AWS Re:Invent 2020 Keynote Andy Jassy 
Tags: aws, cloud
Published: 2020-12-16 17:52:53

Starting off with the news of $ 46 Billion and 29% growth of AWS in the Q3 of 2020, Andy said that the pandemic greatly accelerated the cloud. Survival of companies is really touching only 17% of companies of fortune 500 of the year 1970 remain while half remain of the year 2020. Companies need to reinvent and should not take too long. Keys to reinvent 
1.	The leadership’s will to reinvent. Like Airbnb, Stripe, and Peloton. 
2.	Acknowledge that you cannot fight gravity. Like Netflix did and amazon and eBay with 3rd party sellers. 
3.	Talent that is Hungry to reinvent. Some people are slow to reinvent and they waste time.
4.	Solving Real customer problems with builders. Like AWS is so customer-oriented with S3 and EC2, and not build things merely just because they are cool.
5.	Speed is a choice. It is a culture of urgency. If there is no speed no reinvention.
6.	Do not complexify 
7.	Use the platform with the broadest and deepest set of tools like compute, storage, Edge, etc.
8.	Pull everything together with top-down aggressive goals like general electric did or Capital One in the Banking sector.

The CEO JP Morgan and Snap Inc. say how they have reinvented their respective industries followed by Andy’s announcements.





Compute
Instances 
EC2 Instances: 
Now Mac OS Support. Intel, AMD & ARM Chips.
Nitro Chips: Amazon's key to success is the Virtualization of Network, Security, and Storage. 
Gravition2: 
ARM-Based chip design C6GN 1000 Gbps 40% price-performance breakthrough! In a blog, Honeycomb.io said it got the 40% price performance 
AWS Inferentia: AWS chip Lowering the cost of ML Inference by 30% and latency by 25%
ML Training: Habana Gaudi with cooperation with intel.
AWS Tranium: AWS Training chip.

Containers:
A small chunk of storage.
Amazon ECS Anywhere: which can run on-premises and can run all the API’s available. And Just Like that 
Amazon EKS anywhere: And its distribution is opensource and with be available on GitHub in 2021.

Serverless:
Problems: Certain workloads require more compute but just for a short amount of time. 

Lambda: It Fires compute for a short amount of time and then turns it off now its latency is reducing from 100ms to 1ms. 
Serverless:
API gateway, event bridge, Step function, and triggers.
Lambda Container Support: Package code and dependencies as a Docker or open container initiative compatible container image. Have a consistent set of tools for containers and lambda-based applications, deploy lambda functions built on top of 3rd party-based container images.
AWS Proton: First fully managed deployment service for container and serverless applications. Deployment of Microservices. CI/CD Pipeline.
Storage:
Storage: GB3 volume of elastic block storage. Provision IOPS and throughput separately with next-generation SSD volumes (at a 20% lower price per GB) 1000MB/s peak throughput.
IO2 for even better. 1000MB/s peak throughput and 64000 Max IOPS.
IO2 Block Express is the first SAN built for the cloud and highest IOPS and throughput in the cloud. (4000 MB/s) and 64TB storage capacity.
DataBase:
Amazon Aurora: 1/10th of the cost.
Aurora Serverless: Scale-up in 5 to 50 seconds.
Aurora Serverless V2: upscale in few seconds and 90% save in cost.
Babelfish for Amazon Aurora PostgreSQL: Run SQL Server with little to no code changes. And this is an open-source project.
AWS Glue Elastic Views:
Boom Blake Scholl: Presentation:
Boom is the world’s first supersonic aircraft company. Aviation Industry had not been reinvented. The last reinversion was the jet engine 60 years ago. Boom ran petabytes of data for simulation of its aircraft. Their Aircraft will be carbon neutral. They are reinventing travel Half the time of flight in just $ 100.

