Microservices Mastery Syllabus (Spring Cloud + Azure + AWS + Docker + K8s + DevOps)

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Phase 1 – Core Architecture Foundations

1.1 Domain-Driven Design (DDD)
1.1.1 Strategic Design – Bounded Contexts
1.1.2 Ubiquitous Language
1.1.3 Aggregates, Entities, Value Objects
1.1.4 DDD in code with Spring Boot

1.2 Monolith vs Microservices
1.2.1 Pros/Cons of both
1.2.2 Transition patterns (Modular monolith → MS)

1.3 Stateless Services & HTTP Lifecycle
1.3.1 HTTP 1.1 / 2 / 3.0
1.3.2 Keep-Alive, Pipelining
1.3.3 Stateless authentication (JWT, Cookies)

1.4 Service Decomposition
1.4.1 Decompose by business capability
1.4.2 Bounded Context mapping
1.4.3 Service granularity & anti-patterns

1.5 API Gateway Pattern
1.5.1 Spring Cloud Gateway setup
1.5.2 Route filters, CircuitBreaker, JWT validation
1.5.3 External API Gateway (Azure APIM / AWS API GW)

1.6 Database-per-Service
1.6.1 Shared Nothing Principle
1.6.2 Schema design per microservice
1.6.3 Data duplication vs Sync strategies

1.7 Spring Boot Microservices
1.7.1 Controller → Service → Repo layers
1.7.2 DTOs, Mappers, Entities
1.7.3 Clean Architecture + SOLID Principles

1.8 Communication Fundamentals
1.8.1 REST + gRPC overview
1.8.2 OpenAPI spec, Swagger

1.9 Project Structure Standards
1.9.1 Gradle vs Maven
1.9.2 Feature vs Layer-based structure
1.9.3 Packaging best practices

Phase 2 – Communication Patterns

2.1 Synchronous Communication
2.1.1 Feign Client setup (Spring Boot)
2.1.2 WebClient (Reactive)
2.1.3 Load Balancing via Eureka + Ribbon

2.2 Resilience Patterns
2.2.1 Retry, Timeout, Circuit Breaker (Resilience4j)
2.2.2 Bulkhead pattern
2.2.3 Fallback mechanisms

2.3 Asynchronous Messaging
2.3.1 Kafka, RabbitMQ, NATS
2.3.2 Producers, Consumers
2.3.3 Message serialization, headers

2.4 Event Delivery Design
2.4.1 DLQ (Dead Letter Queue)
2.4.2 Replay and Deduplication
2.4.3 Message Ordering, Partitioning

2.5 Event Types
2.5.1 Integration Events vs Domain Events
2.5.2 Schema governance (Avro, JSON Schema)

2.6 Outbox Pattern
2.6.1 DB change → Event trigger
2.6.2 Outbox polling mechanism
2.6.3 Idempotency

2.7 Distributed Transactions
2.7.1 SAGA Pattern – Choreography
2.7.2 SAGA Pattern – Orchestration
2.7.3 Tools: Camunda, Temporal, Axon

2.8 Service Discovery
2.8.1 Spring Eureka Server & Client
2.8.2 AWS Cloud Map
2.8.3 Azure App Registration

2.9 Centralized Config
2.9.1 Spring Cloud Config Server
2.9.2 Git-backed configuration
2.9.3 Azure App Config / AWS SSM

Phase 3 – Event-Driven & Reactive Architecture

3.1 Event Sourcing
3.1.1 ES vs CRUD
3.1.2 Event Store concepts
3.1.3 Append-only pattern

3.2 Reactive Messaging
3.2.1 Reactor, ProjectReactor, WebFlux
3.2.2 Kafka with reactive consumers
3.2.3 Backpressure handling

3.3 CQRS
3.3.1 Command + Query segregation
3.3.2 Write DB vs Read DB
3.3.3 CQRS + Event Sourcing combined

3.4 Consistency
3.4.1 Eventual consistency
3.4.2 Compensating transactions

3.5 Event Publishing Strategy
3.5.1 Domain events
3.5.2 Integration events
3.5.3 Aggregate Root event publishing

3.6 Event Testing & Monitoring
3.6.1 TestContainers for Kafka
3.6.2 Spring Cloud Stream testing
3.6.3 Event observability

