net microservices with azure service fabric

Agenda

• Microservices?

• Service Fabric?

• Microservices in Service Fabric?

Demo code on GitHub: https://github.com/n3wt0n

Slides on SlideShare: https://www.slideshare.net/n3wt0n

What is a microservice?

• Encapsulates a single capability

• Are developed by a small engineering team

• Can be written in any language and framework

• Contain code plus state that is independently versioned, deployed, and scaled

• Interact with other microservices over well defined interfaces and protocols such as http

• Have a unique name (i.e. URL) that can be resolved

• Remains consistent and available in the presence of failures

• Ideal for DevOps automation!

Reasons to split a monolith into services

• Scaling independently (balancing cost with speed)

• Supporting different technology stacks

Reasons to split a monolith into services

• Two or more clients, where clients adopt new features at will

• Managing conflicting dependencies

Are microservices right for my app?

Maybe, if:

• Your application can be split in many different, independent pieces

• You need/want independent service scalability

• You need/want to have multiple technologies, multiple teams involved

• You are ready to change your DevOps practices and company culture

But:

• Any application that binds its components over a network connection introduces delays

• Security and Authentication get more complex

• Microservices are more complex to deploy, manage, and monitor

• You cannot assume that you can take an arbitrary system and break it into microservices. Most systems acquire too many dependencies between their modules

From Monolith to Microservices

... we support any stage you choose

New or

transformed

microservices app

5

Parts of existing

monolith

extracted

4

Existing Monolith + new

microservices

3

Monolith Hosted as

guest executable or

container

2

Traditional app

1

5 stages in a continuum…

• Comparing an in-process call to an HTTP request• Performance: Worse & increases network congestion

• Unpredictable time: Managing timeouts is challenging; pass deadlines

• Unreliable: Requires retry loops with exponential backup/circuit breakers

• Server code must be idempotent

• Security: Requires authentication, authorization, & encryption

• Debugging: network issues, perf counters/events/logs, causality/call stacks

IntelliSense, refactoring & compile-time type-safety)

IntelliSense, refactoring & compile-time type-safety)

Proven platform powering core Azure and Microsoft services

Microsoft has deep expertise in running global

services such as Cortana, Skype & Cosmos DB

Service Fabric is the foundational technology

powering these services & core Azure infra

Sample scale of one of these services: 60 billion

events per day with millions of databases

Production scenarios with 3500 VMs

SQL

{ }Power BI

Dynamics

Intune

Cortana Skype

Cosmos DB

IoT Hub

Events Hub

SQL Database

Build: data-aware microservices

Lifecycle

Management

Always On

Availability

Orchestration Programming

Models

Health &

Monitoring

Dev & Ops

Tooling

Auto

Scaling

Programming

Models

Dev & Ops

Tooling

Orchestration Lifecycle

Management

Health &

Monitoring

Always On

Availability

Auto

Scaling

.NET or Java …

Built-in ASP.NET core integration; work with VS and VSTS or

Eclipse and Jenkins

Reliable Services

Manage state reliability without a database,

lowering latency

Guest Executables

Run existing code and orchestrate life cycle using

service fabric

Reliable Actors

Implementation of actor design pattern (Isolated, independent unit of compute and state with single-

threaded execution)

Containers

Orchestrate your Windows Server or Linux containers

reliably at scale

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Deploy: any code on any OS

Lifecycle

Management

Always On

Availability

Orchestration Programming

Models

Health &

Monitoring

Dev & Ops

Tooling

Auto

Scaling

Programming

Models

Dev & Ops

Tooling

Orchestration Lifecycle

Management

Health &

Monitoring

Always On

Availability

Auto

Scaling

Monitor and diagnose

Generate, aggregate, and analyze events with built-in tooling and integration with Azure services

Docker Compose

Orchestrate existing container applications

natively

Automate

Deploy or remove applications using PowerShell, CLI, Visual

Studio, and other APIs

CI/CD

Maximize uptime and scalability with isolated compute threads

running concurrently

Rolling upgrades

Upgrade non-disruptively and roll-back in case of failures, automate with PowerShell

