Pragmatic architecture for enterprise systems: avoiding distributed monoliths
Transitioning to microservices without considering operational complexity creates technical debt. We examine approaches for building stable enterprise systems.
DECISIONS & DELIVERY
Transformation field notes
Practical guides to operating models, process automation, transformation governance, management data and controlled AI.
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316 publications
Hybrid development in enterprise: balancing custom code and low-code
How to combine the flexibility of custom development with the speed of low-code while maintaining engineering discipline, version control, and robust system architecture.
Data Mesh and data products: future of system integration by 2027
Transitioning to a Data Mesh architecture resolves integration chaos through data decentralization, data contracts, and moving away from fragile point-to-point connections.
Integrating legacy systems without APIs: CDC, facade services, and RPA limits
A practical analysis of architectural patterns for connecting legacy systems to modern ecosystems: how to avoid point-to-point chaos and why RPA is only a temporary solution.
Common integration mistakes that destroy IT architecture
Why ignoring organizational principles, lacking data owners, and "big bang" migrations doom corporate integration, and how to build a managed architecture.
Data governance and data lineage: quality for AI
The success of AI initiatives depends on data lineage transparency and Data Governance maturity. Learn how to avoid poor data quality traps and prepare enterprise IT architecture for AI scaling.
API Management and Data Contracts: Overcoming Integration Chaos
How to transition from fragile point-to-point connections to a managed integration layer using API gateways and schema registries to ensure enterprise system stability.
Event-driven architecture: Kafka vs RabbitMQ and reliable event delivery
Comparing Kafka and RabbitMQ for building reliable event-driven architectures. Learn how to avoid integration issues and ensure data integrity.
When to use ESB versus point-to-point integration
Comparing architectural approaches: when direct connections become inefficient and how implementing an integration bus helps avoid complexity during scaling.
System integration and MDM: architectural patterns for scaling without chaos
Transitioning from point-to-point integrations to standardized EIP patterns, API Gateways, and managed Master Data Management to preserve corporate data integrity.
AI agents in workflow: first-line processing and BPM future
How to combine the flexibility of AI with the rigid logic of BPMN 2.0 and DMN to automate first-line request processing without security risks or operational chaos.
Process mining: visualizing real flows and shadow processes
Process Mining methodology reconstructs real task flows using digital footprints, revealing hidden bottlenecks and unauthorized workarounds invisible to management.