Computing. Chaitan Baru San Diego Supercomputer Center. Competitive Advantage Through Cloud Computing

(1)

Technical Aspects of Cloud

Computing

Chaitan Baru

San Diego Supercomputer Center

Competitive Advantage Through

Cloud Computing

(2)

News flash…

• “Now Available

in the Cloud..”

• What does this

mean?

▫

 

For the

developers

▫

 

For the users

(3)

Outline

• The changing context

• Cloud computing definitions

▫

 

Implementation considerations

• Application case studies

• Future directions

• Course materials:

▫

 

http://clds.sdsc.edu

, click on Education

▫

 

Files stored in the SDSC Cloud

(4)

The Changing Context

• Rapid growth in data

▫

 



data-driven business decisions

• Scientific workloads as a predictor of future business

workloads

▫

 

Sensor-based systems, remote sensing, genome sequencing

• A point of inflexion

▫

 

Changing software: from RDBMS, to noSQL, to streaming,

to scientific data, …

▫

 

Changing hardware: multi-core, solid-state disk, large

memory and new types of memory

▫

 

Changing platforms: wholly-owned (“on premises”) systems

vs clouds

▫

 

Changing business costs / models: ultra-high productivity,

energy efficiency, rent vs own, …

(5)

New sources of increasing data

volumes

• Sensor Networks Top Social Networks for Big Data, Stacey Higginbotham Sep. 13, 2010,

http://gigaom.com/cloud/sensor-networks-top-social-networks-for-big-data-2/

(6)

Gene Sequencing

• ~2TB/experiment in next-generation gene

sequencing

▫

 

Sequencing of individuals

▫

 

Multiple runs per individual

▫

 

Multiple sequencing over time

• Managing and Analyzing Next-Generation Sequence Data

,

Richter BG,

Sexton DP (2009). PLoS Comput Biol 5(6): e1000369. doi:10.1371/

journal.pcbi.1000369, June 2009

(7)

Remote Sensing

• ~1TB of high-resolution topographic data for

San Andreas Fault

▫

 

10x more for imagery

▫

 

Repeated scans for ecological applications

▫

 

OpenTopography.org

• LaSDI Initiative: Laser Spatial Data

Infrastructure

▫

 

Sub-meter to 10cm scale 3D models of earth

(8)

Data is the new oil !

• The data ecosystem

▫

 

From acquisition, to transfer, storage, creation of

derived products, and exploitation

• Those with data are better off than those without

• Those who can exploit data have the competitive

advantage

▫

 

Walmart, Fedex, Wall Street trading, Internet

companies (Google, Amazon, Facebook, Twitter,..)

• And, cannot find oil without data…!

▫

 

Oil exploration data growing from 10’sTB to PBs over

next few years

(9)

Where should all the data reside?

• All in your private systems (private cloud)?

• All in a public cloud ?

• Hybrid model: Private + Public ?

(10)

Cloud Computing: Definition

• Cloud computing is a model for enabling

convenient, on-demand network access to a

shared pool of configurable computing resources

(e.g., networks, servers, storage, applications,

and services) that can be rapidly provisioned and

released with minimal management effort or

service provider interaction

Another turn of the screw in our push

towards productivity

(11)

Cloud Computing: NIST Definition

• On-demand self-service

▫

 

You get the resource when you ask for it, using APIs

• Broad network access

▫

 

Accessible from anywhere

• Resource pooling

▫

 

Shared resource provisioning

• Rapid elasticity

▫

 

Uniform scaleout

• Measured service

▫

 

Monitoring of usage, reporting of usage

(12)

Delivery Models

• Software as a Service (SaaS)

• Platform as a Service (PaaS)

• Infrastructure as a Service (IaaS)

• Importance?

▫

 

Implications on what type of programming work

needs to be done

▫

 

Who do you have (or want to hire) to work on

(13)

• http://thoughtsoncloud.com/

(14)

Delivery Model: Software as a Service

• Software as a Service (SaaS)

▫

 

The capability provided to the consumer is to use the

provider’s applications running on a cloud

infrastructure

▫

 

A

ccessible from various client devices through a thin

client interface such as a Web browser (e.g., web-based

email)

▫

 

The consumer does not manage or control the

underlying cloud infrastructure

 

W

ith the possible exception of limited user-specific application

(15)

Software as a Service: Example

• Google Maps API

▫

 

http://code.google.com/apis/maps/

▫

 

Users are provided with simple APIs for maps

▫

 

Uses cloud resources at the back-end

• Facebook

▫

 

http://www.facebook.com

▫

 

Social networking site using a suite of cloud-based tools at the

back-end

• Animoto

▫

 

http://www.animoto.com

▫

 

Service that makes videos from user uploaded images

(16)

Salesforce.com: SaaS

(17)

Delivery Models: Platform as a Service

• Platform as a Service (PaaS)

▫

 

