|

Microsoft Releases ‘Microsoft Agent Framework’: An Open-Source SDK and Runtime that Simplifies the Orchestration of Multi-Agent Systems

ByRicardo

Microsoft launched the Microsoft Agent Framework (public preview), an open-source SDK and runtime that unifies core concepts from AutoGen (agent runtime and multi-agent patterns) with Semantic Kernel (enterprise controls, state, plugins) to assist groups construct, deploy, and observe production-grade AI brokers and multi-agent workflows. The framework is on the market for Python and .NET and integrates straight with Azure AI Foundry’s Agent Service for scaling and operations.

What precisely is Microsoft delivery?

  • A consolidated agent runtime and API floor. The Agent Framework carries ahead AutoGen’s single- and multi-agent abstractions whereas including Semantic Kernel’s enterprise options: thread-based state administration, sort security, filters, telemetry, and broad mannequin/embedding assist. Microsoft positions it as the successor constructed by the similar groups, relatively than a substitute that abandons both challenge.
  • First-class orchestration modes. It helps agent orchestration (LLM-driven decision-making) and workflow orchestration (deterministic, business-logic multi-agent flows), enabling hybrid methods the place inventive planning coexists with dependable handoffs and constraints.
  • Pro-code and platform interoperability. The base AIAgent interface is designed to swap chat mannequin suppliers and to interoperate with Azure AI Foundry Agents, OpenAI Assistants, and Copilot Studio, lowering vendor lock-in at the utility layer.
  • Open-source, multi-language SDKs beneath MIT license. The GitHub repo publishes Python and .NET packages with examples and CI/CD-friendly scaffolding. AutoGen stays maintained (bug fixes, safety patches) with steering to think about Agent Framework for brand new builds.

Where it runs in manufacturing?

Azure AI Foundry’s Agent Service supplies the managed runtime: it hyperlinks fashions, instruments, and frameworks; manages thread state; enforces content material security and id; and wires in observability. It additionally helps multi-agent orchestration natively and distinguishes itself from Copilot Studio’s low-code method by focusing on advanced, pro-code enterprise eventualities.

But how is it linked to ‘AI economics’?

Enterprise AI economics are dominated by token throughput, latency, failure restoration, and observability. Microsoft’s consolidation addresses these by (a) giving one runtime abstraction for agent collaboration and instrument use, (b) attaching manufacturing controls—telemetry, filters, id/networking, security—to the similar abstraction, and (c) deploying onto a managed service that handles scaling, coverage, and diagnostics. This reduces the “glue code” that usually drives value and brittleness in multi-agent methods and aligns with Azure AI Foundry’s model-catalog + toolchain method.

Architectural notes and developer floor

  • Runtime & state: Agents coordinate through a runtime that handles lifecycles, identities, communication, and safety boundaries—ideas inherited and formalized from AutoGen. Threads are the unit of state, enabling reproducible runs, retries, and audits.
  • Functions & plugins: The framework leans on Semantic Kernel’s plugin structure and function-calling to bind instruments (code interpreters, customized features) into agent insurance policies with typed contracts. (
  • Model/supplier flexibility: The similar agent interface can goal Azure OpenAI, OpenAI, native runtimes (e.g., Ollama/Foundry Local), and GitHub Models, enabling value/efficiency tuning per process with out rewriting orchestration logic.

Enterprise context

Microsoft frames the release as half of a broader push towards interoperable, standard-friendly “agentic” methods throughout Azure AI Foundry—in line with prior statements about multi-agent collaboration, reminiscence, and structured retrieval. Expect tighter ties to Foundry observability and governance controls as these stabilize.

Our Comments

We like this path as a result of it collapses two divergent stacks—AutoGen’s multi-agent runtime and Semantic Kernel’s enterprise plumbing—into one API floor with a managed path to manufacturing. The thread-based state mannequin and OpenTelemetry hooks deal with the common blind spots in agentic methods (repro, latency tracing, failure triage), and Azure AI Foundry’s Agent Service takes on id, content material security, and instrument orchestration so groups can iterate on insurance policies as a substitute of glue code. The Python/.NET parity and supplier flexibility (Azure OpenAI, OpenAI, GitHub Models, native runtimes) additionally make value/perf tuning sensible with out rewriting orchestration.

The publish Microsoft Releases ‘Microsoft Agent Framework’: An Open-Source SDK and Runtime that Simplifies the Orchestration of Multi-Agent Systems appeared first on MarkTechPost.

Similar Posts