Why does stateless design matter for a .NET API running on Azure App Service?

Why should an App Service-hosted API be stateless across instances?

Explains local filesystem limits, multiple instances, in-memory state, distributed cache, durable storage, and scale-out-safe API design.

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I would design an App Service API as stateless across instances. Requests can land on different workers, instances can restart, and local files are not a durable coordination mechanism. Durable data belongs in a database or storage service, shared cache belongs in a distributed cache, and long-running work belongs behind a queue or worker. Local disk can be scratch space, but not the source of truth for user workflow state.

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Stateless service design, scale-out behavior, local disk risk, in-memory caches, sessions, durable storage, and reliability under restarts.

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Why this question matters
App Service instances can restart, scale out, and receive different requests during normal operation. Durable workflow state, shared files, coordination, and background work therefore need external services rather than assumptions about one process or one local disk.
I would design an App Service API as stateless across instances. Requests can land on different workers, instances can restart, and local files are not a durable coordination mechanism. Durable data belongs in a database or storage service, shared cache belongs in a distributed cache, and long-running work belongs behind a queue or worker. Local disk can be scratch space, but not the source of truth for user workflow state.
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I would identify each kind of state separately: per-request values, per-instance cache, distributed cache, uploaded files, sessions, generated reports, locks, and background jobs. Sticky sessions can mask a design problem, but they do not fix restarts, deployments, or uneven load. If the API writes files locally or keeps static collections as workflow state, scale-out creates inconsistent behavior. I would move durable state to Azure SQL, blob storage, Redis, or queue-backed processing depending on the data and access pattern.

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Using static lists for production background work.
Writing uploaded files to local disk as final storage.
Assuming in-memory cache is shared across instances.
Relying on sticky sessions instead of fixing state ownership.

Why does stateless design matter for a .NET API running on Azure App Service?

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