Microservices

Microservices Architecture

We design and implement microservices architectures that allow your team to scale development and infrastructure independently. Domain-driven design, event-driven communication, API gateway, containerization with Docker and Kubernetes, and full observability.

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The challenge

Monolith vs microservices: your product's most important architectural decision

Not every project needs microservices. A well-designed monolith is the best option for small teams and early-stage products. But when your product grows, when multiple teams need to deploy independently, when one module's load cannot affect the rest of the system, then microservices architecture becomes a necessity, not a luxury.

Migrating from a monolith to microservices is one of the most complex projects in software engineering. It is not simply about splitting code into smaller services. It requires redefining the bounded contexts of the business domain, establishing clear contracts between services, designing communication patterns (synchronous vs asynchronous), implementing distributed transaction management with sagas or event choreography, and building the observability infrastructure needed to operate a distributed system.

The event-driven approach is fundamental in a well-designed microservices architecture. Instead of services calling each other synchronously (creating temporal coupling), services publish events when something relevant happens and other services react to those events. This reduces coupling, improves resilience, and allows each service to scale independently. Message brokers like RabbitMQ, Apache Kafka, or AWS SNS/SQS are the backbone of this communication.

At Soamee, we have designed and implemented microservices architectures for platforms operating at global scale. Orquest manages workforce across 42+ markets with independent services for planning, communication, and analytics. Xceed operates in 125+ cities with microservices for ticketing, payments, and event discovery. InfoAdex processes over 55 million advertising records with distributed data pipelines. Each case required different architectural decisions, but all share the same principles: service autonomy, independent deployment, and complete observability.

DDD

Domain-Driven Design

Event

Event-driven architecture

K8s

Docker + Kubernetes

O11y

Full observability

Key capabilities

The pillars of a microservices architecture

Every component is designed to maximize autonomy, resilience, and system scalability.

Domain-Driven Design

We identify your business domain bounded contexts with event storming sessions. Each microservice encapsulates a complete business context with its own database, models, and rules. Aggregates define transactional boundaries. Ubiquitous language ensures code speaks the same language as the business.

Event-driven communication

Event-based architecture with message brokers (RabbitMQ, Kafka, AWS SNS/SQS). Saga patterns for distributed transactions. Event sourcing when change history is critical. CQRS to separate read and write operations and optimize each independently. Dead letter queues for error management.

API Gateway and service mesh

API gateway (Kong, AWS API Gateway, Traefik) as single entry point with routing, rate limiting, authentication, and request transformation. Service mesh with Istio or Linkerd for secure service-to-service communication with mutual TLS, circuit breakers, retries, and intelligent load balancing. Canary deployments and traffic splitting.

Containerization and orchestration

Docker for consistent packaging of each service. Kubernetes for orchestration with metrics-based auto-scaling (CPU, memory, requests/s), rolling updates with zero downtime, health checks, and self-healing. Helm charts for reproducible deployments. Namespaces for environment isolation (dev, staging, production).

Observability and monitoring

Alle three observability pillars implemented: centralized logs with ELK or Loki, metrics with Prometheus and Grafana, and distributed tracing with Jaeger or OpenTelemetry. Business and technical dashboards. Intelligent alerting with PagerDuty. SLIs and SLOs defined for each service. Automated runbooks for common incidents.

Per-service CI/CD

Each microservice has its own independent CI/CD pipeline. Automatic build, test, security scan, and deploy. Feature flags for gradual activation. Blue-green or canary deployments to reduce risk. Automatic rollback if health metrics degrade. Trunk-based development with short-lived feature branches.

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Technologien

Microservices tech stack

Production-proven tools and platforms for distributed systems at scale.

Node.js NestJS Python FastAPI Go TypeScript Docker Kubernetes Helm Terraform RabbitMQ Apache Kafka Redis PostgreSQL MongoDB Kong Istio Prometheus Grafana OpenTelemetry Jaeger AWS ECS ArgoCD GitHub Actions

Fallstudien

Microservices at scale in production

Real platforms with microservices architecture operating across multiple markets.

Orquest

Workforce management platform with independent microservices for planning, communication, and analytics. Operating in 42+ markets with per-service scaling.

42+ international markets

Xceed

Nightlife platform with microservices for ticketing, payments, discovery, and venue management. Present in 125+ cities with traffic spikes managed by auto-scaling.

125+ operational cities

InfoAdex

Advertising analytics platform with distributed data pipelines. Ingestion, processing, and query microservices over 55 million records.

55M+ records processed

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FAQ

Häufig gestellte Fragen about microservices

When should I migrate from monolith to microservices?

Clear indicators are: multiple teams needing to deploy independently, a system module that needs to scale differently from the rest, deployment cycles getting longer because any change requires deploying everything, or failures in one component affecting the entire system. If your team is small (fewer than 8-10 developers) and the product is in its early stages, a well-structured monolith is almost always the better option. Microservices add significant operational complexity that is only justified when the benefits outweigh that cost.

How much does implementing a microservices architecture cost?

A partial migration from monolith to microservices (extracting 2-3 critical services) typically costs between EUR 40,000 and 80,000 and takes 3-4 months. A complete microservices architecture from scratch with 8-15 services, Kubernetes infrastructure, observability, and per-service CI/CD ranges from EUR 100,000 to 250,000 and requires 6-12 months. Monthly operational costs also increase compared to a monolith, though this is offset by faster development velocity and lower downtime risk.

How are transactions managed between services?

In microservices, distributed transactions are managed with the Saga pattern. Each service executes its part of the transaction and publishes an event. If any step fails, compensating transactions are executed to revert previous steps. There are two approaches: orchestration (a coordinator service directs the saga) and choreography (each service reacts to events autonomously). The choice depends on flow complexity. For simple operations, choreography is sufficient. For complex flows with multiple conditions, orchestration offers better visibility and control.

Do we need Kubernetes for microservices?

Not necessarily. Kubernetes is the most powerful option for container orchestration, but it has a steep learning curve and significant operational cost. Simpler alternatives like AWS ECS/Fargate or Google Cloud Run offer the same basic capabilities (auto-scaling, health checks, rolling updates) with much less operational complexity. For teams without K8s experience, we recommend starting with managed services and migrating to Kubernetes when system complexity justifies it. What matters is containerizing from the start with Docker.

How is a microservices system monitored?

Observability in microservices is based on three pillars: centralized logs (ELK Stack or Loki + Grafana) to see what happened, metrics (Prometheus + Grafana) to know how the system is doing, and distributed tracing (Jaeger or OpenTelemetry) to follow a request across multiple services. Additionally, we define SLIs (indicators) and SLOs (objectives) for each service, configure intelligent alerting (no noise) with PagerDuty, and maintain business and technical dashboards. A good observability system is the difference between resolving an incident in 5 minutes or 5 hours.

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Let's design your microservices architecture

We analyze your current system and define the migration strategy or design from scratch. No commitment, no fine print.

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