The document discusses the advantages of microservices over monolithic applications, emphasizing improved scalability, autonomy, and developer efficiency. It contrasts traditional and microservices approaches in application development, highlighting the benefits such as resilience, selective scaling, and fault isolation. The role of Azure Service Fabric in managing microservices and enhancing resource utilization is also examined.

1. Mukul Jain
Head of Xpirit India
XEBIA

2. Something Interesting is Happening …..

3. Digital Disruption is Better and Faster

4. Speed Up and Scale Up

5. Technology Evolution
Microservices == SOA Done Right == Scalability?

6. App 1
Traditional approach Microservices approach
• A micro service application
separates functionality into
separate smaller services.
• A monolithic application has most
of its functionality within a few
processes.
• Scales by cloning the app on
multiple servers / VMs / Containers
• Scales by deploying each service
independently creating instances of these
services across servers/VMs/containers
App 1 App 2

7. • Single monolithic database
• Tiers of specific technologies
State in Traditional approach State in Microservices approach
• Graph of interconnected microservices
• State typically scoped to the microservice
• Variety of technologies used
• Remote Storage for cold data
stateless services with
separate stores
stateful
services
stateless
presentation
services
stateless
services

8. What is Microservice?
Autonomous Service
Contain code plus state
Interact with other microservices over well defined interfaces
Remain Consistent and Available in the presence of Failures
• Autonomy
• High cohesion
• Low coupling

9. Developer Dependencies
For a monolith to change,
all must agree on each
change. Each change has
unanticipated effects
requiring careful testing
beforehand.
Developers can create and
activate new microservices
without prior coordination with
others. Their adherence to MSA
principles makes continuous
delivery of new or modified
services possible.
Elements in SOA are
developed more autonomously
but must be coordinated with
others to fit into the overall
design.

10. Microservice

11. Benefits
Any
Language and
framework
Resilience
against
failure
Selective
scaling
Deployment
of smaller
pieces with
lower risk
Alignment
with
Organization
• Small Focused
Teams
Improved
Resource
Utilization to
reduce cost
Fault
Isolation
Servers
Treated as
cattle, not
pets

13. Service FabricHigh Availability
Hyper-Scale
Hybrid Operations
High Density
Microservices
Rolling Upgrades
Stateful Services
Low Latency
Fast Startup &
Shutdown
Code Orchestration &
Lifecycle Management
Replication & FailoverSimple
programming
models
Resource Management
Self-healingData Partitioning
Automated Rollback
Health Monitoring
Placement
Constraints
Azure Private cloud Other clouds

14. Azure Cloud Services
(Web and Worker Roles)
Azure Service Fabric
(Stateless, stateful or Actor services)
• 1 role instance per VM
• Uneven utilization
• Slow deployment & upgrade (bound to VM)
• Slow scaling and failure recovery
• Many microservices per VM
• Even Utilization (by default, customizable)
• Fast deployment & upgrade
• Fast scaling of independent microservices

15. Windows OS
Windows OS Windows OS
Windows OS
Windows OS
Windows OS
Fabric
Node
Fabric
Node
Fabric
Node
Fabric
Node
Fabric
Node
Fabric
Node
Linux Support
Java Support
On Premises Clusters

16. App1 App2
App Type Packages Service Fabric Cluster VMs
Handling Machine Failures

17. App1 App2
App Type Packages Service Fabric Cluster VMs
Handling Machine Failures

18. Stateful Microservices - Replication
Primary
Secondary
Replication
Service Fabric Cluster VMs

19. Windows OS
Windows OS Windows OS
Windows OS
Windows OS
Windows OS
Fabric
Node
Fabric
Node
Fabric
Node
Fabric
Node
Fabric
Node
Fabric
Node
App B v2
App B v2
App B v2
App A v1
App A v1
App A v1
App C v1
App C v1
App C v1
App Repository
App A v1
App C v1
App B v2
App C v2
App C v2
App C v2
App C v2

20. Node 5Node 4Node 3 Node 6Node 2Node 1
P2
S
S
S
P4
S
P1
S
P3S
S
S
• Services can be partitioned for scale-out.
• You can choose your own partitioning scheme.
• Replicas automatically scale out & in on cluster changes

21. Performance and stress response
•Rich built-in metrics for Actors and Services programming models
•Easy to add custom application performance metrics
Health status monitoring
•Built-in health status for cluster and services
•Flexible and extensible health store for custom app health reporting
•Allows continuous monitoring for real-time alerting on problems in
production

23. Services built with Service Fabric

25. : Speed Up and Scale UpTakeaways