Microservices Architecture
We design and build microservices architectures, and we help teams understand when microservices are the right choice and when they are not. A microservices architecture is not an upgrade from a monolith by default; it is a different set of trade-offs that makes some things easier and some things significantly harder.
Capabilities
What we do with microservices
Domain-driven design
Service Decomposition
Breaking an application into service boundaries along domain lines. We identify the bounded contexts in the business domain first, then define service boundaries that reflect those contexts rather than technical convenience.
Kafka · RabbitMQ · SQS
Event-Driven Architecture
Asynchronous service communication using message queues and event buses. We design the event schema, consumer group topology, and failure handling for durable messaging between services.
Routing · Auth · Rate limiting
API Gateway Design
API gateway configuration for routing external requests to internal services, enforcing authentication, applying rate limits, and aggregating responses from multiple services into a single client response.
Strangler fig migration
Monolith to Microservices
Migrating a monolithic application to microservices incrementally using the strangler fig pattern. We extract services one at a time while keeping the monolith operational, which avoids a high-risk big-bang rewrite.
Traces · Metrics · Logs
Service Observability
Distributed tracing with OpenTelemetry, structured logging, and metrics collection across all services. Without observability, a microservices architecture is harder to debug than the monolith it replaced.
Deployment · Scaling · Networking
Kubernetes Deployment
Deploying microservices on Kubernetes with proper resource requests and limits, health checks, horizontal pod autoscaling, and service mesh configuration for inter-service communication.
Our approach
Start with the domain, not the technology
Service boundaries that follow database tables or technical layers rather than business domains tend to produce the worst outcome: a distributed monolith that has all of the operational overhead of microservices without the independence. We do domain modeling first, and the service boundaries follow from that.
Each service owns its data
A microservices architecture where services share a database has not actually separated those services. They remain tightly coupled at the data layer. Each service owns its own data store and exposes access to that data through its API, not through direct database queries from other services.
Distributed systems fail differently
A service call across a network can fail in ways that a function call within a process cannot: timeouts, partial failures, out-of-order message delivery, and duplicate messages. We design for these failure modes from the start — circuit breakers, idempotent handlers, and retry logic with backoff are standard parts of the implementation, not additions after the first production incident.
Observability before deployment
A microservices system without distributed tracing is almost impossible to debug when something goes wrong across service boundaries. We set up OpenTelemetry, log correlation IDs, and health endpoints before a service reaches production.
All engineering work is done by US-based engineers. We do not offshore any development or architecture work.
Part of our software engineering services. We work across the full stack, cloud platforms, and architectural patterns.
FAQ
Common questions
Virginia · United States
Need microservices expertise?
If you are designing a new microservices system or migrating from a monolith, reach out and we will assess your situation before recommending an approach.