AutoGen is in maintenance mode. Microsoft Agent Framework is its successor.
Microsoft Agent Framework can run on organization-controlled infrastructure or as a Foundry Hosted Agent. Connic runs Python agents with connectors, tracing, and approvals included; its platform data and connic/* inference stay in the EU.
The most important fact about AutoGen in 2026 is on its own README: the project "will not receive new features or enhancements and is community managed going forward". Microsoft tells new users to start with the Microsoft Agent Framework instead, and existing AutoGen users to migrate. MAF 1.0 went GA on April 2, 2026 as an open-source MIT SDK for .NET and Python, merging AutoGen's orchestration ideas with Semantic Kernel.
MAF can run on organization-operated infrastructure or as a Foundry Hosted Agent. Foundry adds managed infrastructure, automatic scaling, session state, observability, and versioning. Its data-residency outcome depends on the Azure resource, model deployment, and configured tools. Connic provides a managed runtime under a German contract with connectors, tracing, evals, and approvals included. Its platform data and connic/* inference stay in the EU; full-Project residency depends on customer configuration.
Feature Comparison
Connic vs AutoGen + Microsoft Agent Framework, capability by capability.
Development Experience
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| Active developmentAutoGen is in maintenance mode and community managed; new feature work moved to the Microsoft Agent Framework. Connic is actively developed. | Yes | No |
| Agent definitionConnic uses YAML + Python. AutoGen and the Microsoft Agent Framework are class-based SDKs (Python, and .NET for MAF). | Yes | Yes |
| Simple getting startedConnic starts with `connic init` and YAML. AutoGen and MAF are SDKs configured through their Python or .NET APIs. | Yes | Partial |
| Multi-agent workflowsConnic supports sequential agents. AutoGen's conversational multi-agent patterns carry over into MAF's orchestration. | Yes | Yes |
| Custom toolsBoth support Python functions as tools. | Yes | Yes |
EU & Compliance
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| Managed EU data residencyConnic's platform data and connic/* inference stay in the EU; end-to-end Project residency depends on customer configuration. AutoGen and MAF run on the operator's infrastructure. Foundry can keep stored agent data in the Azure resource geography, while model and tool processing depend on configuration. | Yes | Partial |
| EU contract counterpartyConnic contracts through a German company. The open-source frameworks are not hosted services; a Foundry deployment is governed by the customer's Microsoft Azure agreement. | Yes | Partial |
| EU AI Act toolingConnic ships execution logs, approvals, and guardrails mapped to deployer obligations. MAF provides OpenTelemetry and approval primitives, while evidence mapping and retention depend on the deployment. | Yes | Partial |
| EU-hosted platform data and connic/* inferenceConnic keeps its platform data and connic/* inference in the EU. Deployment regions and customer-configured components still determine end-to-end residency. Foundry can keep stored agent data in the Azure resource geography, while model and tool processing depend on configuration. | Yes | Partial |
Production Infrastructure
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| Managed hostingConnic deploys to managed infrastructure. AutoGen and the MAF SDK can be self-hosted; MAF agents can also run on Foundry-managed infrastructure. | Yes | Partial |
| Git-based deploymentsConnic supports push-to-deploy. The frameworks require custom CI/CD setup. | Yes | No |
| Auto-scalingConnic scales automatically. Self-hosted AutoGen or MAF needs scaling infrastructure; Foundry Hosted Agents provide automatic scaling and scale-to-zero. | Yes | Partial |
| Environment managementBuilt-in dev/staging/prod environments. The frameworks need manual environment handling. | Yes | No |
| Secrets managementSecure secrets per environment. The frameworks rely on external solutions. | Yes | No |
Integrations & Triggers
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| HTTP webhook triggersBuilt-in webhooks with Connic. A webhook trigger is not documented as a core AutoGen or MAF feature, so the HTTP layer comes from the deployment stack. | Yes | No |
| Scheduled executionNative cron connector in Connic. A scheduler is not documented as a core AutoGen or MAF feature. | Yes | No |
| Message queue integrationKafka and SQS are first-party in Connic. They are not documented as core AutoGen or MAF connectors and must be added through tools or deployment services. | Yes | No |
| Database triggersPostgreSQL change triggers are first-party in Connic and are not documented as core AutoGen or MAF connectors. | Yes | No |
| Payment/SaaS eventsStripe events are first-party in Connic. SaaS event triggers are not documented as core AutoGen or MAF features. | Yes | No |
Observability & Evals
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| Run tracingAutomatic in Connic. AutoGen has logging, while MAF emits OpenTelemetry. Self-hosted deployments configure an exporter; Foundry supports Application Insights trace integration after configuration. | Yes | Partial |
| Execution historyConnic includes dashboard history. A bare framework deployment needs its own production history store, while Foundry provides managed session state and observability. | Yes | Partial |
| Debug UIWeb dashboard for production debugging in Connic. MAF ships a DevUI debugger aimed at local development; AutoGen is terminal/code-based. | Yes | Partial |
| LLM-judge evals includedConnic includes a first-party judge service. MAF has a built-in evaluation framework with local checks, custom evaluators, and optional Foundry LLM-as-judge evaluators. | Yes | Partial |
| A/B testing in productionConnic runs statistical A/B tests between agent versions in production. A production A/B testing feature is not documented for AutoGen or MAF. | Yes | No |
Agent Capabilities
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| LLM agentsBoth support LLM-powered agents with tool calling. | Yes | Yes |
| Agent-to-agent chatAutoGen excels at conversational multi-agent, and MAF carries the pattern forward. Connic supports sequential pipelines. | Partial | Yes |
| Human-in-the-loopApprovals are a platform feature in Connic. AutoGen uses code patterns; MAF provides a first-class tool-approval agent that still runs within the chosen deployment. | Yes | Partial |
| Code executionBoth can execute code. AutoGen has Docker-based code execution built in. | Yes | Yes |
Pricing
| Feature | Connic | AutoGen + Microsoft Agent Framework |
|---|---|---|
| Free to adoptAutoGen and the Microsoft Agent Framework are MIT-licensed. Connic Basic has no monthly fee and includes a one-time €20 credit; paid plans start at Developer €40/month. | Yes | Yes |
| Credit and custom termsConnic Developer and Pro start at €40 and €200 per month, respectively; the selected monthly amount is released as Project credit. Enterprise uses custom commercial terms. Base rates before package discounts include €0.0337 per started LLM-agent run, €0.00042 per runtime second, and €0.00342 per GB-hour of storage. A self-hosted framework bills across cloud infrastructure, observability, and ops time; the Azure route meters across services. | Yes | No |
The EU question
A framework has no residency, good or bad: AutoGen and the Microsoft Agent Framework run wherever the operator hosts them, as does every service wired around them. If a team operates its own EU infrastructure and wants to own the runtime, that is a legitimate path; it is also a platform project, not an agent project.