The capability provided to the consumer is to deploy

onto the cloud infrastructure consumer-created

applications using programming languages and tools

supported by the provider (e.g., java, python, .Net)

▫

 

The consumer does not manage or control the

underlying cloud infrastructure, network, servers,

operating systems, or storage

 

B

ut the consumer has control over the deployed applications

(18)

Platform as a Service: Google AppEngine

(19)

Delivery Model: Infrastructure as a

Service

• Infrastructure as a Service (IaaS)

▫

 

The capability provided to the consumer is to

provision processing, storage, networks, and other

fundamental computing resources

▫

 

C

onsumer is able to deploy and run arbitrary software,

which can include operating systems and applications

▫

 

The consumer does not manage or control the

underlying cloud infrastructure



 

B

ut has control over operating systems, storage, deployed

applications, and possibly select networking components (e.g.,

firewalls, load balancers)

(20)

Infrastructure as a Service: Amazon

Web Services (AWS)

• Amazon Elastic Compute Cloud (EC2)

▫ 

A web service that provides resizable

compute capacity in the cloud.

▫ 

Configure an Amazon Machine Instance

(AMI) and load it into the Amazon EC2

service

▫ 

Quickly scale capacity, both up and down,

as your computing requirements change

• Amazon Simple Storage Service (S3)

▫ 

A simple web services interface that can be

used to store and retrieve large amounts of

data, at any time, from anywhere on the

web

▫ 

It gives any developer access to the same

highly scalable, reliable, fast, inexpensive

data storage infrastructure that Amazon

uses to run its own global network of web

sites

(21)

AWS,

aws.amazon.com

(22)

Microsoft Azure

www.microsoft.com/windowsazure/

(23)

OpenStack, www.openstack.org

• Receiving attention. Example, Cisco support for OpenStack

• http://www.slideshare.net/CiscoSP360/velocity-2011-cisco-and-open-stack

(24)

Eucalyptus

24

• Target market

▫

 

On-premise (private) IaaS

▫

 

Use existing infrastructure to create AWS-compatible cloud

• Products:

▫

 

Eucalyptus IaaS

▫

 

Eucalyptus OpenSource

(25)

Eucalyptus IaaS

(26)

Nirvanix

• CloudComplete

▫

 

Can vary among private, hybrid, public cloud

implementations, using Nirvanix’s public cloud

(27)

Virtualization and Cloud Computing

• Virtualization is the ability to run “virtual machines” on top of

a “hypervisor.”

▫

 

A virtual machine (VM) is a software implementation of a

machine (i.e., a computer) that executes programs like a physical

machine.

▫

 

Each VM includes its own kernel, operating system, supporting

libraries and applications.

▫

 

A hypervisor provides a uniform abstraction of the underlying

physical machine. Multiple VMs can execute simultaneously on a

single hypervisor.

▫

 

The decoupling of the VM from the underlying physical hardware

allows the same VM to be started on different physical machines.

• Virtualization is an enabler for cloud computing

▫

 

Gives the cloud computing provider the flexibility to move and

allocate the computing resources requested by the user wherever

the physical resources are available.

(28)

SNIA CDMI

• Cloud Data

Management

Interface

• Standardizing

at the IaaS

level

28

(29)

Some Take Home Lessons

• Cloud providers are providing you a

service

, not

just a product

▫

 

Product model: sell product, support product

▫

 

Service model: provide service, become intimately

exposed to all aspects of the service that the

customer sees



 

Seeing this from a customer’s viewpoint

(30)

Cloud Computing Costs*

(31)

Cloud Computing: The Rationale

• Flatten out the peaks and valleys of utilization to

get higher overall utilization of entire

infrastructure

• Bring together workloads with different valley /

peak behaviors

• But…is running a high utilization operation the

same as running a low utilization operation?

• Velocity 2010: Datacenter Infrastructure Innovation, James

Hamilton, VP & Distinguished Engineer, Amazon AWS

http://www.youtube.com/watch?v=kHW-ayt_Urk

(32)

Dealing with Peaks

• Old approach:

▫

 

Provision for peak workload. Low utilization at other

times

• HPC approach:

▫

 

Build a machine for a certain max job size. Provide job

queue and “on-demand”, pre-emptible access at other

times.

