Updated July 2026. Refreshed for current microservices best practices.
What Are Microservices?
Microservices architecture is an approach to building software as a collection of small, independently deployable services. Each service owns a specific business capability, runs in its own process, and communicates over lightweight protocols such as HTTP/REST, gRPC, or asynchronous messaging.
Unlike a monolith — where all features live in one codebase and deploy as a single unit — microservices let teams ship, scale, and fail independently. Netflix, Amazon, and Uber popularized this style to handle massive scale and rapid feature delivery.
Key Characteristics
- Single responsibility — each service does one thing well (orders, payments, inventory).
- Independent deployment — deploy one service without redeploying the entire system.
- Decentralized data — database-per-service; no shared tables across boundaries.
- Polyglot persistence — choose the best database per service (PostgreSQL, MongoDB, Redis).
- Resilience by design — failures are isolated; circuit breakers prevent cascading outages.
Microservices vs Monolith
Start with a monolith when your team is small, domain is unclear, or speed of initial delivery matters most. Split into microservices when you hit scaling bottlenecks, need independent team ownership, or require different scaling profiles for read-heavy vs write-heavy components.
Core Building Blocks (2026)
- API Gateway — single entry point for clients (Kong, Envoy, AWS API Gateway).
- Service discovery — Kubernetes DNS, Consul, or Eureka.
- Message broker — Apache Kafka for event-driven communication.
- Container orchestration — Kubernetes for deployment, scaling, and health checks.
- Observability — OpenTelemetry traces, Prometheus metrics, structured logging.
Example: E-Commerce System
An online store might split into: Product Catalog, Order Service, Payment Service, Inventory Service, and Notification Service. When a customer places an order, the Order Service publishes an OrderCreated event. Payment and Inventory services react asynchronously — no direct database coupling.
Challenges to Planar
- Distributed transactions — use Saga pattern instead of two-phase commit.
- Eventual consistency — reads may lag behind writes; design UX accordingly.
- Operational complexity — more services means more monitoring and deployment pipelines.
- Network latency — prefer async events over chatty synchronous calls.
What to Learn Next
Continue with Monolith vs Microservices, then explore CQRS with Kafka and Kubernetes deployment.
Microservices Tutorial Series
- 1. Introduction to Microservices Architecture
- 2. CQRS Pattern in Microservices with Kafka
- 3. Event Sourcing Explained
- 4. Saga Pattern for Distributed Transactions
- 5. Deploy Microservices on Kubernetes
- 6. Outbox Pattern for Reliable Events
- 7. Apache Kafka for Microservices
- 8. Service Mesh with Istio
- 9. Circuit Breaker Pattern
Next: CQRS Pattern in Microservices with Kafka →
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Go deeper with the book: Practical Microservices Design Using CQRS and Event Sourcing by Kindson Munonye.
Kindson Munonye is a software engineer and technical author specializing in microservices, CQRS, event sourcing, and distributed systems. He publishes free step-by-step tutorials and live classes on Alkademy.