Machine Learning:
Data Wrangler. The fastest way to prepare data for machine learning.it imports and inspects data to identify the data types. Recommends transformations based on the data in the dataset. Applies transformations to features and can see a preview in real-time and checks to ensure data is valid and balanced.
Sage Make IDE was announced last year.
Sage maker Feature store: Store features with low latency. Purpose-built and accessible from sagemaker studio. Easily name, organize, find, and share features. Access features in batches or subsets and low latency for inference.
Amazon Sage maker Pipelines. First-ever CI/CD Pipelines.
AI Services:
Amazon Devops Guru: A service that uses ML to identify security and operational issues before they even impact the users.
Reinventing Business Intelligence: 
Amazon QwickSight: Now you can business query data through natural language processing and get answers in seconds. It automatically generates data models that understand meanings and relationships of data! And not limited to asking a specific set of questions.
Amazon Connect: Call Centre solution built using ML and AI. Setup and configure a contact centre in minutes. Easy to use and configure for non-technical users. Scale from tens to tens of thousands of agents. Save up to 80% over traditional contact centres solutions and no infrastructure to deploy and manage.
Amazon Connect Wisdom: A new capability that uses ML to deliver agents the product and service information they need to solve issues in real time. It reduces the time agents spend finding answers for customers.
Amazon Connect Customer Profiles: Gives agents a unified profile of each customer to provide more personalized service during a call. 
Real Time contact lens for amazon connect: Identifies issues regarding customers in real time to impact customer interactions during the call itself. It uses machine learning to customer experience issues during live calls.
Amazon Connect tasks: Automates, tracks, and manages tasks for contact centre agents. Connect tasks makes follow up tasks easier for agents and enables managers to automate some tasks entirely. 
Amazon Connect Voice ID: Real Time Caller authentication using ML powered voice analysis. Connect voice ID provides real time caller authentication without disrupting natural conversation. 
Reinvention in automotive sector such as RIVIAN, Toyota, Blackberry, BMW Group, Lyft, and Volkswagen. Reinvention in health sector such as Philips, Cerner, Moderna and Mount Sinai. Reinvention in Media and Entertainment industry such as done by FOX, VIACOMCBS, Disney, Comcast NBC Universal and Netflix.

Amazon Monitron: end to end equipment monitoring system to enable predictive maintenance. Sensors will provide data to a gateway and will send it to AWS cloud and then send updates regarding a problem through a mobile app.
Amazon Lookout for Equipment: Anomaly Detection Service for industrial machinery.
Predictive maintenance with Amazon Lookout for Equipment: Sends sensor data to build a ML model. Pulls data from machine operations systems, such as OSISoft. Learns normal patterns and creates a model. Uses real-time data to identify early warning signs that could lead to machine failures.
AWS Panorama Appliance: A new hardware appliance that allows organizations to add computer vision to existing on premises cameras. Plug in appliance, connects to network, and stats to identify video streams from existing cameras. Pre-built computer vision models in manufacturing, retail construction, and other industries. Can also build models in sagemaker and deploy to panorama. Integrates with AWS IoT services including sitewise, to send data for broader analysis.
AWS panorama SDK: Enables hardware vendors to build new cameras that run more meaningful computer vision models at the edge. Provides camera manufactures with an SDK and API’s to create cameras to run CV models at the edge. Chips designed for CV and deep learning form Nvidia and Ambarella. Panorama-compatible cameras work out of the box AWS ML services. Build and train models in SageMaker and deploy to cameras with a single click. 
Head of Infrastructure at Riot Games Zach Blitz tells that How Riot Games use AWS to rethink hybrid to level the playing field. He says “With Outposts, AWS gave us a unique solution to ensure a level playing field for our players and streamlined our deployments using the same tools and API’s on-premises and in the cloud.
VMware Cloud on AWS: use the same VMware software and tools on AWS. Customers reduced IT infrastructure costs by 40%. Reduced total cost of operation by 43%. Estimated 479% ROI over five years.
AWS Outposts: Run AWS infrastructure and services on-premises. AWS Servers with AWS compute, storage, database, and analytics services. Fully managed and supported by AWS. Same hardware that AWS runs in its datacentres. Same API’s, same control plane, same tools, and same functionality.
AWS Outposts in two new sizes: Smaller outposts to run AWS infrastructure in locations with less space. Run AWS compute and storage on-premises at any facility. Two sizes to fit locations with limited space. Provide 64 vCPU, 128 GB memory, 4 TB local NVMe storage. Fully managed by AWS.

AWS Local Zones: AWS infrastructure deployment that places compute, storage, and database services in large cities.
AWS Snow Family: Portable, rugged, secure devices designed for local data collection and processing in remote locations with little or no connectivity.

AWS Wavelength: Extends AWS infrastructure and services to 5G networks. Build applications that serve mobile end users with ultra-low latency. Same AWS APIs, tools, and functionality. Deploy 5G applications globally. Currently available with Verizon in eight US cities. Coming soon KDDI in Tokyo and SK Telecom in Daejeon and Vodafone in London.