Plan an incremental Java monolith migration that gives services real ownership. Separate data, define stable APIs and events, limit shared libraries, place gateways between clients and services, and add the testing and operational practices needed before independent deployment becomes useful.
Refactor a fragile Java shipment workflow in small, behaviour-preserving steps. Extract readable methods, move logic to the right objects, replace primitive values, remove null checks and side effects, simplify conditions, and make future delivery options easier to add.
Refactor a fragile Java checkout workflow where duplicated rules, long methods, primitive values, repeated switches, and an oversized service force one business change across many files. Learn how to recognize the smells, move behaviour to the right objects, and reduce each future change to a focused edit.
Learn how to redesign a fragile Java reservation workflow so that intent is clear, invalid states are harder to create, dependencies are replaceable, and future changes do not spread across unrelated classes.
Learn how to improve a risky Java payment integration without mixing refactoring with feature work, breaking existing behaviour, or forcing a large rewrite. The tutorial covers impact analysis, risk assessment, incremental design changes, Branch by Abstraction, verification, and the decision between refactoring and rewriting.
Refactor a booking workflow that mixes object construction, provider selection, media loading, and notifications. The solution applies Builder, Factory, Proxy, Command, Publisher/Subscriber, and dependency injection only where each pattern removes a specific maintenance problem.
Learn how to split conflicting customer concepts into bounded contexts, model business rules with aggregates and value objects, and use Onion Architecture, repositories, CQRS, and domain events to keep a growing .NET system maintainable.
Use a practical decision process to compare IaaS, PaaS, SaaS, FaaS, and hybrid deployment for a new .NET application, then structure the system so faster delivery does not create avoidable operational work or permanent cloud lock-in.
Refactor a synchronous delivery workflow so services own their data, publish asynchronous updates, reject duplicate messages, and use Polly retries, circuit breakers, rate limits, and timeouts without allowing one dependency failure to congest the whole system.
Refactor an over-fetching event catalog endpoint by isolating the EF Core driver, projecting LINQ directly into DTOs, loading aggregates only for writes, inspecting generated queries, and using explicit transactions when a read and update must remain consistent.