Java and Spring Boot
How to Hire a Spring Boot Developer in India
How to Hire a Spring Boot Developer in India requires decisions about Java depth, Spring conventions, database skill, security, testing, production ownership and communication. This guide explains the architecture, delivery and production practices needed to achieve an evaluation scorecard with a paid architecture or coding exercise based on your real domain.
Assess production judgment, not Java trivia
A strong Spring Boot developer should explain domain boundaries, transactions, authorization, query behavior, testing and incident diagnosis. Use a small paid exercise or architecture review based on your system rather than an algorithm unrelated to the work.
Confirm who reviews code, owns releases and responds when production fails. Communication, documentation and database skill often matter more to delivery than familiarity with every annotation.
Use Spring Boot modules around business capabilities
Organize code by domains such as identity, billing or fulfillment rather than placing every controller, service and repository in global folders. Keep transaction boundaries and dependencies explicit so modules can change without reaching through one another.
Start with a modular monolith unless independent deployment solves a measured team or scaling problem. Spring Boot already provides production conventions; adding distributed services too early multiplies configuration and failure modes.
Secure Spring Boot with explicit authorization
Configure Spring Security with a deny-by-default filter chain and test public, authenticated and privileged routes. Validate token issuer, audience and expiry, then enforce resource ownership or method authorization instead of trusting roles sent by a client.
Define CORS precisely, decide whether CSRF applies to the authentication model, keep secrets outside source control and avoid exposing sensitive Actuator endpoints. Return safe errors and log security events without recording credentials or tokens.
Transactions, JPA and PostgreSQL
Keep transactions short and aligned with business operations. Inspect the SQL generated by the ORM, avoid N+1 loading, page large results and use database constraints for invariants that must survive concurrent requests.
Add indexes from real query predicates and ordering, then confirm plans with EXPLAIN. Configure the connection pool against database capacity; increasing application instances must not create more connections than PostgreSQL can support.
Measure Spring Boot in production
Spring Boot Actuator and Micrometer can expose request latency, error rates, JVM behavior and custom business metrics. Add trace or request identifiers so a user-facing failure can be followed through controllers, database calls and external dependencies.
Set service-level targets before tuning. Profile CPU and allocations, inspect slow queries and load test with production-like data; cache or concurrency changes should respond to a measured bottleneck.