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.
Large Capital Expenditure (CapEx)
Low variable on demand CapEx
Operation Expenditure (OpEx) focused
Broad & Deeper Platform
Responsible for periodic upgrade
New features arrive daily
Lead to Innovation
Slow to roll new feature
Ready to use rapid feature
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.
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:
With free usage and no commitment
For PoCs and getting started
Pay by the hour with no long term commitment
For spiky / seasonal workloads
Low one-time payment with significant discount
For committed utilization
Bid for unused capacity, fluctuates based on demand/supply
Time intensive or transient workloads
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:
Kinesis - allows for large data stream processing and real-time analytics
Elastic MapReduce (EMR) - API styled web service that uses Hadoop ecosystem
Relational Data Store (RDS) - Scalable relational database in the cloud
Simple Storage Service (S3) - Opt for virtually unlimited cloud & internet storage
RedShift - Fast, fully managed, petabyte-scale data warehouse in the cloud
Dynamo DB - Fully managed NoSQL database service that provides fast and predictable performance with seamless scalability
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.