August 24, 2026 Posted in APISIX, Elasticsearch, Enterprise Architecture, Enterprise Integration, ESB, fluentbit, Grafana, Istio, JAEGER, Kiali, Kibana, Kubernetes, Microservices, Prometheus, Zitadel

As a former Oracle Fusion Middleware team member, I would outline middleware and integration methodologies and tools during past two decades.

I authored Enterprise Integration in a Nutshell before, which explains how middleware supports enterprise integration. Middleware covers application servers, ESB, SOA, and API design. A typical 3-tier setup is common in SOA. It includes a front end, business logic on the app server, and a back-end database. This pattern helps organize systems and data flows.

Design patterns apply to both 3-tier and multi-tier development. Additionally, creational, structural, and behavioral patterns guide these layers. Model view controller (MVC) is used in large 3-tier apps. This approach supports scalable, reusable software components across teams...

August 21, 2026 Posted in Data Migration, Datacenter, Enterprise Architecture, Enterprise Integration, Investment Optimization

There is a common requirement to migrate datacenter from on-premises to cloud.

During my consulting career, I led several on-premises datacenter migrations. Additionally, these projects targeted financial, utilities, and transportation organizations.

To give you a big-picture view, I outline the datacenter structure.

The datacenter structure includes racks, power bus, cooling towers, networking gear, air handling units, backup generation, and water storage. This layout supports power distribution, environmental control, and resilience. Understanding how these elements interact helps operators plan capacity and respond to changes.

Within each rack, components such as network switches, cable management, servers, and cooling modules exist...

August 20, 2026 Posted in Blogs, Data Architecture, Data Migration, Database, Enterprise Architecture, Enterprise Integration

I would like to provide a data architecture summary briefly. Additionally, it reflects my long-term working practices in this area.

Data Architecture and Governance:

• Data governance involves strategies, policies, processes and procedures, collaboration, tools, audit and metrics, etc. For detail info, please refer to Seven Steps to Effective Data Governance.
• Data quality includes data validation, foreign keys, constraints and data cleansing. Please refer to 10 Best Practices in Database Schema Design.
• Metadata management involves schema design, data linage, API contracts, etc. Building a Database-driven Application Framework includes good references.
• Toolbox: MS Purview, Ataccama, Denodo

Data Modeling:

• UML: describe the relationship among objects, no emphasize o...