Spring Boot Course

Welcome to the Spring Boot Backend Engineering track on TechLearningPRO — a complete, production-grade roadmap from your first @RestController to designing microservices that ha…

Spring Boot is an opinionated layer on top of the Spring Framework that removes 90% of the boilerplate Spring used to require.

A Spring Boot app is layered: the web layer handles HTTP, the service layer owns business rules, the repository layer talks to the database, and configuration wires it together.

Before writing your first endpoint you need three things: a JDK, a build tool (Maven or Gradle ships with starters), and an IDE.

Spring Initializr (start.spring.io) is the official project generator.

A standard Spring Boot project follows a Maven layout.

Let's build, run and hit your first Spring Boot endpoint.

Dependency Injection (DI) is Spring's superpower.

A Spring bean is any object Spring manages.

Configuration is how an app behaves differently in dev, staging and prod without code changes.

application.properties and application.yml are interchangeable formats for Spring Boot configuration.

Annotations are how you talk to Spring.

Controllers map HTTP requests to Java methods.

Spring offers fine-grained mapping by URL, HTTP method, headers, content type and query params.

Two ways data flows into a controller: path variables identify a resource (/orders/42), query params filter or paginate (?status=PAID&page=1).

REST (Representational State Transfer) is a set of conventions for building HTTP APIs around resources.

Time to ship a real CRUD API: Create, Read, Update, Delete for a Product resource — the workhorse pattern of every backend job interview.

Spring Boot ships with Jackson for JSON.

ResponseEntity<T> gives you full control over the HTTP response: status, headers, body.

DTOs (Data Transfer Objects) are the shapes you expose at API boundaries.

Centralised exception handling turns scattered try/catch into a single, consistent error contract.

Bean Validation (Jakarta Validation) declares constraints on DTO fields and Spring enforces them automatically when you add @Valid.

Spring Boot uses SLF4J as the API and Logback as the default implementation.

Every backend stores state somewhere.

MySQL is the most-deployed open-source SQL database.

PostgreSQL is the database of choice for serious backends in 2026: JSONB, full-text search, partitioning, generated columns, array types, robust replication.

Spring Data JPA turns repository interfaces into runtime implementations.

Hibernate is the default JPA provider Spring Boot ships with.

Entities are Java classes annotated with @Entity that map 1-to-1 to database tables.

Relationships model how entities reference each other.

JPQL (Java Persistence Query Language) looks like SQL but operates on entities and fields, not tables and columns.

When JPQL can't express what you need (Postgres-specific JSON ops, CTEs, window functions), drop to native SQL with nativeQuery = true.

Returning unbounded result sets is how junior backends become production incidents.

@Transactional wraps a method in a database transaction: all writes commit together or roll back together.

Backends die at the database first.

The Repository pattern abstracts persistence behind an interface.

The service layer owns business rules.

Spring Security is the standard for authentication and authorization on the JVM.

Authentication answers who are you?.

Authorization answers what are you allowed to do?.

JWT (JSON Web Token) is a signed, self-contained credential the client sends with every request.

Access tokens are short-lived (15–60 min).

RBAC = permissions tied to roles, roles tied to users.

Never store passwords in plaintext.

Spring Security is a filter chain.

OAuth 2.0 is the standard for delegated authorization: "let users sign in with Google / GitHub without you holding their password." OpenID Connect (OIDC) adds an identity layer…

Securing a REST API is more than authentication.

Beyond auth, production APIs need protection against abuse, replay, scraping and accidental DDoS — even from your own clients.

Two paradigms, one decision: server-side sessions (cookie ↔ session in Redis) vs self-contained tokens (JWT, no server state).

Profiles let one binary behave differently per environment.

12-factor apps configure via the environment.

Uploads are easy to do wrong.

Don't run your own SMTP.

@Scheduled runs methods on a cron or fixed-rate schedule.

Some work shouldn't block the request: sending emails, generating thumbnails, calling slow third parties.

Redis is the universal cache: sub-millisecond reads, tiny footprint, perfect for hot reads, session storage, rate limiting and pub/sub.

