This document introduces the concept of cloud computing by comparing it to earlier models of computing. It discusses how computing has evolved from large centralized mainframes to today's decentralized cloud-based systems. The cloud offers advantages like lower costs, ability to scale up or down as needed, and not having to deal with hardware maintenance. However, it requires constant internet connectivity and gives up some control over data access. The document recommends that developers take advantage of the cloud's ability to break problems into distributed components for better scalability, fault tolerance, and flexibility compared to traditional single-point architectures.

1. Introduction to the Cloud
The journey from the computer.

2. First there were computers
 Pros
 Do difficult math consistently
 Cons
 Only do one thing at a time
 Big
 Expensive
Large centralized machine with physical inputs and hard
wired software

3. Main Frames and Dumb Terminals
• Pros
• Simultaneous use
• Shared resources
• Rarely crashed
• Central to maintain/upgrade
• Cons
• Difficult to get/keep networked
• Expensive investment
• Single point of failure
• Hard to scale
• Always on
Large centralized machine with remote inputs and loaded
software

4. Desktops and Servers
• Pros
• Work disconnected
• Could be turned off when not using
• Cheaper investment
• Distributed
• Cons
• Hard to scale (impossible above a certain
bar)
• Required constant syncing and upgrades
• Duplicate investment depending on use
Small decentralized machine with local inputs and loaded software syncing with
each other and larger centralized machines with loaded software

5. Datacenters and CoLo
• Pros
• Great connectivity (internet)
• Incredible physical security
• Cons
• Expensive investment
• Difficult to fix issues and upgrade
• Usually single point of failure
• Always on
Many servers centrally located in a secure facility with really
good internet

6. Clouds
• Pros
• All the pros of a datacenter
• Cheap investment
• Scale up and down as needed
• Never deal with hardware issues
• Cons
• Requires connectivity for ANYTHING
• Reduced control of data and access
Large corporate datacenters with infrastructure to manage
the complexities

7. What makes a cloud a cloud?
Clouds have common infrastructural components to abstract
server interaction
Azure (Microsoft) AWS (Amazon)
Binary Storage Azure Blobs S3 (Simple Storage Service)
Structured Storage Azure Tables SDB (Simple Database)
Relational Storage SQL Azure RDS (Relational Data Service)
Abstract “Computer” Azure Web/Worker Roles Elastic Beanstalk
Real “Computer” Azure Virtual Machines EC2 (Elastic Compute Cloud)
Queues Azure Queue SQS (Simple Queue Service)
Big Data Processing HDInsight EMR (Elastic Map Reduce)

8. How most people use the cloud…
Same as Datacenter/CoLo with N-Tier architectures
• Pros
• Easy to port to cloud
• Understood
• Cons
• Single point of failure
• Difficult to scale/upgrade/manage

9. How people should use the cloud!
Break the problem apart and abstract the logic from the
computer
• Pros
• Easier to scale
• Easier to upgrade
• Easier to change
• Tolerant of failures (no single point)
• Cons
• New to many people
• More moving pieces to
track/understand

10. Resources
 Azure: http://azure.microsoft.com/en-us/
 Amazon Web Services (AWS): http://aws.amazon.com/
 Author: Lawson Caudill – http://www.getthinktank.com