilot app experience. Installation and session guidance.
My first check would be the intended tenant, subscription, and identity. Use the access needed for the evaluation and keep production administration out of a discovery exercise unless it is genuinely required and approved.
Give the test a written boundary: which environment is in scope, what the engineer is trying to learn, and what actions are excluded. For example, listing nonproduction Function Apps is a clearer initial task than asking an agent to "clean up Azure."
Before sharing a screenshot or exported result, review it for resource names and other internal details. Read-only access can still reveal information that should remain within the team.
Turn Resource Discovery into a Checkable Answer
For my first Resources Query exercise, I would choose a small inventory whose expected contents can be independently checked. Ask for a particular resource type in selected subscriptions, then compare a sample against the team's existing inventory process.
Record the selection and filters with the result. If an expected resource is missing, investigate scope, access, and query assumptions before concluding that the resource does not exist.
The acceptance criterion should be an answer another engineer can reproduce. A useful demonstration explains both what was included and what was outside the query, rather than presenting a count without context.
This also creates a reusable handover artifact: the question, the selected scope, the checks performed, and the unresolved exceptions.
Treat Cost Findings as Review Inputs
My proposed Cost Health Check evaluation starts with a defined billing period, currency, and subscription scope. Compare a small set of figures with the team's normal cost-review process before using the results in a budget conversation.
For a suggested optimization, record the resource owner and the operational reason the resource exists. A recommendation is an investigation item, not an instruction to remove capacity that might serve a recovery or peak-demand requirement.
Separate observed spend, forecast spend, and possible savings in the review notes. Those are different kinds of evidence and should not be combined into a single confident-looking financial result.
I would ask the service owner to accept any proposed action through the team's usual change process. The dashboard can help organize the discussion; it should not silently replace ownership of the decision.
Hosted Skills Need an Action Boundary
For the Functions canvas, I would begin with a test function whose effects are harmless and observable. Use synthetic inputs and a nonproduction destination, then verify the actual output rather than relying only on the agent's description.
Before invoking an existing function, establish what it does. A function that sends a notification, updates a record, or calls an external service can have consequences even when the surrounding task sounds like a demonstration.
My proposed test record includes the requested operation, approved inputs, expected side effects, and recovery procedure. If deployment is part of the exercise, review the proposed resources and configuration before approving that step.
These are evaluation recommendations, not claims that I have installed the canvases or deployed a hosted skill.
Practical Cloud Engineer Takeaway
My proposed checklist is:
Choose one canvas and one bounded task for the first evaluation.
Confirm the identity, tenant, subscription selection, and permitted actions.
Make inventory results reproducible with recorded filters and checks.
Keep cost observations distinct from forecasts and proposed savings.
Review function behavior before any invocation or deployment.
Use approved test data and preserve evidence of the outcome.
Keep resource owners involved in operational decisions.
Who Should Care?
Azure developers, platform engineers, and FinOps practitioners who want interactive tools alongside agent-assisted work without losing a clear review boundary.
Bottom Line
Azure canvases offer a more visible workspace for several common cloud tasks. Start with a small, verifiable result, then expand only when the team understands the scope and consequences of each action.
Sources
Stay radical, stay curious, and keep pushing the boundaries of what is possible in the cloud.
Chriz
Beyond Cloud with Chriz
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