The ability to understand what is happening inside a system or integration from its outputs, using tracing, correlation IDs, dashboards, alerts and replay capabilities rather than plain logs alone.
Title graphic: Observability (Concept)
Type
Concept
Key points about Observability
Deterministic practices such as orchestration, validation, governance, retries, observability and state management are needed. · Enterprise AI Agent Engineering with…
Agentic AI for IT operations combines goal-driven agents with governed workflows, observability, identity and human oversight. · Agentic AI for IT Operations
Autonomy should be introduced gradually with guardrails, observability, measurable outcomes and human oversight. · Agentic AI for IT Operations
In this episode of the M365.fm podcast, Mirko Peters speaks with Microsoft MVP and MCT Anitha Eswaran about the realities of integrating Dynamics 365 Finance & Operations (D365FO) into modern enterprise environments. The discussion focuses on why integrations…
Most organizations believe efficiency improvements come from better tools or faster processes. But the biggest gains rarely come from new software. They come from architectural decisions. In this episode of the M365 FM Podcast, we explore how organizations…
The episode talks about how automation is evolving from simple scripts into more advanced, intelligent systems that can monitor themselves and fix problems automatically. Instead of just executing predefined tasks, modern automation uses telemetry data (like…
In this episode of the M365 FM Podcast, host Mirko Peters speaks with Microsoft AI MVP and CTO Karthikeyan VK about the biggest problem in today’s AI landscape: organizations are relying too heavily on Large Language Models (LLMs) while ignoring the…
Explore agentic AI for IT operations with Christiaan Brinkhoff: Windows 365, Intune, AI agents, governance, security, and Microsoft's agentic OS vision.
In this episode of the M365.fm podcast, we dive deep into building and deploying production-grade AI agents with Microsoft Foundry together with Edgar McOchieng (MVP). The conversation explores how organizations can move beyond AI demos and prototypes into…
In this episode we walk through what really happens when Azure AI Foundry doesn’t behave the way you expect, especially when the Agent Service or deployments start acting up. Azure AI Foundry is supposed to feel smooth, almost invisible, tying together OpenAI…
Enterprise integration is usually invisible until it breaks, and deterministic workflows struggle with the unexpected. This episode is for architects and integration developers who want to understand Azure Logic Apps, connectors, identity and observability…
Most teams still treat Azure SQL as passive storage behind the application. In this interview, Dirceu Resende shows data engineers and architects how Azure SQL Database can call REST APIs, automate workflows and support AI with vector search. You learn where…
Many organizations celebrate early Copilot and chatbot wins, then discover agents borrowing human identities, calling models directly and running long after their projects ended. This episode is for architects, IT and governance leaders who want to scale AI…
Enterprise AI is rapidly evolving from simple chatbots to intelligent agents that can automate business processes, reason over enterprise data, and deliver measurable business value. In this episode of M365.fm, Microsoft MVP Shubhangi Goyal joins Mirko Peters…
CI/CD pipelines are designed to accelerate software delivery, but as organizations grow, speed alone is no longer enough. Without governance, automated pipelines can spread security risks, configuration drift, compliance violations, and inconsistent…
Agents need orchestration, validation, governance, retries, observability and state management. These practices make enterprise AI systems reliable instead of depending only on what a language model produces. · From the episode: Enterprise AI Agent Engineering with…
Gradually, through guardrails, observability, measurable outcomes and human oversight. In enterprise environments autonomy must stay bounded by identity, permissions, policy, logging and escalation paths. · From the episode: Agentic AI for IT Operations
Why is observability important for production agents?
Real-time monitoring maintains performance and helps address issues quickly. Observability shows what an agent is doing in production, so problems are found early instead of after users complain. · From the episode: Production AI Agents with Microsoft Foundry…
Why do Azure AI Foundry projects fail?
Common reasons are unclear goals, poor data quality, weak governance, technical mistakes and missing observability. Teams also set unrealistic expectations or ignore ongoing care, while complexity, GPU limits and rising costs add pressure. · From the episode: Fix Common Azure AI Foundry Project Failures
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