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JMaster
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Microservices Development
We decompose complex systems into independently deployable microservices. Each service owns its data, scales on its own, and communicates through well-defined contracts for maximum resilience.
Independent Scaling
Scale bottleneck services without scaling the entire system. Allocate resources precisely where demand requires them.
Team Autonomy
Small teams own individual services end-to-end, enabling parallel development, independent releases, and faster iteration.
Fault Isolation
A failure in one service doesn't cascade. Circuit breakers and graceful degradation keep the rest of your system healthy.
Microservices development cost
Estimated timelines and budget for microservice architecture
Microservices Platform
A microservices platform decomposes your system into independently deployable services with their own databases, APIs, and CI/CD pipelines for maximum scalability and team autonomy.
3–5 months
from $50,000
Service decompositionAPI gatewaymessage brokerservice meshmonitoring
How We Work
01
1–2 weeksDomain Decomposition
Applying domain-driven design to identify bounded contexts, define service boundaries, and plan inter-service communication.
02
2–4 monthsService Development
Building individual services with their own databases, APIs, and deployment pipelines. Using message queues for async communication.
03
2–3 weeksDistributed Testing
Contract testing between services, chaos engineering experiments, and end-to-end integration tests across the full system.
04
1–2 weeksContainer Orchestration
Dockerized services deployed to Kubernetes with auto-scaling, health checks, rolling updates, and centralized logging.
Technologies
Node.jsRustDockerRabbitMQKubernetes
FAQ
Microservices make sense when you have a large team, need independent scaling, or plan frequent releases. For small teams or early-stage products, a well-structured monolith is often the better choice.
We commonly use RabbitMQ for task queues and reliable messaging, and Apache Kafka for high-throughput event streaming. Redis Streams works well for lighter workloads.
We use the saga pattern for distributed transactions, event sourcing for audit trails, and eventual consistency with compensating actions for most inter-service workflows.
Yes. We follow the strangler-fig pattern, gradually extracting services from the monolith so you get incremental benefits without a risky big-bang rewrite.