Governance with the Agent Governance Toolkit
OWASP Agentic Top 10 coverage with YAML policy files, two API surfaces, and a metric bridge that shows policy denials in Grafana.
Microsoft Agent Framework (MAF) is a production-grade SDK for building multi-agent AI applications with structured orchestration, tool governance, and observability. These articles cover Microsoft Agent Framework architecture, workflow patterns, memory management, agent registry conventions, and migration paths from other frameworks.
21 posts tagged with microsoft agent framework. ← All posts
OWASP Agentic Top 10 coverage with YAML policy files, two API surfaces, and a metric bridge that shows policy denials in Grafana.
I built memory, communication, security, governance, and evals from scratch first. Then I deleted most of it and used the Microsoft Agent Framework-native packages. Here is the audit table and what survived.
Single-turn evals check one decision. Multi-turn evals check the whole trajectory. A Python harness with three evaluators, an offline test suite, and the judge prompt that actually works.
OpenTelemetry through the Microsoft Agent Framework's configure_otel_providers, custom workflow spans, custom metrics for runs/duration/agent selection, Jaeger + Prometheus + Grafana wiring, and the set-once latch gotcha.
The reference architecture distinguishes request-based and message-driven agent communication. For in-process orchestration, the workflow IS the broker — and A2A is just the wire format.
AgentSession is short-term memory. MemoryContextProvider + MemoryFileStore is long-term memory. Mem0 is long-term memory for serious workloads. The boundary that matters and how to implement each.
The Microsoft Agent Framework deliberately does not ship an agent registry. Here is why that is the right call, and what to build as a project-local convention when you need one.
PROVIDER=ollama, granite4.1:3b, zero API keys, no Azure account. How to make a multi-agent project that demonstrates enterprise patterns without requiring enterprise infrastructure.
The first ten posts treated the Microsoft Agent Framework as having four orchestration patterns. The official docs say five. Here are the two I missed — Group Chat and Magentic — and why they matter.
Sequential, Concurrent, Handoff, and Custom WorkflowBuilder. Four shapes the Microsoft Agent Framework ships out of the box, when to pick each, and the gotchas that cost me a day.
Microsoft published a 12-chapter reference architecture for multi-agent systems and a separate framework — the Microsoft Agent Framework — to build them. Here is what the 102 Python files actually contain and how they map to the chapters.
The patterns that worked, the traps we fell into, and what we'd do differently.
What worked, what was hard, and what we'd do differently. Real numbers: 18 agents, 90 days, 5 governance policies, 4 provider swaps.
Running agents on Cloud Run, exposing via A2A, and wiring into production systems.
Deploy Microsoft Agent Framework multi-agent systems on Cloud Run with A2A agent-to-agent communication, autoscaling, load balancing, and production observability dashboards.
How to instrument agents for observability, error handling, and audit logging.
Migrate ADK callbacks to Microsoft Agent Framework composable middleware: decorators for audit logging, retry with backoff, token budget enforcement, and OpenTelemetry tracing.
How to port ADK's model hard-codes to Microsoft Agent Framework's provider factory pattern.
Zero-code LLM provider swaps across environments: Ollama for dev, OpenAI for staging, Azure Foundry for prod. Same agents, different models.
How to port tools, add policy enforcement, and integrate OPA.
Migrate ADK functions to Microsoft Agent Framework governed tools with policy enforcement, DLP scanning, approval gates, and OPA integration for production agent systems.
How conversation threads replace session state; how to track token usage across agent chains.
Sessions to threads: porting multi-turn state from ADK to Microsoft Agent Framework. Token budgeting, long-term memory, and conversation audit trails.
How to port ADK's orchestration callbacks to Microsoft Agent Framework builders without losing control.
How to port ADK's orchestration callbacks to Microsoft Agent Framework builders without losing control. The executor pattern: you own the loop.
The philosophy, trade-offs, and what we learned converting 18+ agents in 3 months.
The philosophy, trade-offs, and what we learned converting 18+ agents in 3 months. Provider abstraction as the foundation for portable agents.
Five interfaces hold the whole platform together. The 30-line orchestrator closure that makes the rest of the architecture testable, auditable, and safe to evolve.
Microsoft's Multi-Agent Reference Architecture in Go. Protocol, registry, bus, governance, orchestration, observability, evaluation — and how the seven hold each other up.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.