1. SARAVANAN G
Principle Engineer
March 10, 2015
Microsoft Azure
Service Fabric Architecture

2. Agenda
• Application development
• Azure Service Fabric
• Microservices
• Reliability & scale-out
• Lifecycle management
• Q&A

3. Application development
Features
Scalability
Availability
Latency
Lifecycle
Data Integrity
Portability
Manage Services
Deliver Features Faster
Create Business Value
Scalability
Availability
Latency
Lifecycle
Data Integrity
Portability

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

7. Applications runs on Service Fabric

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

9. 
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12. Queues Storage
Front End
(Stateless
Web)
Stateless
Middle-tier
Compute
Cache
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Load Balancer

13. Stateful
Middle-tier
Compute
Stateful services: Simplify design, reduce latency
Front End
(Stateless
Web)
data stores used for analytics and disaster recovery
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Load Balancer

14. Microservices

16. Node
Node
Node
Node
Node
Node

17. Time =
t1
83
76 50
46
64 New Node arrived61
Time =
t2
83
61
50 46
Failures
Detected
cluster reconfigured
83
76
64
50
46
Time =
t0
Nodes failed

20. System Services
Failover
manager
Cluster
manager
Naming
Image
store

23.  replica set

linearized read
write
 Read-Write quorums
 Replica set

24. Microservices

26. 
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P
S
S
S
S
WriteWrite
Write
Write
AckAck Ack
Ack
Read
Value Write
Ack

27.  Types of reconfiguration
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 Replica
States
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P
S
S
S
S
S
Must be safe in the presence
of cascading failures
B P
X
Failed
X
Failed

28. Node 103
P
S
S
Node 104
S
S
Node 102
P
S
S
S
Node 105
P
S
S
S
Node 101
S
S
P
Node 100
S
P
S
S
P
S
S
S

29. Microservices

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32. Microservices