The document discusses microservices and provides information on: - The benefits of microservices including faster time to market, lower deployment costs, and more revenue opportunities. - What defines a microservice such as being independently deployable and scalable. - Differences between monolithic and microservice architectures. - Moving applications to the cloud and refactoring monolithic applications into microservices. - Tools for building microservices including Azure Service Fabric and serverless/Functions. - Best practices for developing, deploying, and managing microservices.

1. Design
Designing
Microservices

2. Microservices and cloud native apps

3. The rise of cloud apps and Microservices

4. Why Microservices
Faster Time to Market = address customer needs
more rapidly w/ a more pliable product construction
& composition model
Lower Deployment Costs = change production live
with ultimate granularity
More Revenue Opportunities = can monetize all
aspects of the solution (services, data, rules) based on
more composability options
Business Drivers
Faster Time to Market = more flexible development
cycles (timing, tooling, deployment models)
Faster & More Precise Change Management =
Leverages advanced DevOps tactics for “live”
updates/rollbacks in production
Maximum Capacity = Infinite scale w/ code +
Azure services
Technical Drivers

5. What is a Microservice
App 1
1
2 4
3
App 1 App 2
Monolithic
application approach
Microservices
application approach
• Does one thing well (functionality driven)
• Is developed by a small cross-functional team
• Can be built with task-appropriate
languages/frameworks
• Communicates over well-defined
interfaces/protocols (lightweight)
• Has a unique logical name (URI) that can be
resolved
• Is independent code and configuration (&
optionally state)
• Deploys independently
• Scales independently
• Gets upgraded independently
Microservice applications are composed of small, independently versioned, and scalable customer-
focused services that communicate with each other over standard protocols with well-defined interfaces.

6. What is different – distributed state
The microservices approach has a graph of interconnected microservices where state is typically scoped
to the microservice and various technologies are used. Each microservice manages and stores its own
state.

7. Business value of Microservices
Faster time to market
Competitive differentiation
Improved collaboration
with partners
Workforce management

8. What a Microservice is not
• A service implemented with a small amount of code
• A simple API to a more complex service implemented as
part of a Monolithic application
• A service built and delivered without automation of testing
and deployment and operations
• A service built on mutable compute infrastructure that is
updated and patched separately from software deployment
• A service that has dependencies on its peers that prevent it
from being changed and updated independently
• A large, coarse-grained service or Monolithic set of services
packaged in a Docker container
• A service exposed via API by another party; a published API
• A component, module, service, or capability, labeled as a
“Microservice" by a vendor, over which you do not have
deployment and management control consistent with your
other Microservices

9. Service Oriented Architecture vs Microservices

10. Moving to the cloud

11. Refactoring a Monolith into Microservices

12. Refactoring a Monolith into Microservices

13. Refactoring a Monolith into Microservices

14. Microservices architectural view points

15. Microservices best practices

16. Microservices in Azure

17. Azure application platform

18. Benefits of Microsoft Azure PaaS

19. Microservice tools and approaches
• Unable to find a polyglot
solution that works
consistently
on-premises and cloud, on
Linux and Windows
• Difficult to scale quickly to
meet surging demands, roll
out upgrades faster with zero
downtimes, and be fault
resilient
• Need a prescriptive platform
approach to delivering
microservices; unable to get
started easily
• Delivering same
functionality to multiple
deployment environments
• Ensuring consistency and
avoiding dependency hell
• Unable to migrate and scale
apps while maintaining
compatibility
• Paying for VMs that are
always on to manage the
unpredictable scale of
processes in your apps
• Having to manage operating
system & security patch
updates
• Tightly coupling event-based
code into business logic of
enterprise apps

20. Microservice tools and approaches
Customizable, pick best-
of-breed solutions
Easy to build,
deploy, and manage
Microservices at scale
Quick ramp up, sub second
metering, zero ops
Bring your ownPrescriptive framework“Server-less”

21. Microservice tools and approaches
Build your ownPrescriptive platform for
hyperscale applications
Platform optimized for
developer productivity
Developer productivity Infrastructure control
Azure Container ServicesAzure Service FabricAzure Functions

22. Azure Functions

23. What is “serverless”?
Event-driven
scale
Sub-second
billing
Abstraction
of servers

24. How is it different?
Complex
framework
Micro-
functionality
Outside
client app
Inside client
app
Mono-lithic
application
Loosely
coupled
components

25. Why serverless?
• Stateless  Scale
• Not worth deploying a traditional backend
• Workload is sporadic (very low & high scale)
• Dev ops favored versus dedicated ops
• Lots of different services involved that need “glue”
Focus on business logicShip faster Reduced dev ops

26. Applications
Every 15 minutes Clean tableFind and clean invalid data

27. Applications
Photo taken and
WebHook called Stores in blob storage Produces scaled images
Loaded web page
calls WebHook
Completed pageCreate ad based on user profile

28. Applications
File added to
Blob Storage
Transform CSV to data rows
CSV
Power BI
Chart graphic

29. Applications
Excel file saved
to OneDrive
Microsoft Graph API analyzes content Creates new sheets
with charts

30. Integration
Store
record
Post new
invoice
Fetch Invoice
Grab raw
file
Convert to
JSON
API layer
API
Management
Logic App Function

31. Azure Service Fabric
Azure Service Fabric is a distributed systems platform that makes it easy to package, deploy, and manage scalable
and reliable microservices. Microservices can be developed in using the Service Fabric programming models, to
deploying guest executables and container images.

