AI agents are moving from answers to actions. But how do you safely run what they create? On Azure Friday, @shanselman and Jan Kalis explore how Azure Container Apps Sandboxes isolate agentic AI workloads.
Watch now: msft.it/6018atozp
Watch now: msft.it/6018atozp
Oct 16, 2026 · 4:00 PM UTC
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@Azure @shanselman Got my popcorn ready for another Azure Friday 🍿
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@Azure @shanselman Yep, been having this conversation now for about a year, using @Tanium Atlas. It's interesting for sure the power behind answers to actions. If you don't have a sandbox, be very careful in production with this power. 😁👍
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@Azure @shanselman Sandboxes give SI agents safe playgrounds to act without breaking things! Isolation is key for agentic trust 😁 BANGER move by Azure team!
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@Azure @shanselman sandboxing the runtime is the easy half — the hard half is what the sandbox can reach once the agent needs a real credential. that's usually where the isolation story goes quiet.
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@Azure @shanselman The detail worth copying from the docs: sandboxes running untrusted agent code should start default-deny on egress with a narrow allow list, and egress rules can add auth so the agent never holds the API key. MicroVM isolation plus network policy is the full story. @shanselman
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@Azure @shanselman I’d test the boundary with a concrete case: an agent reads a document containing instructions to export data. Does the sandbox deny the network request even if the generated code tries it? Isolation is most convincing when the failure path is demonstrated.
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