Transcript Lecture 5

INFRASTRUCTURE AS A SERVICE
CLOUD ARCHITECTURES
CS 595
LECTURE 5
IAAS CLOUD ARCHITECTURES
• Introduction to IaaS
• Hardware virtualization
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CPU
Memory
I/O
Network
• Software virtualization
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Hypervisors
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• IaaS Ecosystems
KVM
Xen
VirtualBox
Full Virtualization
Para Virtualization
Host OS Virtualization
Container-based Virtualization
Open Source
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Eucalyptus
Openstack
Cloudstack
OpenNebula
Nimbus
Public Clouds
• Amazon AWS
• Google App/Compute Engines
• Microsoft Azure
• Other Cloud Issues
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Live Migration
Scalability
Availability
Management
Performance
Security
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AMAZON AWS
• Grew out of Amazon’s need to rapidly provision and configure machines of standard
configurations for its own business.
• Early 2000s – Both private and shared data centers began using virtualization to perform
“server consolidation”
• 2003 – Internal memo by Chris Pinkham describing an “infrastructure service for the world.”
• 2006 – S3 first deployed in the spring, EC2 in the fall
• 2008 – Elastic Block Store available.
• 2009 – Relational Database Service
• 2012 – DynamoDB
• Does it turn a profit?
$2.57 billion in 2015 (56% of Amazon’s total operating budget)
AMAZON AWS – DATA CENTERS
• 13 regions:
• United States:
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Virginia, California (2), Oregon
• Brazil:
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Sao Paulo
• Europe:
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Ireland, Germany
• Asia:
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Mumbai, Singapore, Tokyo, Seoul, Beijing
• Australia:
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Sydney
• 5 new regions by the end of 2017
• Canada, China, India, Ohio, United Kingdom
AMAZON WEB SERVICES
A set of APIs and business models which give developers access to Amazon technology and
content
Compute Services
Amazon Elastic Compute Cloud “EC2”
Amazon Elastic MapReduce
Amazon Lambda
Networking Services
Amazon Route 53
Amazon Virtual Private Cloud
AWS Direct Connect
Elastic Load Balancing
AWS Elastic Network Adapter
Storage Services
Amazon Simple Storage Service “S3”
Amazon Glacier
AWS Import/Export
Other Services
Amazon Mechanical Turk
Amazon Simple Notification Service
Amazon Elastic Transcoder
Amazon Simple Email Service
AWS COMMERCIAL SIDE
• Standard licensing terms
• Commercially usable
• Aggressive pricing
• Monthly credit card billing
• Self-serve model:
• Sign up as developer
• Choose services
• Agree to service licenses
• Enter payment info
• Start coding
AMAZON EC2
• Amazon Elastic Compute Cloud (EC2)
• Hardware As A Service
• A Web service that provides resizable compute capacity in the cloud.
• Designed to make Web-scale computing easier for developers.
• really Xen virtual machine instances running on AMD x86; each instance has 2GB RAM and
150GB disk
• A simple Web service interface that provides complete control of your computing resources
• create/destroy from the command line
AMAZON EC2 CONCEPTS
• Amazon Machine Image (AMI):
• Bootable root disk
• Pre-defined or user-built
• Catalog of user-built AMIs
• OS: Fedora, Centos, Gentoo, Debian, Ubuntu, Windows Server
• App Stack: LAMP, mpiBLAST, Hadoop
• Instance:
• Running copy of an AMI
• Launch in less than 2 minutes
• Start/stop programmatically
• Network Security Model:
• Explicit access control
• Security groups
• Inter-service bandwidth is free
USING AMAZON EC2
• Create an Amazon Machine Image (AMI).
• Upload the AMI into Amazon S3.
• Configure security and network access.
• Choose the type(s) of instance you want to run.
• Start, terminate, and monitor as many instances of your AMI as needed, using the
web service APIs.
• Pay for the instance-hours and bandwidth that you actually consume.
EC2 SOAP/QUERY API
• Images:
• RegisterImage
• DescribeImages
• DeregisterImage
• Instances:
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RunInstances
DescribeInstances
TerminateInstances
GetConsoleOutput
RebootInstances
• Keypairs:
• CreateKeyPair
• DescribeKeyPairs
• DeleteKeyPair
• Image Attributes:
• ModifyImageAttribute
• DescribeImageAttribute
• ResetImageAttribute
• Security Groups:
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CreateSecurityGroup
DescribeSecurityGroups
DeleteSecurityGroup
AuthorizeSecurityGroupIngress
RevokeSecurityGroupIngress
PRICING – EC2
• Pay only for what you use and there is no minimun fee.
• Pricing is per instance-hour consumed for each instance type.
• Partial instance-hours consumed are billed as full hours.
Type
vCPU
ECU
RAM
Storage
Cost
Gen. Purp
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Variable
500MB
EBS
$0.0065/hour
Gen Purp
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26
30GB
2x80GB SSD
$0.532/hour
Compute Opt.