32. Azure Service Fabric

33. Microservices using Service Fabric
Microservices
Service Fabric
High Availability
Simple
Programming
Models
Hybrid
Operations
High
Density
Hyper-Scale
Rolling
Upgrades
Data Partitioning
Automated Rollback
Stateful
Services
Low Latency High Monitoring
Container Orchestration
& Lifecycle Management
Load Balancing
Self-Healing
Replication
& FailoverPlacement
Constraints
Fast Startup &
Shutdown
Windows Server Linux Windows Server Linux
Azure
Windows Server Linux
Private Clouds Hosted Clouds

34. Inside the Service Fabric Platform
Reliability Subsystem
Reliability, Availability,
Replication, Resource
Management
Management
Subsystem
Deployment, Upgrade
and Monitoring
Transport Subsystem
Secure point-to-point communication
Federation Subsystem
Federates a set of nodes to form a consistent scalable fabric
Communication
Subsystem
Reliable messaging and
service discovery
Native and Managed APIs
Hosting & Activation
Application Lifecycle
Application Model
Declarative Application Description
Reliable, Scalable, Manageable Scalable Applications

35. Microservices runtime
App1
App2

36. Handling server failures

37. Stateful microservice
Application
Package

38. Microservice upgrades
• Upgrade progresses one UD at a time
• Upgrade limited to the code/config
package that changed
Node
Node
NodeNode
Node
Node
Service
Package
B
Service
Package
A

39. Migrating a traditional application to Microservices
1)Traditional app
2)Hosted as guest executable or container in Service Fabric
3)With new microservices added alongside
4)Breaking into microservices
5)Transformed into microservices

40. The Container Revolution

41. Azure Container Service
• Simplest way to deploy your container
orchestration environment on Azure
• Agile, flexible, and provides choice of orchestrator
• Open source templates for provisioning your
environment
• Easy ramp up to an optimized enterprise grade
container management
• Kubernetes on Azure
Container Service (preview)
• DC/OS Upgrade to 1.8.4
• Open Source Azure
Container Service Engine
• Azure Container Registry (preview)
• VS, VSTS, and VS code integration and
deployment to Azure Container Service
Azure
Container
Registry

42. Azure Container Service

43. Azure Application Platform

44. Living with Microservices

45. Balance of responsibility
Balance of control and responsibility
depends on the category of the service
MOVE-IN READY
Use immediately with minimal configuration
SOME ASSEMBLY REQUIRED
Existing services are a starting point, with additional
configuration for a custom fit
BUILD FROM THE GROUND UP
Building blocks, create your own solution or apps from
scratch
Responsibility On-Prem IaaS PaaS SaaS
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
MicrosoftCustomer

56. Ok, How to I get Started?
Readiness
• Azure
Learning
Paths
Prioritize
• Functional
Matrix
Document
• Models
(Current &
Future State)
Start
• Always On
Options for
You

57. Azure Learning Path:
https://azure.microsoft.com/en-us/documentation/learning-paths/service-fabric/

58. Functional Matrix
Service Overview
Business Value
(1 highest, 5 lowest)
Technical Complexity
(1 simple, 5 most complex)
Ranking

59. Decomposing Functionality of a Stable Architecture
Decomposition Approaches Service Bylaws

60. Decomposition Example via Functional Matrix
Service Overview
Business Value
(1 highest, 5 lowest)
Technical Complexity
(1 simple, 5 most complex)
Ranking
Shopping Cart
Bill Presentment, Shipping
Options, Packaging 1 4 4
Account Management
User Account Management,
Preferences, Payment History 1 4 4
Checkout Payment, Tracking 1 2 2
Inventory Management Inventory controls, Reorder 1 1 1
Campaign Management
Ad Management, Sales &
Promotions, Social Manger 1 5 5
…
High Ranking = Decompose Again

61. Decomposition Example via Functional Matrix
Service Overview
Business Value
(1 highest, 5 lowest)
Technical Complexity
(1 simple, 5 most complex)
Ranking
Shopping Cart
Bill Presentment, Shipping
Options, Packaging 1 4 4
Account Management
User Account Management,
Preferences, Payment History
Access/Auth Service Sign in / Access rights 1 1 1
PaymentHistory Service List all orders (shipped, returns, pending) 2 1 2
CustomizeSite
Adapts all pages to include users select
preferences 1 5 5
Checkout Payment, Tracking 1 2 2
Inventory Management Inventory controls, Reorder 1 1 1
Campaign Management
Ad Management, Sales &
Promotions, Social Manger 1 5 5
…
High Ranking = Decompose Again

62. Team Model
Role Responsibilities Deliverables # of Resources Skillset
Software Architecture
System architecture and
service model
Logical / Physical Design
Functional Matrix
1-2 / Project
Cloud Architect
API Architect
Operations
Create Dev, Test,
Production deployment
plan for new solution
DevOps Plan 1-2 / Project
Docker expertise
DevOps expertise
Developers App Builder
Web App / Service / Data
Structures, etc.
As Appropriate
As Needed for your
Solution
Quality Assurance
Test scripts for new
application architecture
Test Scripts 1-2 / Project
Bold = Potential Investment Areas

63. Architectural Modeling – Free Tools & Reference Models
• Solution / Logical:
https://azure.microsoft.com/
en-us/solutions/architecture/
• Physical:
https://docs.microsoft.com/
en-us/azure/architecture/
reference-architectures/
• Visio 2016 Stencil -
https://www.microsoft.com/en-
us/download/confirmation.aspx?id=41937
• Stencil organizers services into Azure
service groupings

64. Comparing App Architectures

65. Architectural Modeling
Monolithic Application Microservices Approach
Web App
Visual Studio Team
Services Build and Release Agent
Visual Studio Team
Services Build and Release Agent
Service Fabric
Blob Storage
Blob Storage

66. Architectural Modeling – Future Possibilities
Microservices Approach
Visual Studio Team
Services Build and Release Agent
Service Fabric
Blob Storage
PowerBI Machine Learning
Cognitive
Services

67. Q&A

68. Thank you!