Spark the future.

May 4 – 8, 2015Chicago, IL

Deploying and Managing Hyper Scale Applications on Azure VMsAlan Stephenson – Azure Program ManagerGuy Bowerman – Azure Program Manager

BRK3733

Cloud Compute continuum – IaaS -> PaaS

Building blocks - Units of work Deploying resources in Azure Resource

Manager at scale Managing apps with higher level

services

What’s in this session?

Enterprise-grade Hybrid Hyper-Scale

Customer

ServiceProviderMicrosoft

ConsistentPlatform

ONE

Microsoft Cloud OS

Open

Cloud Compute Continuum

Ultimate Control

Rapid Development

VMs /VM Scale Sets

VM ExtensionsService Fabric /Batch

Websites / App Platform

IaaS PaaS

VMs and VM Scale Sets

Azure Public CloudAzure Pack Private Cloud

VM Extensions

SCALR, RightScale, Mesos, Swarm

Service Fabric (VMs and

Containers)Batch

App Service Media

Web Apps

MobileApps

Apprenda, CloudFoundryOpenShift, Jelastic, Marathon

Infrastructure

IaaS and IaaS+

General Compute

PaaS

Vertical Compute

PaaS

VMs and VM Scale Sets

Azure Public CloudAzure Stack Private Cloud

VM Extensions

SCALR, RightScale, Mesos, Swarm

Service Fabric (VMs and

Containers)Batch

App Service Media

Web Apps

MobileApps

Apprenda, CloudFoundryOpenShift, Jelastic, Marathon

Infrastructure

IaaS and IaaS+

General Compute

PaaS

Vertical Compute

PaaS

Open Choice at Every Layer

Cluster Orchestratio

n

HDInsight

VMs and VM Scale Sets

Azure Public Cloud

VM Extensions

SCALR, RightScale, Mesos, Swarm

Batch

Media

HDInsight

IoT Finance Media Oil / Gas …Most

industries

Some Scale Application Scenarios

Visual Assets

VM

Frame Description

VM

VM

Rendered Frame

Rendered Frame

Rendered Frame

Merge Task AnimationCloud Processing

IoT Devices in the Wild

Monitoring / Analytics

Decision Making

Changing the Environment

Cloud Processing

EOD Report

Trading Report

Market Data

Company Transactions

Financial Models

Many scenarios, fewer patterns Big Data Big Compute Microservices at Scale All built from basic elements

Cloud Scale Patterns

BigData

Big Compute

Your goal is to run a workload / service Workload breaks into pieces

Compute Storage Networking

Unit of work Manageable Recoverable

Building Hyper Scale Apps – Scale Units

Local vs. Blob VHD Storage Custom Images vs. Gallery Images Scaling up vs. out Patching/ security story Azure throttling limits

As you design, consider:

Cloud Services

Deploying Resources with Azure Resource Manager

Resource Groups

Collection of resources with a similar lifetime

Every resource belongs to a resource group

Resources have types, defined by resource providers

RBAC integration Declarative model driven

deployment Consistent

RESOURCE GROUP

• Re-usable components

• Simple Orchestration

• Simple Roll-back

• Source file, checked-in

• Specify resources, dependencies and connections

• Parameterized

Instantiation of repeatable config.Configuration Resource Group

Azure Templates - Repeatability

SQL - A Website VirtualMachines

SQL-AWebsite[SQL CONFIG] VM (2x)

DEPENDS ON SQLDEPENDS ON SQL

SQLCONFIG

http://azure.microsoft.com/en-us/documentation/templates/

Resource Group

Subnet

Storage

VM

VNET

Public IP

Azure Resource Manager: Building a Virtual Machine

NIC storageAccount- accountType

publicIPAddress- allocationMetho

d- domainNameLa

bel

virtualNetwork- addressSpace- Subnet

- addressPrefix

networkInterface- privateIPAlloc

ationMethod

virtualMachine- hardwareProfile- osProfile- storageProfile- networkProfile

https://github.com/Azure/azure-quickstart-templates/tree/master/101-simple-windows-vm

Azure Resource Manager: Deploying an App

Resource Group

Subnet

Storage

VM

VNET

Public IP

Resource Loops: Declare multiple resources

NIC

https://github.com/Azure/azure-quickstart-templates/blob/master/resource-loop-vms-vnet/azuredeploy.json

VM

Public IP

NIC

VM

Public IP

NIC…

Subnet

Storage

{ "apiVersion": "2015-05-01-preview", "type": "Microsoft.Compute/virtualMachines", "name": "[concat('myvm', copyIndex())]", "location": "West US", "copy": { "name": "virtualMachineLoop", "count": "10" }, "dependsOn": [ "[concat('Microsoft.Network/networkInterfaces/', 'nic', copyindex())]", "[concat('Microsoft.Storage/storageAccounts/', parameters('newStorageAccountName'))]" ],

Resource Loops: copy() / copyIndex()

{ "apiVersion": "2015-05-01-preview", "type": "Microsoft.Network/networkInterfaces", "name": "[concat('nic', copyindex())]", "location": "West US", "copy": { "name": "nicLoop", "count": "10" }, ...