Operate: on any cloud at any scale

Lifecycle

Management

Always On

Availability

Orchestration Programming

Models

Health &

Monitoring

Dev & Ops

Tooling

Auto

Scaling

Programming

Models

Dev & Ops

Tooling

Orchestration Lifecycle

Management

Health &

Monitoring

Always On

Availability

Auto

Scaling

Scale programmatically

Use PowerShell, CLI, or APIs to scale programmatically achieving

very high densities

Use controlled chaos

Test graceful and ungraceful failure

scenarios

Recover gracefully

Recover from node or service failure gracefully; replicate

data automatically

Use familiar tools

Such as Splunk, OMS, ELK, or AppInsights to gain deep insights

or monitor application health

Secure at scale

Secure node-to-node communication and user access

using built-in capabilities

Awesome for developers

Use .NET, Java or more• Stateless and Stateful services

• ASP.NET core integration

Visual studio integration• Use single node cluster for dev/test purposes

• Use 5-node local cluster for extensive dev/test

Consistent experience across environments• Run the same environment on dev box as in production

Awesome for dev-ops

Automated deployment• Use PowerShell, Service Fabric CLI or APIs

Rolling upgrades for reliability• Upgrade your services in an automated fashion

Visual studio team services integration• For continuous integration and deployment

Integration with Jenkins and more• Use tools familiar to you for deploying Java applications

Awesome for infrastructuremanagement

Cluster management• Secure your clusters and handle failures gracefully

• Scale clusters programmatically or manually

• Ease maintenance with integrated OS patching

PowerShell, CLI, and GUI management• Be productive and choose tools that suit your needs

Applications as an ARM resource

• Manage clusters as well as deploy app using templates

Health monitoring

• Monitor using integrated or 3rd party tool of your choice

• Query health using PowerShell or APIs programmatically

Handling Machine Failures

Cluster

V1V1

V1V1

V1V1

V2V2

V2V2

V2V2

Cluster

V1V1

V1V1

V1V1

V2V2

V2V2

V2V2

Cluster (or across 2 clusters)

V2V2

V2V2

V2V2

V1V1

V1V1

V1V1

LB / Rev Proxy

• All API requests must pass version info starting with v1

• New service versions must be backward compatible

• What about intra-service instance requests?• During rolling update, old & new service instances run together

• Failure occurs if v2 instance makes v2 API request to v1 service instance

• Fix by performing a 2-phase update1. Deploy v2 service instances (which accept v2 & v1 API requests)

• But never send v2 API requests

2. After all instances are v2, reconfigure instances to send v2 API requests

• OPTIONAL: After all instances upgraded, deploy again with v1 code removed

• Services start/stop, scale up/down, & crash/move• Each instance has its own endpoint (dynamically-assigned IP/port)

• Clients must dynamically discover service instance endpoints and load balance between them• Beware: a new service instance could be assigned a previous instance’s endpoint

• This requires certificates or some ID/uniqueness so client knows whichservice it’s communicating with

Who is App1/Service1?There you go: 10.0.0.8:1234

Different ways

Stateless microservice

Stateful microservice

Stateless microservices pattern

Load Balancer

Front End

(Stateless Web)

Stateless

Middle-tier

Compute

Cache

StorageQueues

Stateless microservices pattern

• Stateless services can have an external endpoint

• Configure the endpoint in ServiceManifest.xml (especially the port)

• For external accessible services, remember to configure Load Balancer

• Stateless service instances are equivalent and activated “randomly”

Stateful microservices pattern

Load Balancer

Front End

(Stateless Web)

Stateful

Middle-tier

Compute

Cold Data

Stores

(Optional)

Stateful microservices pattern

• Stateful services cannot have an external endpoint

• Stateful services must specify partitions

• Stateful service instances are not equivalent and not activated “randomly”

• Stateful services use Reliable Collections to persist the data

Reliable collections

• Reliable collections make it easy to build stateful services.

• An evolution of .NET collections for the cloud.

Collections

• Single machine

• Single threaded

Concurrent

collections

• Single machine

• Multi threaded

Reliable collections

• Multi machine

• Replicated (HA)

• Persistence (durable)

• Asynchronous

• Transactional

Some notes…

• Development

• Service communication

References

Demo Code and Slides

https://github.com/n3wt0n

https://www.slideshare.net/n3wt0n

Service Fabric Reference Documentation

https://docs.microsoft.com/en-us/azure/service-fabric/

Service Fabric Reference Architecture

https://docs.microsoft.com/en-us/azure/architecture/guide/architecture-styles/microservices#microservices-using-azure-service-fabric