• Cloud approach:

▫

 

Charge different rates for use at different times, based

on usage

▫

 

E.g. Amazon Spot Instance

• Typical server workloads: 10-15%

(33)

Some Application Case Studies

from XLDB

• XLDB11: 5

th

Extremely Large Databases

Workshop, Oct 18-19, SLAC, Palo Alto, CA

• “State of practice” workshop

• Presentations on current system implementation

and challenges, and needs and requirements

▫

 

E.g. presentations from: Facebook, LinkedIn,

eBay, Google, Netflix, Novartis, Quora,

Metamarkets, Microsoft, …

• http://www-conf.slac.stanford.edu/xldb2011/Program.asp

(34)

Quora.com

• Scaling up

Quickly in the

Cloud,

Edmond Lau,

Quora, XLDB

Workshop

34

(35)

Quora.com

(36)

(37)

Quora

(38)

Quora

(39)

(40)

Metamarkets, Michael Driscoll,

co-founder, CTO

(41)

(42)

(43)

Metamarkets: Performance at scale

• Evaluating the online ad market

• Billions of microtransactions per day

• Require billion rows/second performance

• Fast analytics over 100’s of terabytes

• Metamarket’s Druid system

▫

 

Partial aggregates + In-memory data + Indexes

▫

 

Distributed data + Parallelizable Queries =

Horizontal Scalability

▫

 

Real-time analytics

▫

 

Implemented in the cloud (AWS)

(44)

Cloud Data Analytics, Roger Barga,

Microsoft Azure

(45)

(46)

(47)

(48)

Netflix

• Presentation by Eric Colson, VP, Netflix

• All Netflix processing (DVD rentals and

Streaming video) is in the cloud (AWS)

• Total cost of Netflix implementation may be

higher than an in-house solution but,

▫

 

Netflix made a business strategy decision. They

are not in the business of running IT

infrastructure

▫

 

Cloud computing required them to build a

distributed IT team, which did not match their

culture of building close teams.

(49)

Application Examples: Bioinformatics

• Crossbow

▫

 

Genotyping from short reads using cloud

computing

▫

 

http://bowtie-bio.sourceforge.net/crossbow/

index.shtml

• SDSC Project to implement Hadoop-based

processing for next generation sequencing on

SDSC’s HPC systems as well as clouds (AWS)

(50)

Role of Big Data

• What is the connection between cloud and big data?

• Cloud



Scaling



Lots of data

• Big data



Lots of data

• Hadoop

▫

 

A software (eco)system for efficient processing of very

large data

▫

 

Uses MapReduce, which has become a convenient

language for low entry barrier, very large-scale data

processing

• Could use cloud computing resources to implement

Hadoop

▫

 

$1M Question: data movement and data locality

(51)

Discussion of Survey

• Results from “Cloud Storage: Adoption, Practice

and Deployment”, survey conducted for the

Storage Networking Industry Association (SNIA)

(52)

Research and Markets Survey

Cloud Computing in HPC: Rationale for Adoption

• Top reason: Access to extra resources to meet peak system load

requirements

• Cost Avoidance

▫

 

Continued demand for HPC compute cycles. Cloud computing could deliver

low-cost computing cycles.

• Capacity Management

▫

 

Deal with periodic demand peaks and better management of data center growth,

power, and cooling issues.

• Collaboration

▫

 

Integration of internet-based applications and communications may allow HPC

users to better work with those both inside and outside of their organizations.

• Evaluation of Cloud Systems

▫

 

Looking at the cloud system alternative to determine if and how they can make

use of the technology and concepts.

• Organizational Requirement

▫

Making sure that the competition does not “steal a march” with a new technology.

(53)

Monitoring and Benchmarking

• Monitoring of resource usage is essential for

cloud environments

• What about SLAs and QoS?

• “Cloud computing means get your legal teams

lined up” !

• Resource monitoring is well-recognized need

▫

 

But need to ensure the right level of monitoring

and reporting is available

• Benchmarking is a new frontier

(54)

Amazon Cloudwatch

54 http://aws.amazon.com/

cloudwatch/

(55)

(56)

Azurescope

56

(57)

Azurescope application “probe”

(58)

Azurescope write “probe”

(59)

Future Directions: Benchmarking

• The need for Big Data and Cloud benchmarks

• The changing software landscape

▫

 

From RDBMS and Data Warehousing to NoSQL,

Hadoop, Unstructured data, Stream Processing, Graph

Processing, …

▫

 

The changing hardware landscape



 

Multi-core, SSD, new types of memory, large memory,

different networking options, commodity vs high-end, …

▫

 

Multiple platform choices



 

Dedicated data platforms

(60)

Benchmarking Issues

• “Reference benchmarks” for big data (TPC style)

▫

 

Define modalities of big data

▫

 

Define end-to-end flows of big data

▫

 

Identify key real-world characteristics, e.g. multi-rack,

heterogeneous hardware

▫

 

Identify which existing benchmarks can be reused

• “Probe” benchmarks for clouds

▫

 

Cloud performance can be variable

▫

 

“Application-level” performance probes

▫

 

The

Cloud Weather Service™

(61)

Future Directions: “Vertical” Clouds

• Clouds that are aimed at major markets

▫

 

Should have something unique about them, and a

sizable market

• E.g.

▫

 

Collocated clouds for performance



 

e.g. Wall Street trading systems, online

advertisement systems, etc.

▫

 

Collocated clouds for security / privacy

(62)

Email: [email protected]