In this episode, we explore how AI enhances Operational Excellence. From observability and troubleshooting to automation, governance, and human-in-the-loop decision making.
 
In this conversation, Boris Scholl and Niels Buit discuss where AI delivers real value—and where architects must carefully manage risks and tradeoffs.
 
If you’re a cloud architect, platform engineer, or developer responsible for operating systems in production, this video will help you understand how to apply AI practically and assess risks and tradeoffs in real-world environments.
 
✅ What You’ll Learn
 
How AI fits into the Operational Excellence pillar of the Well-Architected Framework
How AI improves observability, dependency mapping, and proactive issue detection
What AI can do today in root cause analysis, summarization, and remediation
The risks of non-deterministic systems and how to mitigate them
When and why to keep a human in the loop
Security, privacy, and governance considerations for AI-driven operations
How AI can turn WAF from a static checklist into a living, evolving system

00:06 – AI and Operational Excellence in the Well-Architected Framework
00:48 – Running AI vs Using AI to Improve Operations
01:21 – Why Day Two Operations Matter More Than Day One
02:05 – Observability, Deployment, and Troubleshooting
02:40 – Why Observability Is the Best Starting Point for AI
03:38 – Non-Deterministic AI and Operational Risk
04:05 – Real-World AI Use in Engineering Operations
04:39 – AI Opportunities: Simulation and Auto-Remediation
05:00 – Getting Started with OpenTelemetry
05:48 – What AI Enables in Observability Today
06:24 – Dependency Graphs and Predictive Failure Detection
07:01 – Human-in-the-Loop for Critical Incidents
08:00 – Fail Fast, Guardrails, and Responsible AI
08:50 – Hallucinations, RCA Accuracy, and Summarization Risk
09:29 – AI-as-a-Judge and Evaluation Patterns
10:17 – Security and Privacy Considerations
11:30 – How WAF Helps Navigate AI Tradeoffs
12:19 – Making WAF a Living, AI-Driven Framework
13:15 – Key Takeaways and Final Thoughts

🔗 Resources & Links
🚀 Azure Well-Architected Framework
https://learn.microsoft.com/azure/well-architected/
Microsoft Learn
https://learn.microsoft.com/en-us/azure/well-architected/operational-excellence/
⚡ Try Azure for free
https://aka.ms/AzureFreeTrialYT

👥 Speakers
Boris Scholl
https://www.linkedin.com/in/bscholl/

Niels Buit
https://www.linkedin.com/in/nielsbuit/


#Azure
#AI
#OperationalExcellence
#WellArchitectedFramework
#CloudArchitecture
#Observability
#OpenTelemetry
#DevOps
#ResponsibleAI
#AzureArchitecture
#MicrosoftDeveloper
#CloudComputing

Microsoft Developer

A conversation exploring how AI can enhance operational excellence within the AWS/Azure Well-Architected Framework. Key themes include using AI for observability (dependency graph analysis, SLI monitoring, automated alerting), the importance of starting with OpenTelemetry as a common schema, and the need for human-in-the-loop controls for critical or compliance-sensitive decisions. The discussion covers risks of non-deterministic AI behavior, the 'AI as judge' pattern for validating agent outputs, PII handling, and how WAF can become a dynamic rather than static checklist when enriched with AI capabilities.

Use AI to Achieve Operational Excellence with the Well-Architected Framework practices