Phase 4 – Scaling & Throughput

4.1 Scaling Strategies
4.1.1 Horizontal, Vertical
4.1.2 Kubernetes HPA/VPA
4.1.3 Azure AutoScale / AWS AutoScale

4.2 Load Balancing
4.2.1 Ribbon
4.2.2 Server-side LB (Ingress, ALB)
4.2.3 API Gateway LB

4.3 Queue-based Load Leveling
4.3.1 Message buffering
4.3.2 Kafka backpressure handling

4.4 Rate Limiting
4.4.1 Bucket4j + Redis
4.4.2 API Gateway-based rate limits

4.5 Partitioning & Sharding
4.5.1 Kafka Partition logic
4.5.2 DB Sharding strategies
4.5.3 Tenant-based partitioning

4.6 Polyglot Persistence
4.6.1 MySQL, PostgreSQL
4.6.2 MongoDB, Cassandra
4.6.3 Redis as cache layer

4.7 Caching Strategy
4.7.1 Redis + Spring Cache
4.7.2 Caffeine, In-memory
4.7.3 Cache invalidation strategy

Phase 5 – Resilience & Chaos Engineering

5.1 Resilience4j Patterns
5.1.1 Retry
5.1.2 CircuitBreaker
5.1.3 Bulkhead
5.1.4 RateLimiter

5.2 Timeout & Fallback
5.2.1 Reactive timeout
5.2.2 Blocking timeout
5.2.3 Resilient fallback methods

5.3 Chaos Testing
5.3.1 Gremlin setup
5.3.2 LitmusChaos on K8s

5.4 Graceful Degradation
5.4.1 Static fallback response
5.4.2 Reduced functionality paths

5.5 Fail-fast Design
5.5.1 Service isolation
5.5.2 Pre-checks and short-circuit logic

Phase 6 – Security & Governance

6.1 OAuth2 & OIDC
6.1.1 Spring Security integration
6.1.2 Keycloak setup
6.1.3 Token storage & introspection

6.2 JWT Token
6.2.1 Access Token vs ID Token
6.2.2 Token propagation via Gateway

6.3 Role-Based Access Control
6.3.1 Method-level security
6.3.2 Scopes and permissions

6.4 Secrets Management
6.4.1 Spring Vault
6.4.2 Azure Key Vault
6.4.3 AWS Secrets Manager

6.5 Encryption
6.5.1 Field-level encryption
6.5.2 Hashing (SHA256, Bcrypt)

6.6 Compliance
6.6.1 GDPR, HIPAA handling
6.6.2 Data masking & auditing
6.6.3 Consent logs

Phase 7 – API Design & Versioning

7.1 API Versioning
7.1.1 URI based
7.1.2 Header based
7.1.3 Query Param based

7.2 OpenAPI / Swagger
7.2.1 SpringDoc setup
7.2.2 API grouping & filtering

7.3 Contract Testing
7.3.1 Pact setup
7.3.2 Consumer-driven contracts

7.4 Schema Governance
7.4.1 JSON Schema
7.4.2 Avro / Protocol Buffers

7.5 Mocking & Stubbing
7.5.1 WireMock
7.5.2 SwaggerHub examples

7.6 Gateway Caching
7.6.1 Spring Gateway
7.6.2 Azure APIM cache policies

7.7 Rate Quotas
7.7.1 Per-consumer rate limiting
7.7.2 API Key throttling

Phase 8 – Dockerization & Containerization

8.1 Docker Basics
8.1.1 Docker CLI
8.1.2 Docker Images, Containers
8.1.3 Dockerfile creation for Spring Boot apps

8.2 Docker Best Practices
8.2.1 Multi-stage builds
8.2.2 Image size optimization
8.2.3 .dockerignore, health checks

8.3 Local Dev with Docker Compose
8.3.1 Compose file for MS bootstrap
8.3.2 Networking containers
8.3.3 Volumes for persistence

