Microservices Architecture
Highly scalable backend systems using Node.js, NestJS, and Golang with event-driven communication. We design systems that grow with your business demands.
Overview
Modern applications require architectures that can scale independently, deploy frequently, and handle failures gracefully. Our microservices solutions deliver exactly that—highly scalable, maintainable systems built for the demands of modern business.
We design event-driven architectures using Node.js, NestJS, and Golang that enable loose coupling between services, allowing your teams to develop and deploy independently. Our microservices communicate efficiently through REST APIs, GraphQL, message queues, and event streams.
From domain-driven design to containerization and orchestration, we implement best practices that ensure your microservices architecture is robust, observable, and ready to scale.
Key Benefits
Scalable distributed systems
Event-driven microservices for performance
Improved fault tolerance and maintainability
Use Cases
SaaS platform backend
Real-time messaging apps
Multi-service e-commerce systems
Technologies We Use
Frequently Asked Questions
When should I use microservices instead of a monolith?
Microservices are ideal when you need independent scaling, have multiple teams working on different features, require different technologies for different services, or need to deploy features independently. For smaller applications or MVPs, a well-structured monolith might be more appropriate.
How do you handle inter-service communication?
We use a combination of synchronous (REST, gRPC) and asynchronous (message queues, event streams) communication patterns based on the use case. For real-time needs, we use gRPC; for eventual consistency, we use event-driven patterns with Kafka or RabbitMQ.
How do you ensure microservices reliability?
We implement circuit breakers, retry mechanisms, health checks, distributed tracing, centralized logging, and comprehensive monitoring. We also use service mesh technologies like Istio for advanced traffic management and security.
What about data consistency across services?
We use the Saga pattern for distributed transactions, event sourcing for audit trails, and CQRS (Command Query Responsibility Segregation) when appropriate. Each service owns its data, and we ensure eventual consistency through well-designed event flows.
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