AWS Enterprise Summit 2015

AWS (Amazon Web Service) Enterprise Summit are designed to educate new customers about the AWS platform; offers existing customers deep technical content to be more successful with AWS.

Today(23 Jun), I had the chance to attend AWS Enterprise Summit at Chennai, India. In a nutshell, it covers keynote address, panel discussion, customers use case on technical track, etc. Herez the highlights of Today's sessions:

Development Focus
"Moore's law" is the observation that, over the history of computing hardware, the number of transistors in a dense integrated circuit has doubled approximately every two years.

Itz true and reflected in IT industry. In 1971, Intel's first processor 4004 contained 2,300 embedded transistors to execute. Now, in 2015, Intel's 18-core Xeon Haswell-EP has over 5.5 billion transistors. Amazing growth, right!!!

As hardware is rapidly expanding its band, software's development focus is migrating in the below order:

• Mainframe - 1970s
• Personal Computer (PC) - 1980s
• Data Centre (RDBMS) - 1990s
• High Performance Computing (HPC) - 2000s
• Cloud; Horizontal Scaling - 2010s

Amazon Web Service (AWS) platform is the key player in 2010s era.

Business Model

	Traditional IT	Emerging IT	Business Model
	Large Capital Expenditure (CapEx)	Low variable on demand CapEx	Cost Reduction
	CapEx focused	Operation Expenditure (OpEx) focused	Cost Model
	Basic Computing	Broad & Deeper Platform	Scalability
	Responsible for periodic upgrade	New features arrive daily	Lead to Innovation
	Slow to roll new feature	Ready to use rapid feature	Agile
	Traditional DR	Automatic DR	Improved Availability

Costing Strategy

Cost drop is achievable by TWO key factors in the business theory.

1. Large customer base
2. Better economy of scale

In alignment with this costing strategy, Amazon had the multiple historical price reductions i.e. 48 price slashing since 2006.

Pricing Philosophy

Like mobile plan/cost, it starts from base to advanced package based on the user's demand. It is upto the customer to select their choice. AWS has the multiple pricing plan as below:

	Purchase Model	Description	Usage
	Free Tier	With free usage and no commitment	For PoCs and getting started
	On Demand	Pay by the hour with no long term commitment	For spiky / seasonal workloads
	Reserved	Low one-time payment with significant discount	For committed utilization
	Spot	Bid for unused capacity, fluctuates based on demand/supply	Time intensive or transient workloads
	Dedicated	Launch instance run on hardware dedicated to a single customer	Highly intensive or compliance loads

Data Growth Trend

It is interesting to observe the data growth @ our industry

• 7.9 Zetta Bytes of Data Persistence
• 90% of data growth just in last 2 years
• 5+ billion devices usage
• 966 Exa Bytes transfer rate

Big Data Platform

AWS Platform has the end-end solution for Big Data use cases with their own cloud based tools:

1. Kinesis - allows for large data stream processing and real-time analytics
2. Elastic MapReduce (EMR) - API styled web service that uses Hadoop ecosystem
3. Relational Data Store (RDS) - Scalable relational database in the cloud
4. Simple Storage Service (S3) - Opt for virtually unlimited cloud & internet storage 
5. RedShift - Fast, fully managed, petabyte-scale data warehouse in the cloud
6. Dynamo DB - Fully managed NoSQL database service that provides fast and predictable performance with seamless scalability

Closing Note

Statistics indicates that 6% Enterprise into Big Data and 9% Enterprise are into Cloud platform to adapt this data growth.

Thus, AWS (Amazon Web Service) is matured enough in each and every space of Big Data and Cloud platform.  In fact, their own line of business (amazon.com) in world's leading online store, is helped to set the validity of their solution/products, before serving to the industry.  Awesome work, AWS.