Enterprise architects can measure and track architectural technical debt across their application estate, evaluating and detecting pockets of architectural drift. Report on remediation programs and pinpoint specific applications requiring attention. Application architects can measure complexity, risk, and technical debt on their apps and prioritize aging frameworks and high tech debt targets to fix.

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Analyze application architectures through AI-enabled dynamic and static analysis. Immediately pinpoint and fix current sources of tech debt. Identify and refine domains, uncovering root cause of cross-domain pollution, resource interdependencies, and domain exclusivity problems across class, beans, database tables, and stored procedure relationships. Set desired architecture state as basis for drift observation.

Customer Case Study

Continuously observe, find, and fix architectural issues. Detect architectural drift events after each sprint or test cycle, such as newly introduced dead code, new domains, unexpected dependencies, database table interdependencies, or new common class library issues. Validate modernization updates and resulting tech debt improvements. Refine domain boundaries for emergent architectures. Create modernization stories for each sprint.

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Decompose and extract new miniservice or microservice code and create restful APIs. Eliminate dead code, upgrade frameworks, and deploy efficient, compact microservices. Use the refactoring studio to refine service boundaries, automatically refactor classes, assign code to common libraries, conduct impact analysis of design decisions based on architect’s input. Incrementally deploy new microservices with the Strangler Fig Pattern.

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