Posts tagged "Operations"

Turn observability patterns into operational infrastructure with alert rules, workbooks, and deployment guidance that makes AI monitoring actionable.

Infrastructure metrics can't tell you if AI responses are helpful. Learn to instrument semantic quality, conversation degradation, and user outcomes.

RAG systems fail silently when retrieval breaks. Learn to monitor Azure AI Search, vector stores, and the retrieval pipeline that feeds your models.

Skip the Netflix-scale chaos. Learn to start chaos engineering in Azure with simple, safe experiments that actually improve your systems without breaking production.

Stop building useless dashboards. Learn to create Azure Workbooks that actually help your team make decisions and solve problems faster.

Stop monitoring AI infrastructure like web servers. Learn to instrument Azure OpenAI with queries that reveal token consumption, content filters, and cost attribution.

Master KQL from an infrastructure perspective. Learn to write queries that solve real operational problems, from capacity planning to incident response.

Deploy the Beyond Azure Monitor patterns as infrastructure code. Complete monitoring stack with intelligent alerts, workbooks, and ITSM integration.

Transform advanced KQL patterns into production monitoring systems with automation, intelligent alerting, and integration strategies that scale across enterprise environments.

Master advanced KQL techniques for correlation analysis, anomaly detection, and building monitoring queries that connect the dots across your entire infrastructure.

Azure Monitor is just the starting point. Real enterprise monitoring requires custom solutions, advanced KQL, and architectural thinking beyond the basics.

Organizations ask 'are we hybrid or not?' as if it's a strategic decision they haven't made yet. The answer is yes. The question is whether you're operating like it.

You'll build the instrumentation. Leadership will nod at the dashboard. Then nothing will happen. The same organizational failure that killed SRE adoption.

A framework for building confidence in AI-enabled systems through observable criteria, instrumentation, and staged authority expansion. Theory meets practice.

Stop asking if you can trust AI. Start building confidence in systems you understand. The trust discourse is sabotaging adoption with the wrong frame.

You bought a 4K smart TV to play VHS tapes. Why Azure-only shops keep choosing tools that solve problems they dont have.

Why SRE adoption failed outside Google and what we learned from attempting to transplant a complete system rather than adapting principles to organizational reality.

How to implement resiliency as a design principle woven into platform architecture, with practical guidance for operations teams and AI integration.

Practical steps to implement Platform Resiliency on Monday morning - from drawing clear boundaries to enforcing standards through the platform.

Large language models changed AIOps from expensive vendor theater to genuine operational intelligence that can absorb the toil.

The shift from monitoring servers to observing user experience isn't obvious until a cloud-native customer exposes your blind spots.