8.4 Docker Networking
8.4.1 Bridge vs Host
8.4.2 Container-to-container communication

8.5 Docker Security
8.5.1 Image scanning (Trivy, Snyk)
8.5.2 Secrets injection into containers

8.6 Docker Registries
8.6.1 DockerHub
8.6.2 GitHub Container Registry
8.6.3 AWS ECR / Azure ACR

Phase 9 – Kubernetes Fundamentals

9.1 Core Concepts
9.1.1 Pods, ReplicaSets, Deployments
9.1.2 StatefulSets, DaemonSets

9.2 Service Management
9.2.1 ClusterIP, NodePort, LoadBalancer
9.2.2 Headless Services

9.3 Configuration
9.3.1 ConfigMaps
9.3.2 Secrets (base64, external secret stores)

9.4 Health Probes
9.4.1 Liveness
9.4.2 Readiness
9.4.3 Startup probes

9.5 RBAC & Security
9.5.1 Role, RoleBinding
9.5.2 ServiceAccount

9.6 Auto Scaling
9.6.1 Horizontal Pod Autoscaler (HPA)
9.6.2 Vertical Pod Autoscaler (VPA)

9.7 Node Scheduling
9.7.1 Node affinity/anti-affinity
9.7.2 Taints and tolerations

9.8 Namespace Isolation
9.8.1 Resource quotas
9.8.2 Network segmentation

Phase 10 – Helm, Ingress & Advanced K8s

10.1 Helm Basics
10.1.1 Chart structure
10.1.2 values.yaml overrides
10.1.3 Helm repo management

10.2 Ingress Management
10.2.1 NGINX Ingress Controller
10.2.2 Traefik as alternative
10.2.3 TLS with Let's Encrypt

10.3 Deployment Strategies
10.3.1 Rolling updates
10.3.2 Blue-Green Deployment
10.3.3 Canary Deployment

10.4 Advanced K8s Resources
10.4.1 CronJobs
10.4.2 Init Containers
10.4.3 Sidecars

10.5 Network Policies
10.5.1 Ingress/Egress rules
10.5.2 Isolation for zero trust

10.6 SecurityContext & PodSecurity
10.6.1 Drop Linux Capabilities
10.6.2 ReadOnlyRootFilesystem
10.6.3 RunAsNonRoot

Phase 11 – CI/CD, GitOps & Automation

11.1 CI/CD Basics
11.1.1 Jenkins pipelines
11.1.2 GitHub Actions
11.1.3 GitLab CI

11.2 GitOps Approach
11.2.1 ArgoCD
11.2.2 FluxCD
11.2.3 Sync, rollback, auto PR sync

11.3 Build Automation
11.3.1 Docker build & push
11.3.2 Maven/Gradle workflows

11.4 Helm & Kustomize
11.4.1 Helm CI/CD integration
11.4.2 Environment overlays with Kustomize

11.5 Secret Management in CI/CD
11.5.1 Sealed Secrets
11.5.2 External Vault Integration

11.6 Canary Automation
11.6.1 Argo Rollouts
11.6.2 Progressive delivery

11.7 Infra as Code
11.7.1 Terraform
11.7.2 Pulumi
11.7.3 Azure Bicep

Phase 12 – Cloud-Native Deployment (Azure, AWS, GCP)

12.1 Azure
12.1.1 AKS (Azure Kubernetes Service)
12.1.2 Azure Spring Apps
12.1.3 Azure Monitor, ACR, Key Vault, CosmosDB

12.2 AWS
12.2.1 EKS, ECS, Fargate
12.2.2 RDS, DynamoDB, Secrets Manager
12.2.3 CloudWatch, SQS/SNS, CodePipeline

12.3 GCP
12.3.1 GKE (Kubernetes)
12.3.2 CloudSQL, Pub/Sub, Secret Manager
12.3.3 Stackdriver for logs & metrics

12.4 Cost Optimization
12.4.1 Reserved vs Spot Instances
12.4.2 Auto-scaling thresholds
12.4.3 Monitoring spend

Phase 13 – Data Engineering & Multitenancy

13.1 DB Choices
13.1.1 PostgreSQL, MySQL, MariaDB
13.1.2 MongoDB, Cassandra, Couchbase

13.2 CDC & Sync
13.2.1 Kafka Connect
13.2.2 Debezium
13.2.3 Real-time replication

13.3 Multi-Tenancy
13.3.1 Shared schema
13.3.2 Isolated schema
13.3.3 Hybrid models

13.4 Security & Compliance
13.4.1 Row-level security
13.4.2 Auditing & Logging
13.4.3 Field-level masking

13.5 Schema Versioning
13.5.1 Flyway
13.5.2 Liquibase

Phase 14 – Service Mesh, Platform Engineering & AI

14.1 Service Mesh
14.1.1 Istio basics
14.1.2 Linkerd intro
14.1.3 mTLS, Telemetry, Traffic splitting

14.2 Envoy Proxy
14.2.1 Sidecar pattern
14.2.2 Protocol translation
14.2.3 Rate limiting and observability

14.3 API Management
14.3.1 Kong Gateway
14.3.2 Apigee
14.3.3 Spring vs Cloud API Gateways

14.4 Internal Developer Platforms (IDP)
14.4.1 Backstage setup
14.4.2 Developer self-service flows
14.4.3 Golden paths

14.5 AI/ML Ops
14.5.1 Smart routing decisions
14.5.2 AI-based anomaly detection
14.5.3 Logging intelligence

14.6 Legacy Integration
14.6.1 Anti-corruption layer
14.6.2 Event adapters
14.6.3 SOAP to REST proxying

Phase 15 – Real-World Projects & Case Studies

15.1 E-Commerce Platform
15.1.1 Product + Order + Cart + Payment
15.1.2 Gateway, Saga, Outbox

15.2 Ride Booking Platform
15.2.1 Kafka + Event Tracing
15.2.2 Dynamic pricing logic

15.3 Payment Gateway
15.3.1 Idempotency
15.3.2 Transactional outbox

15.4 Billing System
15.4.1 CQRS
15.4.2 Retry + Deduplication

15.5 Monitoring Dashboard
15.5.1 Prometheus + Grafana
15.5.2 Alerting + SLOs

Phase 16 – Full Deployment Blueprints

16.1 Spring Cloud VM-based
16.1.1 Spring Gateway + Eureka + Config
16.1.2 Docker + K8s (Minikube/K3s)
16.1.3 GitHub Actions → DockerHub → K8s

16.2 Azure AKS & Azure Spring Apps
16.2.1 AKS Infra + ACR
16.2.2 CI/CD via Azure DevOps
16.2.3 App Insights, Key Vault, APIM

16.3 AWS ECS/EKS
16.3.1 Fargate deployment
16.3.2 GitHub Actions / CodePipeline
16.3.3 CloudWatch, X-Ray, Route53