Loading Ucanly AI
Preparing your workspace...
From developer to Java architect: JVM internals, performance engineering, distributed microservices, and a multi agent AI platform.
8 modules · 48 lessons
JVM internals and performance engineering, system design and scalable architecture, microservices and distributed systems, event driven architecture and resilience, observability testing and production operations, a minor project on JVM performance engineering, advanced AI engineering with Java, and a major project architecting a distributed AI platform.
This is the final stage of the Ucanly Java Programming and Application Development track, where developers become Java architects. Built for practitioners with hands on experience shipping tested Spring Boot services with JPA, security, and Docker, this program goes deep into JVM internals, garbage collector tuning across G1, ZGC, and Shenandoah, and profiling with JFR, async profiler, and JMH. You will design distributed systems with Spring Cloud, Kafka, and gRPC, event driven architecture with event sourcing and CQRS, and resilience patterns with Resilience4j. In your week six minor project, you will take a genuinely slow enterprise service to production speed through profiling, GC tuning, query optimization, and a virtual thread rewrite, proven under real load. You will also build full observability with OpenTelemetry, Prometheus, and Grafana, and move into advanced AI engineering with Java: production RAG, Spring AI at depth, multi agent orchestration, and evaluation with guardrails. You will graduate having architected a distributed, event driven Java microservices platform in your week twelve major project, with Kafka, gRPC, saga based consistency, a multi agent AI layer, full observability, Kubernetes deployment, and a defended architecture document.
Complete this course to earn a verified Ucanly certificate you can add to your profile, share on LinkedIn, and showcase to employers as proof of the skills you've built.
It is recommended, but hands on experience shipping tested Spring Boot services with JPA, security, and Docker is sufficient to start.
Yes, your minor project takes a genuinely slow enterprise service to production speed through profiling, GC tuning, query optimization, and a virtual thread rewrite, with load tested proof of the improvement.
Production RAG architectures in Java, Spring AI at depth with advisors and streaming, multi agent orchestration, and evaluation pipelines with guardrails and cost engineering.
A distributed, event driven Java microservices platform with Kafka, gRPC, saga based consistency, a multi agent AI layer, full observability, Kubernetes deployment, and a defended architecture document.