Java & Spring Boot
Java and Spring Boot are the workhorses of enterprise backend engineering. Almost every bank, insurer, telco and large e-commerce platform runs a substantial fraction of its critical business logic on the JVM, and Spring Boot is the framework the last decade of that industry has settled on. What makes this stack worth learning is not that it is fashionable — it isn't — but that it is where the interesting problems live: multi-year systems, high-throughput trade paths, twenty-year-old data models that still have to serve mobile clients. Learning Spring Boot well means learning the ergonomics of the ecosystem (starters, auto-configuration, actuator) alongside the deeper Java runtime it hides: the class loader, the garbage collector, the JMM.
What this track covers
This track walks the full Spring Boot surface area a working backend engineer actually touches — building REST APIs with validation and error handling, persistence with Spring Data JPA (including the N+1 traps every team hits), Spring Security with JWT for stateless services, caching with Redis, messaging with Kafka, and the resilience primitives from Resilience4j. It also covers the deployment story: packaging as a fat jar or a native image, containerising for Docker, and running behind an API gateway.
Who this is for
Backend developers moving from junior to mid-level who already know Java syntax and want to ship real services, and engineers coming from another stack (Node, Python, .NET) who need to become productive on a Spring codebase quickly. If you have never written Java before, start with the CS Fundamentals track first.
Prerequisites
- Comfortable with core Java 17+ syntax, generics and lambdas
- Basic SQL (SELECT, JOIN, WHERE) and how a relational database differs from a document store
- HTTP fundamentals — verbs, status codes, headers, JSON payloads
- Command line and Git basics for cloning and running examples
Recommended learning order
// beginner
Start with 'Building REST APIs with Spring Boot' to get a service running end-to-end, then 'Spring Data JPA Best Practices' to persist data properly. Add 'Spring Security JWT' once you need to protect endpoints. Deploy the result with 'Dockerizing a Spring Boot Application' — at this point you have a shippable service.
// intermediate
Add integration and unit testing with the testing strategy guide, wire in Redis caching, and learn API rate limiting. Then move to service-to-service concerns: circuit breakers with Resilience4j, and messaging with the Spring Boot + Kafka tutorial. This is the boundary where 'a backend' becomes 'a system'.
// advanced
Study the Spring Boot microservices architecture guide alongside the Software Architecture track. Focus on the operational surface: JVM tuning, observability with Micrometer, GraalVM native images, and multi-tenant patterns. At this level the framework fades and the underlying distributed-systems problems dominate.
Common mistakes to avoid
- Reaching for @Autowired field injection instead of constructor injection — makes testing painful and hides dependencies
- Loading entire entity graphs into memory because a @OneToMany relation is EAGER by default in some mappings
- Storing JWTs in localStorage on the frontend and treating that as 'secure enough'
- Using Spring's transactional annotations on private methods (they don't work — self-invocation bypasses the proxy)
- Enabling every Spring Boot starter 'just in case' and then wondering why cold start is 12 seconds
Career relevance
Spring Boot fluency is one of the single highest-leverage skills in enterprise hiring. Job boards in London, Frankfurt, New York and Singapore consistently list more Spring roles than any other backend stack, and salaries for engineers who can debug a production JVM sit at the top of the backend market. It is also portable — a strong Spring engineer can move into Kotlin, Scala or general JVM roles with weeks, not months, of ramp-up.
Featured tutorials in this track
Redis Distributed Caching Architecture for High-Traffic APIs
Build a production-grade distributed cache with Redis and Spring Boot — cache-aside, @Cacheable, TTL, eviction, cache stampedes, warming, hit-rate monitoring and scalability for high-traffic APIs.
API Rate Limiting in Spring Boot with Bucket4j and Redis
Protect your APIs from abuse with per-user and per-IP rate limiting using Bucket4j, Redis and a clean filter-based implementation.
Spring Boot + Kafka — Build a Real-Time Messaging System
Produce and consume Kafka messages from Spring Boot with proper serialization, error handling and consumer groups.
Spring Boot + Redis Caching — Make Your API 10× Faster
Cache hot reads with Redis and Spring's @Cacheable in minutes. Includes TTLs, eviction and key design tips.
Spring Data JPA — 10 Best Practices for Production
Avoid N+1, lazy loading traps, and slow startup. The 10 JPA practices that separate hobby apps from production systems.
Spring Security + JWT — Stateless Auth Done Right
A practical, modern Spring Security 6 setup: JWT validation, stateless sessions, and method-level authorization.
A Pragmatic Spring Boot Testing Strategy
What to unit-test, what to slice-test, and when to spin up Testcontainers. A pyramid you can actually maintain.
Building REST APIs with Spring Boot: A Complete Guide
Design and build a production-ready REST API with Spring Boot — proper layering, DTOs, validation, error handling and testing.