For each resource, use copy to set the number

Use copyIndex to create the names.

1

2

Deploying a Resource Loop

Define multiple storage accounts

Allocate VMs per storage account depending on workload

Load balancer routes connections to individual VMs

Scaling to 100s of VMsResource Group

VNet

Subnet

Load Balancer

Storage Account

40 VMs

40 NICs

Storage Account

40 VMs

40 NICs

Storage Account

40 VMs

40 NICs

Public IP

Traffic Manager -> Multiple load balancers

Multiple VNETs VMs run workloads in 1

or more containers Event Management

across application Container repository in

Azure Auto-scale containers

and VMs

Larger scale example

Containerization Abstract the unit of

work from the VM Lightweight, fast

provisioning, density

Simplify application updates

Works with cluster managers for auto-scale capabilities

Container Host - 1

ContainerA

ContainerA

ContainerB

Container Host - 2

ContainerA

ContainerA

ContainerB

Orchestration Engine

ARM Template2 Hosts

4 Instances of Container A2 Instances of Container B

Manage groups of identical VMs

Auto-scale

Performance

Customization

Ease of Management

Future VM Scale Sets: “Next-Gen Worker Role”

https://github.com/gbowerman/azure-myriad/

Resource Group

Subnet

Scalable Storage

VM

VNET

Scalable NIC…

VM

VM

VM

Scale Set

Extensions

"networkProfile": { "networkInterfaces": [ { "namePrefix": "vmssNic", "properties": { "ipConfigurations": [ {

"publicIPAddressNamePrefix": "vmssIp", "subnet": { ...

VM Scale Sets: targetInstancecount

{ "type": "Microsoft.Compute/virtualMachineScaleSets", "apiVersion": "2014-12-01-preview", "name": "myVMSS", "location": "East Asia", "Properties": { "scaleSettings": { "targetInstanceCount": "40" }, ...

Specify a target instance count

Specify a prefix for repeating resources.

1

2

Virtual Machine Scale-Sets

How this all fits together

Groups of containers

Groups of VMs

Application Orchestrators (e.g. Mesosphere)

Your Application/Service

Making Life Easier

VMs and VM Scale Sets

Azure Public CloudAzure Stack Private Cloud

VM Extensions

SCALR, RightScale, Mesos, Swarm

Service Fabric (VMs and

Containers)Batch

App Service Media

Web Apps

MobileApps

Apprenda, CloudFoundryOpenShift, Jelastic, Marathon

Infrastructure

IaaS and IaaS+

General Compute

PaaS

Vertical Compute

PaaS

IaaS v2: Open Choice at Every Layer

Cluster Orchestratio

n

HDInsight

Why higher level services

• Commodity to high-performance• Small to huge• RDMA network for

tightly coupled tasks

• IaaS or Cloud Service• Standard or

custom images• Windows or Linux

Cloud ServicesIaaS

Virtual Machines

Hardware

User workload or service

Get and manage VM’s

Start the tasks

Move task input and output Queue tasks

Install task applications

Scale up and downTask failure? Task frozen?

Manage and authenticate users

Significant amount of infrastructure, not related to business

Hadoop Clusters in Azure (with Yarn) Big data analytics Deploys MapReduce (MR/Hive), Real time

streaming (Strom) and NoSQL database (HBase) applications

IaaS offering now in preview Up to hundreds of nodes

HDInsight

Designed to code at scale in Azure Highly variable workloads Installs applications Gets the task on the machine Up to thousands / tens of thousands of

nodes

Batch

Batch Demo

Offer video transcode as a service

Used by MSN, XBox, Office Video, Skype, and others

Scale Unit – 1 video Their focus is video – so

they use Batch

Example: Media Services

Azure Batch

Azure Media Services

Batch Demo

You can build anything on Azure Choice at every level of the stack Azure Resource Manager Templates help

scale repeatable resources Scale Sets will simplify auto-scale Higher level services (Batch, HDInsight etc.)

make things easier while you focus on the app logic

Summary

For more informationSession Title Speaker(s) When

BRK3505 Taking a Deep Dive into Microsoft Azure IaaS Capabilities

Drew McDanielMahesh Thiagarajan

Tues, May 59:00AM - 10:15

BRK3705 Running Large-Scale Batch and High Performance Computing Applications with Azure Batch

Karan Batta Wed, May 61:30PM - 2:45

BRK3478 Deploying and Managing Services with Microsoft Azure Service Fabric

Chacko Daniel Wed May 65PM-6:15

BRK3722 Managing Linux and Windows on Microsoft Azure with Chef Kundana  Palagiri Thu, May 7

9-10:15 AM

BRK3702Running Docker Containers on Microsoft AzureSpeakers:

Khalid Mouss, Tom Hauburger

Thu, May 710:45 AM - 12:00

BRK2557 Harnessing the Power of Hadoop: Cloud Scale with Microsoft Azure HDInsight

Lance Olson Tues, May 510:45 AM – 12:00

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