1. Build 2015
4/26/2018 6:17 AM
Building Resilient, Scalable Services with Microsoft Azure Service Fabric
Érsek Attila
@ersekattila
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

2. Challenges

3. Common Cloud Service Architecture
Compute
(Stateful?)
Frontend/API/Gateway
(Stateless)
Network
Load-balancer
Web Server
Storage
(Stateful)

4. Common Cloud Service Architecture
TechReady 18
4/26/2018
Common Cloud Service Architecture
Attempting to scale…
Compute
(Stateful?)
Gateway
(Stateless)
Network
Load-balancer
Web Server
(Web Role) …
(Worker Role)
Storage
(Stateful)
Cache
© 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

5. Common Cloud Service Architecture
TechReady 18
4/26/2018
Common Cloud Service Architecture
Attempting to Increase Reliability…
Compute
(Stateful?)
Gateway
(Stateless)
Network
Load-balancer
Web Server
(Web Role) …
(Worker Role)
Storage
(Stateful)
DB (P1)
DB (P2)
DB (N)
Queue
Cache
Services become complex with many moving parts
© 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

6. Challenges with PaaS High Availability and Reliability Scale
“All my worker roles are up but my service is down!”
Scale
Scaling up and Down for performance vs. costs
Performance and Latency
Read and Write Performance
Management
Managing Resource Utilization & Application Lifecycle
Portability
Run the same application on my dev box, Windows Server, Azure
Complexity
Many different components to manage and maintain

7. Service Fabric
PaaS Evolved

8. Azure Service Fabric platform Applications and microservices
Build 2015
4/26/2018 6:17 AM
Azure Service Fabric platform
Applications and microservices
Programming models
Scaling
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9. 4/26/2018
Microsoft Azure Service Fabric A platform for reliable, hyperscale, microservice-based applications
microservices
Service Fabric
Health Monitoring
Container Orchestration & lifecycle management
High Availability
Hybrid Operations
Data Partitioning
Self-healing
Simple programming models
High Density
Rolling Upgrades
Low Latency
Placement Constraints
Fast startup & shutdown
Replication & Failover
Load balancing
Hyper-Scale
Automated Rollback
Stateful services
Private Clouds
Windows
Server
Linux
Azure
Windows
Server
Linux
Hosted Clouds
Windows
Server
Linux
© 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

10. Battle-hardened for over 5 years
4/26/2018
Battle-hardened for over 5 years
Skype for Business
Hybrid Ops
Azure Document DB
billions transactions/week
Intune
800k devices
Azure Core Infrastructure
thousands of machines
Event Hubs
20bn events/day
Bing Cortana
500m evals/sec
Azure SQL Database
1.4 million databases
Power BI
© 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

11. Typical datacenter A set of independent machines; physical or virtual
Build 2015
4/26/2018 6:17 AM
Typical datacenter
A set of independent machines; physical or virtual
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

12. Cluster: A federation of machines
Build 2015
4/26/2018 6:17 AM
Cluster: A federation of machines
A set of machines that Service Fabric stitches together to form a cluster
Clusters can scale to
1000s of machines
Node
Node
Node
Node
Node
Node
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

13. Cluster: System view System Services Failover manager Cluster Naming
Build 2015
4/26/2018 6:17 AM
Cluster: System view
System Services
Failover
manager
Cluster
Naming
Image
store
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

14. Build 2015
4/26/2018 6:17 AM
What is a microservice?
Is (logic + state) that is independently versioned, deployed, and scaled
Has a unique name that can be resolved
e.g. fabric:/myapplication/myservice
Interacts with other microservices over well defined interfaces and protocols like REST
Remains always logically consistent in the presence of failures
Hosted inside a “container” (code + config)
Can be written in any language and framework
node.js, Java VMs, any EXE
Developed by a small engineering team
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

15. Types of microservices
Build 2015
4/26/2018 6:17 AM
Types of microservices
Stateless microservice
Has either no state or it can be retrieved from an external store
There can be N instances
e.g. web frontends, protocol gateways, Azure Cloud Services etc.
Stateful microservice
Maintain hard, authoritative state
N consistent copies achieved through replication and local persistence
e.g. database, documents, workflow, user profile, shopping cart etc.
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

16. Programming Models

17. Runtime APIs Levels & Capabilities
Reliable Actors
[ ]
IoT Applications, Halo…
Reliable Services
[ ]
Current Enterprise Developers…
Reliable Collections
[ ]
InTune, …
State Management APIs
[ ]
Doc DB, Lync…
Replica Set Management APIs
[ ]
SQL Azure
Provided by Platform
Provided by User
Replica Set Management
State
Replication
State
Storage
Messaging
[ ]
Programming Model
Business Logic

18. Reliable Actors Stateless or Stateful Virtual Actors
Single Threaded by Default
Re-entrancy options
Timers and Reminders
public class Voic BoxActor : Voic BoxActorBase {
public override Task<List<Voic >> GetMessagesAsync()
return Task.FromResult(this.State.MessageList); }
public override Task LeaveMessageAsync(string message)
this.State.MessageList.Add(
new Voic ()
Id = Guid.NewGuid(),
Message = message,
ReceivedAt = DateTime.Now
});
return Task.FromResult(true);

19. Reliable Services
More control over data partitioning so you can determine data relationships and consistency requirements between chunks of state
Multithreaded
More likely to BYO transport S1 S3
Client S2 S4

20. TechReady 18
4/26/2018
Reliable Collections
Use our replicated datastructures or build your own
Single Machine Multi-Machine
Reliable Collections
Multi-Node
Replicated (HA)
Persistence Option
Asynchronous
Transactional
Concurrent Collections
Multi-Threaded
Collections
Single Threaded
Dictionary<TKey, TValue> ConcurrentDictionary<TKey, TValue> ReliableDictionary, Tvalue>
© 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

21. High Availability, Low Latency, and Scale
Compute
(Stateful?)
Gateway
(Stateless)
Network
Load-balancer
Web Server
(Web Role) …
(Worker Role)
Storage
(Stateful)
DB (P1)
DB (P2)
DB (P3)
Queue
Cache
Conventionally data is made highly available with external storage.
Scale is achieved by scaling out stateless front ends and affinitization to workers
Latency is caused by many network hops and data layer contention at scale.

22. High Availability, Density, Low Latency, and Scale
Compute
(Stateful
and
Highly
Reliable) …
Network
Load-balancer
Stateless Gateway
Stateful Worker
Code & State
Stateful Workers used for “hot” data to minimize contention and network hops External Storage used for “cold” data such as analytics
Storage
ElasticSearch
DataLake