The important bits of cloud computing

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Information about The important bits of cloud computing

Published on October 10, 2008

Author: carsonified

Source: slideshare.net

Important Bits of Cloud Computing Jeff Barr – jbarr@amazon.com Senior Web Services Evangelist Future of Web Apps 2008 - London

What is it? Why is it important? Amazon’s approach! Who is using it? The Important Bits of Cloud Computing

What is it?

Why is it important?

Amazon’s approach!

Who is using it?

Characterizing Cloud Computing Infrastructure on demand Provision via API calls, not phone calls Scale to meet actual demand Effectively infinite capacity Reduced need for capital Pay as you go Operating expense, not capitalized cost Business flexibility Abstracted view of resources Reduced concern for “specs” Storage, processing, messaging, bandwidth Focus on business

Infrastructure on demand

Provision via API calls, not phone calls

Scale to meet actual demand

Effectively infinite capacity

Reduced need for capital

Pay as you go

Operating expense, not capitalized cost

Business flexibility

Abstracted view of resources

Reduced concern for “specs”

Storage, processing, messaging, bandwidth

Focus on business

Justifying Cloud Computing Developers Focus on application Leverage powerful service repertoire Less time on base technology & system issues Entrepreneurs Reduce need for capital Reduce need for diverse set of skills No more “success disasters” Enterprises Adapt to changing conditions with ease Operate with cyclic or unpredictable loads No investment in depreciating hardware

Developers

Focus on application

Leverage powerful service repertoire

Less time on base technology & system issues

Entrepreneurs

Reduce need for capital

Reduce need for diverse set of skills

No more “success disasters”

Enterprises

Adapt to changing conditions with ease

Operate with cyclic or unpredictable loads

No investment in depreciating hardware

50 Servers to 3500 Servers in 3 Days

Amazon’s Approach to Cloud Computing! Amazon Web Services Third major line of business Long term investment for us First service released in early 2006 Access to Amazon’s robust & scalable infrastructure Goal: Provide infrastructure services for developers Economically priced

Amazon Web Services

Third major line of business

Long term investment for us

First service released in early 2006

Access to Amazon’s robust & scalable infrastructure

Goal: Provide infrastructure services for developers

Economically priced

AWS Infrastructure Services EC2 - Elastic Compute Cloud - 5 sizes of servers by the hour S3 – Simple Storage Service - Web-scale, highly available object storage Content Distribution for S3 - Global points of presence for low-latency access SDB – Simple Database - Scalable, redundant, indexed data storage SQS – Simple Queue Service - Message service for distributed applications DevPay – Developer Payment Processing – Billing for AWS applications FPS – Flexible Payments Service - Developer-oriented payment service

EC2 - Elastic Compute Cloud - 5 sizes of servers by the hour

S3 – Simple Storage Service - Web-scale, highly available object storage

Content Distribution for S3 - Global points of presence for low-latency access

SDB – Simple Database - Scalable, redundant, indexed data storage

SQS – Simple Queue Service - Message service for distributed applications

DevPay – Developer Payment Processing – Billing for AWS applications

FPS – Flexible Payments Service - Developer-oriented payment service

Trends We’re Seeing Use of multiple services in one application EC2, S3, and SQS usage is very common Massive datasets & large-scale parallel processing Hundreds of terabytes of data per application Hadoop, Condor, MPI Blast Enterprise adoption on the rise NASDAQ, ESPN, Indy 500, New York Times, Washington Post, SanDisk Increased need for support and transparency Service Health Dashboard Premium Developer Support Running more sophisticated software JBoss, MySQL, Oracle Enterprise stacks and applications

Use of multiple services in one application

EC2, S3, and SQS usage is very common

Massive datasets & large-scale parallel processing

Hundreds of terabytes of data per application

Hadoop, Condor, MPI Blast

Enterprise adoption on the rise

NASDAQ, ESPN, Indy 500, New York Times, Washington Post, SanDisk

Increased need for support and transparency

Service Health Dashboard

Premium Developer Support

Running more sophisticated software

JBoss, MySQL, Oracle

Enterprise stacks and applications

Thanks!

Thanks!

For More Information AWS Home Page: aws.amazon.com AWS Blog: aws.typepad.com AWS Service Health Dashboard: status.aws.amazon.com AWS Forums: aws.amazon.com/forums

AWS Home Page: aws.amazon.com

AWS Blog: aws.typepad.com

AWS Service Health Dashboard: status.aws.amazon.com

AWS Forums: aws.amazon.com/forums

Cloud Computing Use Cases Backup / Archive Media Sharing Media Distribution Academic Computing Quantitative Trading Media Rendering Search Engines Social Networking

Backup / Archive

Media Sharing

Media Distribution

Academic Computing

Quantitative Trading

Media Rendering

Search Engines

Social Networking

Use Case – Backup / Archive Guard against catastrophic data loss. Features: De-duplication Compression Encryption Backup / Restore Services: S3, EC2. Examples: JungleDisk , ElephantDrive , SecoBackup , Zmanda .

Guard against catastrophic data loss.

Features:

De-duplication

Compression

Encryption

Backup / Restore

Services: S3, EC2.

Examples: JungleDisk , ElephantDrive , SecoBackup , Zmanda .

Use Case - Academic Computing Computationally powered research by bioinformaticians and computer scientists. Features: Large number of servers. Highly parallel computation. Use of distributed computing frameworks (Hadoop, Condor, Sun Grid Engine). Services: EC2, S3, SDB. Examples: RunBlast , Hadoop .

Computationally powered research by bioinformaticians and computer scientists.

Features:

Large number of servers.

Highly parallel computation.

Use of distributed computing frameworks (Hadoop, Condor, Sun Grid Engine).

Services: EC2, S3, SDB.

Examples: RunBlast , Hadoop .

Use Case – Quantitative Trading Use of algorithmic techniques and quantitative analysis for financial needs such as risk management or derivatives pricing. Features: Large number of servers. Highly parallel computation. Use of distributed computing frameworks (Hadoop, Condor, Sun Grid Engine). Services: EC2, S3, SDB, EBS. Examples: Banks, Hedge Funds.

Use of algorithmic techniques and quantitative analysis for financial needs such as risk management or derivatives pricing.

Features:

Large number of servers.

Highly parallel computation.

Use of distributed computing frameworks (Hadoop, Condor, Sun Grid Engine).

Services: EC2, S3, SDB, EBS.

Examples: Banks, Hedge Funds.

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