Spark the future.

Mahesh Krishnan

Creating highly available and resilient Microservices on Microsoft Azure Service Fabric

CLD334

AgendaWhy use microservices?Azure Service Fabric Platform – An introductionService Fabric Programming model

Reliable ActorsReliable Services

Wrap up

Traditional Monolithic approachA monolithic application has most of its functionality withina single process that is commonly componentized with libraries

Scales by cloning the app on multiple servers/VMs/containers

Microservices approachSeparates functionality into separate smaller services

Uses a standard communication protocol

Scales out be deploying each service independentlycreating instances of these services across servers/VMscontainers

Why use microservices?Can be versioned, deployed and scaled independentlyAllows use of different technologiesLoose coupling of servicesFaster delivery of featuresFacilitates small, focused teamsImproves fault isolation

Microsoft Azure Service FabricA platform for reliable, hyperscale, microservice-based applications

Azure

WindowsServer Linux

Hosted Clouds

WindowsServer Linux

Service Fabric

Private Clouds

WindowsServer Linux

High Availability

Hyper-Scale

Hybrid Operations

High Density

microservices

Rolling Upgrades Stateful

services

Low LatencyFast startup & shutdown

Container Orchestration & lifecycle management Replication &

Failover

Simple programming models

Load balancing

Self-healing

Data Partitioning

Automated Rollback

Health Monitoring

Placement Constraints

App1

App2

Service Fabric cluster with microservices

Types of MicroservicesStateless microserviceStateful microservices

Stateless MicroservicesHas either no state or state is persisted externally (such as Azure database or Azure storage)

There can be multiple instances of the services

e.g. Existing ASP.NET web apps, Azure cloud services

Stateful MicroservicesState is maintained within the microserviceAllows for hot data to be next to the computeState is partitioned for scaleEach partition state is replicated for reliability

e.g. Database, documents, user profile, shopping cart, etc

Programming models

Service fabric applications

Reliable Actors API

Actor programming modelIntroduced in 1973!An actor is the fundamental unit of computation

Does some processingHolds state

Communicates with other actors

Similar to objects in OOP

Reliable Actors APIBuild reliable stateless and stateful objects using a virtual Actor programming model

Suitable for applications with multiple independent unitsof scale and compute

Automatic state management and turn based concurrency

Reliable ActorsActors have an lD that maps to an object

Service Fabric manages nodes and can transparentlymove actors amongst them (provides HA and scale)

Actor methods run via turn based concurrency

Getting startedDownload the Service Fabric Download

Ensure PowerShell is installed and right execution policies set up

Run the DevClusterSetup.ps1script to start local cluster

Server side code - Interfacepublic interface IMyActor : IActor{ Task<string> DoWorkAsync();}

Server side code - Implementationpublic class MyActor : Actor, IMyActor{ public async Task<string> DoWorkAsync() { … return await Task.FromResult("result"); }}

Client side codevar app = "fabric:/HelloWorld";

var proxy = ActorProxy.Create<IMyActor> (ActorId.NewId(), app);

var result = proxy.DoWorkAsync().Result;

Demo

Reliable Actors

Actor Lifecycle

Actor lifecycle - ActivationIf actor is not active, a new actor is created

Its state is then loaded (for stateful actors)

OnActivateSync method is called

Added to Active Actors table

Actor lifecycle - DeactivationUnused actors removed from the Active Actors table

OnDeactivateSync method is called on Actor

Once deactivated, objects are garbage collected by CLR

Actor lifecycle – more conceptsScan interval – Time interval between successive scansby Actor runtime for inactive actors (Default: 60 seconds)

Idle timeout – Time an actor can be idle before it is deactivated (Default: 60 seconds)

ActorGarbageCollection attribute used to change defaults

Reliable Services API

Reliable Services APIWrite services that are reliable, available, scalable and provide consistency

Use Reliable Collections to persist state

Communicate using tech of your choice (WCF, WebAPI, ..)

Reliable CollectionCan be used to create Stateful services.

Features:Multi-machineReplicated (HA)Persistance (durable)AsynchrounousTransactional

Getting started…Only two methods you need to implement to get started.

CreateCommunicationListener – Method where the communication stack for the service is defined

RunAsync – This is where the Service runs the business logic – similar to WorkerRole’s Run method

Server side code - Implementationpublic class MyStatelessService : StatelessService{ protected override ICommunicationListener CreateCommunicationListener() { …}

protected override async Task RunAsync(CancellationToken cancellationToken) { … }}

Reliable Collectionvar myDictionary = await this.StateManager.GetOrAddAsync <IReliableDictionary<string, long>>("myDictionary");

using (var tx = this.StateManager.CreateTransaction()){ … await myDictionary.AddOrUpdateAsync(tx, "counter", 0, (k, v) => ++v); await tx.CommitAsync();}

Demo

Reliable Services

Demo

Service Fabric in the portal

Wrap up…Service Fabric is the next generation of PaaS that canbe used to create microservicesHas 2 programming models:

Reliable Actor APIReliable Service API

Can create either stateful or stateless servicesAvailability, Scalability, load balancing, etc comes OOB

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