A practical mental model to understand microservices architecture without drowning in buzzwords.
🧠 Objective
This post offers a visual-first reference map for Microservices Architecture — a simplified and structured way to understand the essential components of building, scaling, and maintaining distributed systems. You won’t find deep theory or excessive buzzwords here. Just a practical framework that brings clarity to complexity.
🔍 Introduction
Microservices have moved from hype to necessity. In today’s cloud-native world, if you’re building scalable and resilient systems, you’re likely adopting microservices — or at least considering it.
But let’s be honest — the architecture is broad, interconnected, and often overwhelming. That’s why we created a mental map: to make sense of it all.
Think of this blog as your home base. It won’t explain everything, but it gives you the whole picture. Future posts will go deep into each block. For now, use this to structure your understanding.
🗺️ Microservices Architecture Mental Map
└── MICROSERVICES ARCHITECTURE (Independent, Scalable, Resilient Services)
├── DESIGN & DECOMPOSITION (How to break down and structure services)
│ ├── Principles
│ │ ├── Conway's Law (Organizational structure influences design)
│ │ └── Single Responsibility Principle (SRP)
│ ├── Decomposition Strategies
│ │ ├── Decompose by Subdomain (Domain-Driven Design)
│ │ ├── Decompose by Business Capability
│ │ └── Strangler Fig Pattern (Migration from Monolith)
│ │ └── Branch by Abstraction
│ └── Service Granularity
│ └── Database per Service (Each service owns its data)
├── COMMUNICATION (How services interact)
│ ├── Synchronous (Direct, real-time)
│ │ ├── RESTful APIs (HTTP/JSON)
│ │ └── gRPC (High-performance RPC)
│ ├── Asynchronous (Event-driven, message-based)
│ │ ├── Message Queues (e.g., RabbitMQ, Kafka)
│ │ └── Event Bus
│ ├── API Management
│ │ ├── API Gateway (Routing, Authentication, Rate Limiting, Aggregation)
│ │ │ └── Backends for Frontends (BFF)
│ │ └── API Versioning
│ ├── Service Discovery
│ │ ├── Client-side Discovery (e.g., Eureka client)
│ │ └── Server-side Discovery (e.g., Consul, Kubernetes DNS)
│ ├── Load Balancing
│ │ └── Client-side Load Balancing
│ └── Service Mesh (Infrastructure layer for inter-service communication)
│ ├── (e.g., Istio, Linkerd, Envoy)
│ ├── Traffic Management (Routing, Retries, Timeouts)
│ ├── Policy Enforcement
│ └── Observability Integration
├── DATA MANAGEMENT (Ensuring consistency and integrity in distributed data)
│ ├── Data Ownership (Service owns its data)
│ ├── Consistency Models
│ │ └── Eventual Consistency (Data consistent over time)
│ ├── Distributed Transactions
│ │ └── Saga Pattern (Long-running business processes)
│ │ ├── Orchestration-based Saga
│ │ └── Choreography-based Saga
│ ├── Data Patterns
│ │ ├── CQRS (Command Query Responsibility Segregation)
│ │ └── Event Sourcing (Immutable event log as source of truth)
│ └── Idempotent Consumers/Producers (Handling duplicate messages)
├── RESILIENCE (Making services robust against failures)
│ ├── Fault Tolerance
│ ├── Circuit Breaker (Preventing cascading failures)
│ ├── Retry / Timeout (Handling transient failures)
│ ├── Bulkhead (Resource isolation)
│ ├── Fallback (Providing alternative responses)
│ └── Rate Limiting (Controlling request volume)
├── OBSERVABILITY (Understanding system behavior)
│ ├── Monitoring (Metrics collection and visualization)
│ │ └── Prometheus, Grafana
│ ├── Logging (Centralized log aggregation)
│ │ └── ELK Stack (Elasticsearch, Logstash, Kibana)
│ ├── Tracing (Following requests across services)
│ │ └── Zipkin, Jaeger
│ ├── Health Checks (Service readiness and liveness)
│ └── Alerting (Notifying on anomalies)
├── SECURITY (Protecting microservices)
│ ├── Authentication (Verifying identity)
│ │ ├── OAuth 2.0 / OpenID Connect (OIDC)
│ │ └── JWT (JSON Web Tokens)
│ ├── Authorization (Controlling access)
│ │ └── Role-Based Access Control (RBAC)
│ ├── API Keys / Tokens
│ └── Secure Communication (TLS/SSL)
├── DEPLOYMENT & OPERATIONS (Building, deploying, and running services)
│ ├── Containerization (Packaging applications)
│ │ └── Docker
│ ├── Container Orchestration (Managing containers at scale)
│ │ └── Kubernetes, ECS, Nomad
│ ├── CI/CD Pipelines (Automated build, test, deploy)
│ │ └── Jenkins, GitHub Actions, Argo CD
│ ├── Deployment Strategies
│ │ ├── Blue-Green Deployments
│ │ └── Canary Deployments
│ ├── Scaling
│ │ ├── Autoscaling (Horizontal Pod Autoscaler - HPA)
│ │ └── Self-Healing
│ └── Serverless Functions (FaaS)
│ └── AWS Lambda, Google Cloud Run
└── CROSS-CUTTING CONCERNS (Shared functionalities)
├── Centralized Configuration (Externalized configuration management)
│ └── Spring Cloud Config, Vault
└── Feature Toggles / Flags (Dynamically enabling/disabling features)📌 Conclusion
This map is not just documentation — it’s a compass. Use it to navigate discussions, architecture reviews, interviews, or system planning sessions.
We’ll break each section down with deep dives and real-world examples in upcoming posts. Bookmark this, share it with your team, and revisit it whenever the architecture starts feeling like chaos.
Stay tuned. Byte by Byte.
