Monolith to Microservices Migration
Strategic monolith to microservices migration. We decompose monolithic applications into scalable microservices using proven patterns and incremental approaches.
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Why Choose MicrocosmWorks for Monolith Decomposition?
Breaking a monolith into microservices is one of the highest-risk, highest-reward architectural changes a company can make. We've guided dozens of teams through this transition — identifying the right service boundaries, managing data ownership challenges, and executing the migration without disrupting production workloads.
Our Monolith Migration Capabilities
- Domain Boundary Analysis — Use Domain-Driven Design to identify natural service boundaries that align with team structure and business capabilities.
- Data Decomposition Strategy — Design patterns for splitting shared databases, managing distributed state, and handling cross-service data consistency.
- Strangler Fig Execution — Implement anti-corruption layers, route traffic progressively to new services, and maintain feature parity throughout.
- Event-Driven Decoupling — Replace synchronous dependencies with event-based communication for resilient, independently deployable services.
- Platform Engineering — Build the shared infrastructure (service mesh, API gateway, observability) that makes microservices operational.
- Team Topology Design — Align service boundaries with team boundaries following Conway's Law for sustainable, autonomous team ownership.
Technology Stack
We use Kubernetes for orchestration, Apache Kafka for event streaming, Istio or Linkerd for service mesh, and ArgoCD for GitOps deployments. Each service gets independent CI/CD, its own datastore, and comprehensive distributed tracing with Jaeger and Prometheus.
Who This Is For
Engineering organizations where the monolith is limiting team autonomy, deployment frequency, or system scalability. If releases require cross-team coordination, a single component's load affects the whole system, or onboarding new developers takes months — it's time to decompose.
Our Process
Domain Mapping
Analyze the monolith's domains, identify bounded contexts, and map coupling between components.
Decomposition Strategy
Design target service architecture, plan data splitting, and prioritize extraction sequence by business value.
Platform Foundation
Build shared infrastructure — Kubernetes, CI/CD templates, service mesh, and observability stack.
Incremental Extraction
Extract services one at a time, implementing anti-corruption layers and routing traffic gradually.
Operational Maturity
Establish service ownership, on-call practices, SLO tracking, and continuous architecture governance.
Technology Stack
Orchestration
Messaging
Service Mesh
Observability
Industries We Serve
Ready to Decompose Your Monolith?
Let's design a safe, incremental path from your monolith to scalable, independently deployable services.
Frequently Asked Questions
We identify bounded contexts using domain-driven design, extract services incrementally starting with the least coupled modules, implement API gateways for routing, and maintain backward compatibility throughout the migration process.
Monolith to microservices migration at MicrocosmWorks is priced at $25-$50/hour. The total investment depends on the monolith's size, coupling complexity, and the number of services to be extracted.
Timeline varies significantly based on monolith size and complexity. We typically extract the first service in 4-8 weeks, with full migration spanning 6-18 months. Our incremental approach delivers value at each stage rather than requiring a complete rewrite.
We implement synchronous REST or gRPC for request-response patterns and asynchronous messaging via Kafka or RabbitMQ for event-driven communication. We use the saga pattern for distributed transactions and API gateways for external routing.
We follow the database-per-service pattern, extracting service-specific tables into dedicated databases incrementally. During transition, we use database views, CDC, or API calls to maintain data access while gradually decoupling shared database dependencies.