Re-Inventing for the Cloud Future

In order to simplify solutions and accelerate at pace using cloud, every year AWS develops a list of new services both for developers as well as its Business partners. In the keynote today, Andy Jassy ,CEO, Amazon Web Services introduced a few key services in this AWS Cloud journey

Person of the Year: Amazon Web Services’ Andy Jassy.

The new services launched during the keynote have been classified into categories :-

Compute :-

This category consists of the actual machines  i.e our EC2 instances, AMI’s, Elastic Containers, EBS , EFS etc. Basically the backbone of all the server capabilities built on Amazon.

Following is the current class classification of the AWS EC2 classes :-

On the extreme left is the basic T2 classes of machines and on the extreme right is the P2 set of machines (used for Petabytes of data )

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What’s new in Compute :-

  • R4 generation of Machines for more memory intensive operations
  • C5 generation of Machines for highly compute excellence.

 

What’s the Game-changer in Compute :-

  • Amazon LightSail
    • Problem Statement :– Many a times, we build a demo/POC code, everything is  running fine locally, but for the actual demo we may need to host it AWS. But for hosting on AWS, we need to know the following :-
      • Managing IAM.
      • Setting up DNS.
      • Creating Security Groups.
      • Allocating IAM.
    • As a front-end developer learning the right policies and AWS services for handling the above services can be a bottle-neck for accelerating our experimentation speed. So starting today Amazon has coupled in everything needed to a simple website hosting into a single AWS Service Amazon LightSail.Yes, setting up a web-server for your experiment is just 3 clicks away.

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  • Amazon Athena
    • Problem Statement :– Where does the majority of data in AWS lie which can be accessed/downloaded by any of the end user ?  S3 it is. The biggest problem with data in S3:-
      • It has to be moved before we make any insights/analysis into such data. It has to be downloaded to a machine, feed to a data-source and then finally processed.
      • Now imagine doing all of the that in one single step, that’s possible using Amazon Athena , the power to run direct SQL queries into data pumped into S3 using simple SQL queries.

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  • Elastic GPUs for EC2 :-
    • Problem Statement :– Currently the only part of the Compute Ecosystem which is elastic is the storage( EBS). For any particular feature the developers have to select a particular EC2 instance class, even if the usage is only 10-20% of the capabilities and also paying for the high-end Instance class
    • Similar to EBS now we can plug and play GPU’s into any EC2 instance just seamlessly without any loss of the Graphic Workload.

 

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Deep Learning :-

Amazon and Deep Learning have went hand in hand for the last few years. Using Amazon Alexa developers can interact with devices in a more intuitive way using voice. Using the skill set API developers could add new skills to the Alexa and train the voice service for a given use-case. However the Amazon deep learning experience had one limitation till date :-

  • Skills needed to be built around the Alexa service and the underlying Natural Language Understanding which is the core of functioning for Alexa wasn’t exposed as an API for easy integration with custom solutions.

In order to accelerate further on this AI journey Amazon has basically changed the entire ballgame by providing all of these as a platform in the form on three new services :- Amazon Polly, Amazon Rekognition and Amazon Lex.

Amazon Polly :-

  • Using Polly now one can turn varied text inputs into lifelike speech. This is significant for primarily two-reasons :-
    • The Natural Language Understanding at core of this can turn snippets of raw text into 47 lifelike voices spread across 24 languages.
    • The entire solution is real time with an option to cache and save Polly’s speech audio to replay offline or redistribute for a future use.

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Amazon Rekognition :-

  • Imagine adding the power of image analysis to our applications on the go, using Rekognition one  can detect objects, scenes, and even faces in these images. One can now also search and compare faces. The same technology is  currently used to analyse billion of images in Amazon Prime.
  • The key features :-
    • Easily integrated with services such as Amazon S3 and Amazon Lambda.
    • The service provides consistent response times regardless of the volume of analysis requests one makes.

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  • Amazon Lex
    • Lex is derived from A’Lex‘a, so basically what Amazon did behind Alexa, the same can be done for any other application using Lex. The core to the advanced deep learning functionalities which Lex enables this platform are primarily two :-
      • Automatic speech recognition (ASR) for converting speech to text.
      • Natural language understanding (NLU) to recognise the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.

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In addition to the above services Amazon also launched the following :-

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The key highlight of re-invent has been this message :-

“We have moved from the age of whether cloud is secure to

how early can we make the cloud secure in the our product

journey. The next big shift in this journey will be how integral

can cloud be a part of day to day life in solutions which

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