Voc On Steroid

Vocabulary‑Learning Platform

Full‑stack Go monolith (Clean Architecture)

A web application that lets users discover, organise, and master new words through instant search, contextual examples, spaced‑repetition, and gamified challenges. The codebase is deliberately structured for long‑term testability and maintainability, and it runs on a production‑grade Kubernetes platform that I also built and operate.

Technical Strengths

Category	Details
Language & Framework	Go + Gin for HTTP routing, gqlgen for a GraphQL API (`/graphql`).
Architecture	Clean Architecture (Domain ↔ Application ↔ Infrastructure). Business rules live in `internal/domain`; use‑case orchestration and CQRS handlers in `internal/application`; external adapters (PostgreSQL, Redis, JWT) in `internal/infrastructure`.
CQRS & Event Bus	In‑memory bus powered by go‑dew – commands (e.g., `CreateWordListCommand`) mutate state, queries (e.g., `GetWordListQuery`) read data.
Persistence	PostgreSQL via GORM for relational data; Redis for caching / session storage.
Generic Repository	`generic.Repository[T,F]` defines CRUD; `GormGenericRepository` provides type‑safe implementations for all domain entities.
Dependency Injection	Compile‑time wiring with Google Wire, making services easily replaceable in tests.
Authentication	JWT – short‑lived access token stored in an HTTP‑only cookie; long‑lived refresh token stored in the DB. Gin middleware extracts the token and injects `userID` into the request context.
Logging	Structured logging with Zerolog (JSON output, request IDs).
Testing	Unit & integration tests using GoMock, table‑driven test patterns, and in‑memory repositories for fast CI execution.
Observability	Metrics exported via Prometheus, traces via OpenTelemetry, and logs aggregated in a cluster‑wide stack (Prometheus + Grafana + Loki + Jaeger).
Deployment Platform	Runs on a self‑managed 3‑node HA Kubernetes cluster (MetalLB, Cilium CNI) with a GitOps workflow powered by Argo CD. Deployment time dropped from 1–2 h to < 10 min and failure rate reduced from ~40 % to < 5 %. ~

User‑Facing Core Features

Instant Word Search – definitions, etymology, phonetic transcription, and audio playback; toggle between simple and detailed views.
Custom Lists & Tagging – one‑click saving into user‑defined collections (e.g., Philosophy Terms) with label‑based tags for targeted review.
Contextual Examples – literature, news, film excerpts, and community‑submitted quotes, filterable by genre or culture.
Gamified Daily Challenges – adaptive quizzes (definition guess, fill‑in‑the‑blank, synonym matching) that award badges and update mastery graphs.
Spaced‑Repetition Engine – automated review reminders at optimal intervals; users can override schedules for intensive training.

Operational Flow

Request → Gin Router – Incoming HTTP (or GraphQL) request passes through JWT middleware.
Resolver → go‑dew Bus – Light GraphQL resolvers validate input and publish a command or query onto the in‑memory bus.
Handler → Domain Logic – Appropriate handler executes business rules in the application layer, invoking generic repositories as needed.
Infrastructure → DB / Cache – GORM reads/writes PostgreSQL; Redis serves cached lookups and session data.
Observability Hooks – Custom OpenTelemetry spans and Prometheus counters are emitted for each command/query, feeding the cluster‑wide monitoring stack.

Why it matters – The project demonstrates end‑to‑end mastery of modern Go engineering (clean architecture, CQRS, DI), production‑grade Kubernetes operations (GitOps, observability, rapid deployments), and a user‑centric product that turns vocabulary learning into an engaging, data‑driven experience.