WebSockets give you persistent, bidirectional connections — the right tool for chat, live dashboards, notifications.

Apache Kafka is the durable, partitioned log behind every event-driven enterprise.

Event-Driven Architecture (EDA) replaces synchronous calls between services with events on a log.

An API Gateway is a single front door for all your microservices: routing, auth, rate-limiting, request rewriting, observability.

Rate limiting protects your service from abuse, runaway clients, and the occasional internal bug-loop.

You can't fix what you can't see.

Optimisation order matters: measure, then change.

Unit tests verify a single class in isolation: services, mappers, validators.

Integration tests spin up a slice (or all) of the Spring context against real dependencies — best done with Testcontainers for Postgres, Redis, Kafka.

Microservices split one big app into many small ones, each owning a bounded slice of business capability.

Monolith: one process, one DB, one deployment.

In a microservices world, services come and go.

In microservices, the gateway is even more critical: clients should talk to one URL while you reorganise services freely behind it.

Spring Cloud Config Server centralises configuration for all your services in a Git repo.

When a downstream service is failing, hammering it makes everything worse.

When a request hops 5 services, logs alone won't tell you where the latency went.

Services talk via HTTP, gRPC, or async messaging.

Each microservice ships as a Docker image.

Kubernetes orchestrates containers across machines: scheduling, scaling, healing, networking, config.

Once containerised, deploying is a choice of platform: AWS ECS / EKS, GCP GKE / Cloud Run, Azure AKS, or simpler PaaS like Render / Railway / Fly.io.

Docker packages your app + its runtime into an immutable image that runs the same on every machine.

Three good ways to containerise Spring Boot, in order of preference: buildpacks, Jib, hand-written Dockerfile.

CI/CD automates the path from commit to production: build, test, scan, push image, deploy.

GitHub Actions is the default CI for most Spring Boot teams in 2026: free for public repos, native to GitHub, huge action marketplace.

Jenkins is the legacy CI workhorse — still everywhere in enterprises.

AWS hosts more Spring Boot apps in production than any other cloud.

For side projects and startups, Railway, Render, Fly.io remove 95% of cloud ceremony.

Production logs are read by machines: a JSON log shape, shipped to Loki / CloudWatch / Datadog, queryable by trace ID.

The de-facto monitoring stacks in 2026: Prometheus + Grafana + Loki + Tempo (self-hosted), Datadog / New Relic / Honeycomb (SaaS).

Scaling isn't more servers — it's removing the bottleneck.

Twelve-factor app rule #3: store config in the environment.

Production-grade security is layered.

Performance engineering is a discipline: define SLOs, measure under load, fix the hottest path, repeat.

Clean Architecture (Uncle Bob) puts the business core at the centre and pushes frameworks, DBs and HTTP to the outside.

Layered architecture is the pragmatic, Spring-shaped flavour of clean architecture: Controller → Service → Repository → DB.

DDD is the playbook for complex domains: identify bounded contexts, model aggregates with strong invariants, communicate via events.

A short list of patterns you'll meet weekly in real Spring Boot codebases.

Enterprise APIs are contracts that outlast their authors.

Scalable systems are built on a few invariants: stateless services, shared-nothing data, async where possible, observable everywhere.

HA is about surviving failures invisibly.

System design interviews and real-world architecture share the same vocabulary: load estimates, data modelling, storage choice, caching, scaling, consistency.

A condensed, repeatable optimisation playbook used at Netflix, Stripe and Shopify.

Enterprises hold regulators, auditors and red teams to a higher bar than startups.

How serious teams organise a Spring Boot service.

Hands-on exercises to cement what you've learned.

Sharpen your API design skills with these scenarios.

Debugging is the highest-leverage skill in backend engineering.

Database mastery separates senior from junior backend engineers.

Authentication is where mistakes are public and expensive.

Stretch your architecture muscles with these whiteboard-style problems.

Twenty rapid-fire questions across the course.

A curated bank of senior backend interview questions across Spring Boot, system design and behavioural rounds.

End-to-end portfolio projects modelled on what real backend teams ship in their first year.

Read how the world's most demanding backends are actually built.