16
55
30GB
2x160GB SSD
$0.84/hour
GPGPU
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26
16GB
1x60GB SSD
$0.65/hour
Memory Opt.
16
52
122GB
1x320GB SSD
$1.33/hour
Storage Opt.
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30.5GB
3x2TB SSD
$0.69/hour
PRICING – NETWORKING SERVICES
Name
Service
Cose
Route 53
DNS
$0.50/month
Virtual Private Cloud
Logically Isolated cloud resources
$0.05/hour (VPN)
Direct Connect
Dedicated connection from outside AWS
$0.29 - $2.14/hour (speed)
PRICING – S3
Data Size
Standard Storage
Infrequent Access
Glacier Storage
First 1TB/month
$0.03/GB
$0.0125/GB
$0.007/GB
Next 49TB/month
$0.0295/GB
$0.0125/GB
$0.007/GB
Next 450TB/month
0.029/GB
$0.0125/GB
$0.007/GB
Transferring Data
Data into S3
$0/GB
Data out of S3 to another
AWS region
$0.02/GB
Data out of S3 to Internet
$0 - $0.09/GB
AMAZON AWS BENEFITS
• Zero capital expenditures
• No up-front cost for purchasing equipment, software, server rooms, etc.
• Resource Interfacing
• AWS provides through API for provisioning of resources
• Compatible with many open source cloud softwares
• Flexibility
• Allows customers to scale up/down the amount of resources needed automatically
• Security
• Both physical and software security
AMAZON AWS – THINGS TO KNOW
• Local storage is non-persistent
• When you shut down, your data is lost
• Need to write it elsewhere; but S3 is free!
• You can "freeze" a running instance's "disks" to S3, as an "AMI"
(Amazon Machine Instance), then duplicate that to as many servers as
you like
• DHCP IP address assignment
• So IP changes when instance reboots
• Hard to use as a public server
LARGE COMPANIES USING AMAZON AWS
GOOGLE APP/COMPUTE ENGINE
• App engine:
• Standard environment based on containers running on Google's infrastructure.
• Containers:
• Java 7, Python 2.7, Go, PHP
• Supports App Engine APIs
• Persistent storage, automated scaling/load balancing, integration with other Google
cloud APIs
• Compute engine:
• Create and launch virtual machines on Google's infrastructure.
• Flexible resource accommodation (CPU, Memory, Network)
• CentOS, CoreOS, Debian, openSUSE, SUSE, RHEL, Ubuntu, Windows Server
GOOGLE APP/COMPUTE ENGINE – DATA CENTERS
• 15 regions:
• United States:
• South Carolina, Iowa, Georgia, Alabama, North Carolina, Oklahoma, Tennessee,
Oregon
• South America:
• Chile
• Asia:
• Taiwan, Singapore
• Europe:
• Ireland, Netherlands, Finland, Belgium
GOOGLE APP/COMPUTE ENGINE COMMERCIAL
SIDE
• Standard licensing terms
• Commercially usable
• Aggressive pricing
• Monthly credit card billing
• Self-serve model:
• Sign up as developer
• Choose services
• Agree to service licenses
• Enter payment info
• Start coding
PRICING – GOOGLE APP ENGINE
PRICING – GOOGLE COMPUTE ENGINE
GOOGLE APP/COMPUTE ENGINE BENEFITS
(Similar to AWS)
• Zero capital expenditures
• No up-front cost for purchasing equipment, software, server rooms, etc.
• Resource Interfacing
• Provides through API for provisioning of resources
• Compatible with many open source cloud softwares
• Flexibility
• Allows customers to scale up/down the amount of resources needed automatically
• Security
• Both physical and software security
LARGE COMPANIES USING GOOGLE
MICROSOFT AZURE
• Microsoft’s collection of integrated cloud services
• Computing
• Database
• Mobile devices
• Networking
• Storage
• IoT
• Analytics and web
• PaaS and IaaS services
MICROSOFT AZURE– DATA CENTERS
• North America:
• Canada East/Central, US West/Central/East
• South America:
• Brazil
• Europe:
• UK south/west, Germany Northeast/Central
• Asia:
• China North/South/East, India West/Central/South, Japan East/West
• Australia:
• East/Southeast
MICROSOFT AZURE COMMERCIAL SIDE
• Standard licensing terms
• Commercially usable
• Aggressive pricing
• Monthly credit card billing
• Self-serve model:
• Sign up as developer
• Choose services
• Agree to service licenses
• Enter payment info
• Start coding
PRICING – MICROSOFT AZURE WINDOWS VM
PRICING – MICROSOFT AZURE LINUX VM
PRICING – MICROSOFT AZURE STORAGE
MICROSOFT AZURE BENEFITS
(Same as Amazon and Google)
• Zero capital expenditures
• No up-front cost for purchasing equipment, software, server rooms, etc.
• Resource Interfacing
• AWS provides through API for provisioning of resources
• Compatible with many open source cloud softwares
• Flexibility
• Allows customers to scale up/down the amount of resources needed automatically
• Security
• Both physical and software security
LARGE COMPANIES USING MICROSOFT AZURE