4. Traditional and Microservices
User Interface
Business Logic
Data
User Interface
Business Logic
Data
Features
Scalability
Manage Services
Deliver Features Faster
Create Business Value
Availability
Latency
Lifecycle
Data Integrity
Portability
5. • Scales by cloning the app on multiple
servers/VMs/Containers
Monolithic application approach Microservices application approach
• A microservice application
separates functionality into
separate smaller services.
• Scales out by deploying each service
independently creating instances of these services
across servers/VMs/containers
• A monolith app contains domain
specific functionality and is
normally divided by functional
layers such as web, business and
data
App 1 App 2App 1
6. Azure Cloud Services
(Web and Worker Roles)
Azure Service Fabric
(Stateless, stateful or Actor services)
• 1 service instance per VM with uneven workloads
• Lower compute density
• Slow in deployment & upgrades
• Slower in scaling and disaster recovery
• Many microservices per VM
• High microservices density
• Fast deployment & upgrades
• Fast scaling microservices across the cluster
8. Microservices
Azure
Windows
Server
Linux
Hosted Clouds
Windows
Server
Linux
Service Fabric
Private Clouds
Windows
Server
Linux
High Availability
Hyper-Scale
Hybrid Operations
High Density Rolling Upgrades
Stateful services
Low Latency
Fast startup &
shutdown
Container Orchestration
& lifecycle management
Replication & Failover
Simple
programming
models
Load balancing
Self-healingData Partitioning
Automated Rollback
Health
Monitoring
Placement
Constraints