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You are designing a multitenant software as a service (SaaS) platform that uses multiple agents. Users will send latency-sensitive inference requests to the platform by using a shared API.
Initially, there will be 20 tenants, and the platform will expand to 200 tenants.
You need to identify the compute component for a production agent runtime. The solution must meet the following requirements:
Isolate workloads for each tenant by using containerization.
Dynamically scale based on demand.
Minimize administrative effort.
What should you use?
Microsoft Foundry Agent Service is the managed option that best satisfies containerized production agent execution, dynamic scaling, and low administrative overhead. Hosted agents run in Foundry-managed container compute and scale according to workload demand while the platform manages much of the runtime, endpoint, identity, and operational plumbing. AKS could provide strong tenant/workload isolation and autoscaling, but it also requires Kubernetes cluster operations, policy, upgrades, node pools, and scaling configuration, which conflicts with the requirement to minimize administration as the tenant count grows. Azure Container Instances is simpler but lacks the same managed autoscaling model, and GPU virtual machines create the highest infrastructure burden. Therefore C is the strongest fit for a SaaS platform that wants production agent compute without owning the orchestration platform. From an architecture perspective, the selection also creates explicit ownership and boundaries that can be tested independently. That matters in multi-agent systems because implicit sharing or loosely defined authority often becomes the source of cross-agent coupling, security drift, and difficult incident diagnosis.
Official Microsoft reference: Microsoft Foundry Agent Service overview