Operationalizing AI Agents with Microsoft Foundry and Azure Services
A practical look at moving agent-based solutions from proof of concept into production by integrating Azure services, enterprise data, and resilient deployment patterns.
8 min readPerspectives on data platform architecture, analytics engineering, Azure and Snowflake delivery, machine learning, and enterprise AI implementation.
A practical look at moving agent-based solutions from proof of concept into production by integrating Azure services, enterprise data, and resilient deployment patterns.
8 min readPatterns for structuring raw, business, and mart layers while keeping orchestration, CI/CD, and warehouse governance manageable for enterprise teams.
6 min readHow to connect data preparation, model training, container deployment, monitoring, and retraining into an Azure-based machine learning operating model.
7 min readA practical comparison of modeling approaches and when each pattern makes sense in enterprise analytics environments.
10 min readWhy tool selection is only one part of the problem, and how data quality, transformation discipline, and delivery practices shape the outcome.
9 min readHow to think about storage, ingestion, orchestration, identity, and deployment when Azure services and Snowflake both play central roles.
7 min readI'm available for speaking engagements, workshops, and architecture discussions on any of these subjects.
Get in Touch