Serverless / Container Runtime
Deployment target family for stateless agents, tool gateways, MCP servers, and isolated execution.
Source boundary
Runtime entry groups serverless and container targets for compatibility planning rather than naming a single vendor.
Relationships
| Type | Source | Target | Citation |
|---|---|---|---|
| supports | serverless-container-runtime | filesystem-tool | Runtime relationship is a planning fact based on deployment and sandbox constraints. |
Compatibility
| Type | Target | Status | Evidence |
|---|---|---|---|
| runtime_deployment | serverless-container-runtime | supported | AutoGen applications can be packaged as Python or .NET services and deployed in server or container environments. |
| runtime_deployment | serverless-container-runtime | supported | Dify can be deployed as a containerized application on serverless and container platforms. |
| runtime_deployment | serverless-container-runtime | verify_required | Google ADK is positioned for building and deploying agents, but runtime-specific process, secrets, and network assumptions must be verified for each target. |
| runtime_deployment | serverless-container-runtime | supported | Haystack pipelines and agent workflows are suitable for server and container deployment patterns. |
| runtime_deployment | serverless-container-runtime | supported | LangChain and LangGraph applications commonly run in server, container, and workflow runtime deployments. |
| runtime_deployment | serverless-container-runtime | supported | LlamaIndex agent and workflow applications can run as service or container deployments for data-connected agent workflows. |
| runtime_deployment | serverless-container-runtime | verify_required | Mastra is a TypeScript agent framework that can fit serverless or containerized Node.js deployments, subject to persistence, workflow, and provider configuration. |
| runtime_deployment | serverless-container-runtime | supported | Agent Framework targets production-grade agent and workflow deployments that fit server and container runtime patterns. |
| runtime_deployment | serverless-container-runtime | verify_required | OpenAI Agents SDK workflows can be deployed in server or container environments, but production runtime assumptions should verify process lifetime, secrets, network access, and tracing setup. |
| runtime_deployment | serverless-container-runtime | verify_required | Pydantic AI Python agents can be evaluated for server or container deployment, but packaging, process lifetime, and observability must be verified. |
| runtime_deployment | serverless-container-runtime | verify_required | Semantic Kernel can run in application services and containerized enterprise stacks, but language runtime and connector dependencies must be validated. |