Rewrite Java/Spring applications to Go with spec-driven parity

You rewrite Java/Spring to Go by extracting specifications, generating tests, implementing in parallel, and rolling out with parity using the LEAP Protocol. We start by extracting behavioral specs from your Spring Boot code: OpenAPI from springdoc-openapi/Springfox, controller contracts (Spring MVC/WebFlux), validation rules (Bean Validation), data models (JPA/Hibernate), and security flows (Spring Security). From those specs we generate a conformance test suite that captures current behavior and edge cases: HTTP routes, status codes, error bodies, JSON shapes (Jackson), date/time and number formats, validation messages, and SQL semantics. In parallel, we implement Go services with Gin or Chi, map interceptors and filters to middleware, translate @Transactional to database/sql transaction scopes, and port persistence either to explicit SQL (sqlc, sqlx) or an ORM like GORM/ent. We run the new Go service behind a compatibility harness, shadow traffic, and gate promotion on the tests you approved—no production cutover until parity is proven. Finally, we roll out incrementally (canary/blue‑green), verifying logs and metrics match before decommissioning the Java service. That is how we deliver a safe, auditable Java/Spring-to-Go rewrite.

Why Go for Java/Spring migrations

Faster cold starts and lower memory footprint than the JVM, enabling leaner containers and quicker autoscaling for bursty workloads.
Static binaries and simple deployment: no JVM tuning, classpath, or fat JARs; multi-stage Docker builds produce tiny images (Alpine/distroless).
Concurrency that scales: goroutines and channels avoid thread-per-request overhead; ideal for high-IO and streaming services often built with WebFlux.
Predictable performance with zero GC pauses large enough to impact tail latencies in many services, plus pprof/native tooling for profiling.
Standard library strength: database/sql, net/http, and first-class support for tracing/logging; easy integration with OpenTelemetry.

Our methodology

Spec extraction (Java/Spring) - Derive OpenAPI from springdoc-openapi/Springfox; enumerate controllers, @RequestMapping, @ControllerAdvice, and filters. - Capture Jackson serialization, Bean Validation constraints, and Spring Security flows (JWT/OAuth2, CSRF, roles). - Normalize data-access intent: lift JPA/Hibernate queries (JPQL/Criteria) into explicit SQL specs, including pagination, sorting, and transaction boundaries.
Test generation (LEAP test-gated) - Produce HTTP conformance tests (status codes, headers, error payloads), schema/shape tests (including nullability and default values), and idempotency/consistency checks. - Create SQL golden tests to lock in query semantics, isolation levels, and cascade behaviors; add clock/locale fixtures for time and number formatting. - Wire tests to run against both the Java reference and the Go candidate; no promotion without green parity.
Parallel Go implementation (agent-agnostic) - Build handlers in Gin or Chi; port validation with go-playground/validator; map exception handling to structured error responses. - Choose persistence: explicit SQL with sqlc/sqlx for clarity or GORM/ent for higher-level modeling; replicate @Transactional with context-scoped tx. - Implement interceptors/middleware equivalents: authZ/authN, correlation IDs (MDC → context), rate limits, and retry/backoff. - Performance baselines via pprof and k6; lock in SLOs before rollout.
Parity rollout and cutover - Shadow traffic or dual-write reads behind a proxy; compare responses and logs. - Canary by endpoint or tenant; observability via OpenTelemetry, Prometheus, and structured JSON logs. - Final switch only when conformance and SLO gates are met; keep a reversible toggle for fast rollback.

Specific Java/Spring concerns we handle

JPA/Hibernate to Go data access: translating lazy loading and cascading rules to explicit SQL or ORM behavior; handling N+1 queries with joins.
@Transactional semantics: mapping propagation and isolation to database/sql transactions; ensuring retry/compensation for optimistic locking.
Jackson vs Go JSON: field naming, null vs omitted, custom serializers/deserializers, and enum/string coercion with encoding/json or jsoniter.
Spring MVC/WebFlux binding: path/query/form/multipart parsing, type conversion (@InitBinder) to Go types; Unicode, locales, and time zones.
Spring Security: porting method/route security, OAuth2/JWT validation, CSRF/session behavior to Go middleware (e.g., oidc, casbin), including role/claim mapping.

Proof

sqlite-leap — five SQLite engines generated from one spec, demonstrating spec-first, cross-implementation consistency: https://github.com/safitudo/sqlite-leap
semver-leap — 5,632 passing tests validating precise behavioral compatibility: https://github.com/safitudo/semver-leap
LEAP Protocol — spec-first, test-gated, agent-agnostic delivery method: https://github.com/safitudo/leap

These public artifacts show we don’t hand-wave about parity; we codify it, test it, and publish the results.

Pricing & timeline

Typical engagement: 4–12 weeks depending on service scope and data-access complexity.
Fixed-price proposal after a 3–5 day discovery that inventories controllers, data paths, and nonfunctionals (SLOs, compliance).
Typical budgets: $40k–$120k for a well-bounded service (single domain, <50 endpoints, moderate data modeling).
Deliverables: specs, generated tests, Go codebase (Gin/Chi), migration playbook, and a reversible cutover plan.

Ready to turn Java/Spring into lean, maintainable Go—without surprises? Email hello@leapagentic.com with your OpenAPI or a link to your Spring Boot repo; we’ll return a firm plan in days, not weeks.

Leap Agentic is distinct from Legacyleap.ai and Impetus Leap AI.