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Gopal KakivayaCorporate Vice President
Microsoft Azure Service Fabric Architecture
2-640
Agenda
• Application development • Azure Service Fabric• Microservices• Reliability & scale-out• Lifecycle management• Summary
Application development in the age of the Cloud
FeaturesScalability
Manage ServicesDeliver Features FasterCreate Business Value
AvailabilityLatencyLifecycleData IntegrityPortability
Cloud Service Architectures
traditional
User Interface
Business Logic
Data
User Interface
Business Logic
DataMicroservices
FeaturesScalability
Manage ServicesDeliver Features FasterCreate Business Value
AvailabilityLatencyLifecycleData IntegrityPortability
Microsoft Azure Service FabricA platform for reliable, hyperscale, microservice-based applications
Microservices
Application Programming Models
Azure
WindowsServer Linux
Hosted Clouds
WindowsServer Linux
Service Fabric
Private Clouds
WindowsServer Linux
High Availability
Hyper-Scale
Hybrid Operations
High Density
Rolling Upgrades Stateful
services
Low Latency Fast startup & shutdown
Container Orchestration & lifecycle management Replication &
FailoverSimple
programming models
Load balancing
Self-healingData Partitioning
Automated Rollback
Health Monitoring
Placement Constraints
Battle-hardened for over 5 years
Azure Core Infrastruct
ure
thousands of machines
Power BI
Intune
800k devices
Azure SQL
Database
1.4 million databases
Bing Cortana
500m evals/sec
Azure Documen
t DB
billions transactions/wee
k
Skype for
Business
Hybrid Ops
Event Hubs20bn
events/day
Microsoft Azure Service FabricA platform for reliable, hyperscale, microservice-based applications
Microservices
Communication
Management Reliability HostingSubsystem
Testability
Federation
Transport
Application Programming Models
Azure
WindowsServer Linux
Hosted Clouds
WindowsServer Linux
Service Fabric
Private Clouds
WindowsServer Linux
High Availability
Hyper-Scale
Hybrid Operations
High Density
Rolling Upgrades Stateful
services
Low Latency Fast startup & shutdown
Container Orchestration & lifecycle management Replication &
FailoverSimple
programming models
Load balancing
Self-healingData Partitioning
Automated Rollback
Health Monitoring
Placement Constraints
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
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.
Stateless microserviceDemo
Federation and transport subsystems
Communication
subsystem
Reliabilitysubsystem
Activationsubsystem
TestabilitysubsystemFederation
Transport
Application Programming Models
Microservices
Managementsubsystem
A set of independent machines; physical or virtual
Typical datacenter
A set of machines that Service Fabric stitches together to form a cluster
Clusters can scale to1000s of machines
Cluster: A federation of machines
Node
Node
Node
Node
Node
Node
Machine failure detection
Time = t1
83 76 50 4664 New Node arrived61
Time = t2
8361
50 46Failures Detected
cluster reconfigured
83 76 6450 46
Time = t0
Nodes failed
Cluster: System viewSystem Services Failover manager
Cluster manager
Naming
Image store
Service Fabric ExplorerDemo
Reliability and hosting subsystems
Communication
subsystem
Managementsubsystem
Reliabilitysubsystem
Hostingsubsystem
TestabilitysubsystemFederation
Transport
Application Programming Models
Microservices
Queues Storage
3-Tier service pattern
Front End(StatelessWeb)
StatelessMiddle-tierCompute
Cache
• Scale with partitioned storage
• Increase reliability with queues
• Reduce read latency with caches
• Manage your own transactions for state consistency
• Many moving parts each managed differently
Load Balancer
StatefulMiddle-tierCompute
Stateful services: Simplify design, reduce latency
Front End(StatelessWeb)
data stores used for analytics and disaster recovery
• Application state lives in the compute tier
• Low Latency reads and writes
• Partitions are first class for scale-out
• Built in transactions
• Fewer moving parts
Load Balancer
Stateful microserviceDemo
• Each service is backed by replica set to make its internal state reliable
• All replicas are logically consistent – meaning all replicas see the same linearized order of read and write operations to initial state
• Read-Write quorums are supported and are dynamically adjusted
• Replica set is dynamically reconfigured to account for replica arrivals and departures
Stateful microservices are reliable and consistent
Stateful microserviceApplication Package
PSSreplication
replication
PSS
Replication• Reads are completed
at the primary• Writes are replicated to
the write quorum of secondaries P
S
S
S
SWriteWrite
WriteWrite
AckAck AckAck
ReadValue WriteAck
Reconfiguration• Types of reconfiguration
• Primary failover• Removing a failed
secondary • Adding recovered
replica• Building a new
secondary
• Replica States• None• Idle Secondary • Active Secondary• Primary
P
S
S
S
S
S
Must be safe in the presence of cascading failures
B PXFailed
XFailed
Microservices placement and failover
Node 103
P
SS
Node 104
SS
Node 102
P
SS
S
Node 105
PSSS
Node 101
SS
P
Node 100
S
PS
S
P
SS
S
Cluster MonitorDemo
Application Lifecycle Management
Communication
subsystem
Managementsubsystem
Reliabilitysubsystem
Hostingsubsystem
TestabilitysubsystemFederation
Transport
Application Programming Models
Microservices
Application: logical grouping of microservices
Application Contain
erContain
er
Container
Container
• Provisioning and deployment of constituent microservices
• Upgrade microservices without loss of availability• Monitor microservices • Interface with machine management layer for
autoscale and initiating reboot, reimage, and repair actions
• Provide operational insight into aggregate utilization – inventory, performance counters/metrics, etc. – for capacity planning
Application Lifecycle Management
No Downtime UpgradeDemo
Upgrading Services with zero downtimeApplication Package
FD0/UD0
FD0/UD1
FD1/UD6
FD1/UD5
FD2/UD4
FD2/UD3
Testability subsystem
Communication
subsystem
Managementsubsystem
Reliabilitysubsystem
Hostingsubsystem
TestabilitysubsystemFederation
Transport
Application Programming Models
Microservices
Automatic Orchestration
Hybrid Operation
Self-Healing
Self-sufficient
Comprehensive
The same technology Microsoft uses
Proven more than 5 years
Investment & Roadmap
Stateless or Stateful
Visual Studio tools
Focus on features not infrastructure
Rolling upgrades
Azure Service FabricRapidly develop
microservice based
applications
Operate reliable, scalable services
Enjoy the confidence of a battle-
tested platform
• Download the Service Fabric developer SDK• http://aka.ms/ServiceFabric• Learn from the tutorials and videos• http://aka.ms/ServiceFabricdocs• Attend other talks• Building Resilient, Scalable Services with Microsoft Azure
Service Fabric• Deploying and Managing Services with Microsoft Azure
Service Fabric• Provide feedback• http://aka.ms/ServiceFabricforum• http://
stackoverflow.com/questions/tagged/azure-service-fabric
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