Domain-Driven Service Design
Identify bounded contexts, ownership, contracts, consistency requirements, and team boundaries before decomposing a system into services.
Java and Cloud-Native Engineering
Java and Spring Boot Microservices That Stay Operable at Scale
ARINITS architects enterprise Java platforms around clear domain boundaries, dependable data ownership, secure APIs, event-driven integration, and production observability. We balance service independence with the operational cost of distributed systems.
Discuss Your ProjectWhat We Deliver
Spring Boot Platform Engineering
Build secured REST APIs, validation, persistence, caching, configuration, resilience, and reusable platform capabilities with modern Java and Spring Boot.
Kafka and Event-Driven Systems
Design event contracts, partitions, ordering, consumer groups, retries, dead-letter handling, idempotent consumers, schema evolution, and end-to-end traceability.
Cloud-Native Operations
Package services with Docker, orchestrate with Kubernetes, automate delivery, and instrument logs, metrics, traces, health checks, and service-level indicators.
How We Work
- 1
Architecture assessment
Understand domains, workloads, dependencies, data, non-functional requirements, failure modes, and current operational pain.
- 2
Boundary and contract design
Define service responsibilities, APIs, events, schemas, security, data ownership, and consistency patterns.
- 3
Incremental implementation
Deliver vertical slices with automated tests, deployment pipelines, observability, and backward-compatible contracts.
- 4
Reliability validation
Test load, recovery, retries, duplicates, dependency degradation, autoscaling, and rollback before production expansion.
Technology Expertise
Java 17+Spring BootSpring SecurityKafkaPostgreSQLRedisResilience4jOpenTelemetryDockerKubernetesPrometheusGrafana
Engineering Outcomes
- ✓Services aligned to business domains rather than technical layers
- ✓Explicit consistency and failure-recovery patterns
- ✓Versioned APIs and evolvable event contracts
- ✓Production diagnostics through logs, metrics, and traces
Frequently Asked Questions
Should every monolith be converted to microservices?
No. A modular monolith is often the better starting point when team size, scaling, deployment independence, and domain complexity do not justify distributed-system overhead.
How do you choose service boundaries?
We combine domain capabilities, data ownership, change cadence, scaling needs, transaction boundaries, failure isolation, and team ownership. Database tables or UI screens alone are poor boundaries.
How do services maintain consistency?
For local invariants we use database transactions. Across services we use explicit workflows such as sagas, transactional outbox, idempotent consumers, compensating actions, and reconciliation rather than distributed database transactions.