Microsoft also offers Foundry Hosted Agents, with managed infrastructure, scaling, session state, observability, and versioning. Stored agent data follows the geography of the configured Azure OpenAI resource. Model and tool processing locations still depend on the selected endpoints and services.
Connic's answer is explicit: a German contract counterparty, EU-hosted platform data, and EU-hosted connic/* inference. Deployment regions and customer-configured components determine the rest of the Project boundary. Related analysis is available in the EU data residency shortlist and Connic feature mapping for the EU AI Act.
Where AutoGen and the Microsoft Agent Framework genuinely fit
AutoGen's research pedigree is real, and its conversational multi-agent patterns shaped the whole category. Its successor deserves credit too: the Microsoft Agent Framework is an actively developed MIT SDK for both .NET and Python, with OpenTelemetry observability and a DevUI debugger, and it is the natural choice for teams building inside the Microsoft ecosystem, especially .NET shops heading toward Azure AI Foundry.
New AutoGen adoption means starting on a codebase Microsoft has moved past. With self-hosted MAF, the team still owns hosting, triggers, production history, and the residency configuration. Foundry can supply managed hosting, state, observability, and evaluation under Azure's terms. If the goal is Python agents in production in the EU without an Azure deployment, Connic supplies that runtime directly. The comparison of the best EU agent platforms for 2026 covers the alternatives side by side .
Why teams choose Connic
What teams get on day one without writing connectors, wiring observability, or running infrastructure.
The Bottom Line
AutoGen is in maintenance mode. Microsoft Agent Framework is its supported successor and can run on organization-controlled infrastructure or Foundry; Connic provides a managed Python runtime outside the Azure stack.
Use Connic when
- Agents running in production rather than a framework migration project
- EU data residency and an EU contract counterparty are procurement requirements
- Managed infrastructure without DevOps overhead
- Enterprise integrations for webhooks, queues, and databases from day one
- Tracing, evals, and approvals as platform features
Use AutoGen + Microsoft Agent Framework when
- Adoption of the Microsoft ecosystem with Azure AI Foundry as the target
- The Microsoft Agent Framework's .NET support
- Research into conversational multi-agent patterns
- An existing AutoGen codebase and platform capacity to keep hosting it
- Fine-grained control over agent-to-agent communication
Frequently Asked Questions
Bring the workflow, trigger source, compliance constraints, and deployment path under evaluation. We will help separate what AutoGen + Microsoft Agent Framework should handle from what belongs in a managed agent runtime.
Compare with SalesOther platforms on the shortlist
Head-to-head comparisons against the platforms most teams weigh alongside Connic. For the full field, survey the 2026 agent deployment platform landscape.
Connic vs CrewAI
MIT-licensed Python and YAML framework plus CrewAI AMP for managed deployment, tracing, evaluations, integrations, knowledge, and approvals. Standard managed-region choice is not publicly specified; Enterprise offers vendor cloud, customer VPC, or customer infrastructure.
Connic vs Self-Hosting
Operating an agent stack on infrastructure controlled by the organization gives direct control over the runtime and its data, subject to configured cloud, model, and tool dependencies. This comparison uses production Kubernetes as a representative baseline and counts the operating work left with the organization.
Connic vs AI by Zapier
Zapier is moving standalone Agents into AI by Zapier, an agentic step inside the Zap editor with model choice, BYOK, tools, knowledge, approvals, and task-based billing. It suits UI-driven automation; Connic remains Git-native and keeps its managed core in the EU.
Connic vs Amazon Bedrock AgentCore
AWS's managed, framework-agnostic agent infrastructure spans runtime, memory, identity, gateways, observability, policy, and evaluations across multiple EU regions. Connic offers a more opinionated Python and YAML path with first-party connectors and an integrated Enterprise governance surface.
Connic vs Google ADK + Agent Platform
Google's current stack combines the open-source Agent Development Kit with a managed Agent Runtime, custom containers, sessions, memory, evaluation, observability, and Google Cloud controls. Connic narrows that surface into a Python and YAML operating model with managed connectors, selectable EU Project regions, and Enterprise governance.
Connic vs Mistral AI Studio
Mistral's European Studio platform combines Agents with Workflows and Connectors, both currently Public Preview, plus observability, evaluations, governance, and hosted, hybrid, dedicated, or self-hosted deployment. Connic remains model-agnostic and adds first-party event connectors, traffic-split experiments, and a Python-and-YAML workflow.