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AWS Re-Invent 2020- What’s New

It is here at last! AWS re:Invent is an annual event where all the innovative services and improvements they have been working on during the year are laid out by the fine people at AWS.

We’re happy to say that we've seen some long awaited enhancements and some amazing new updates to some key AWS services.

We’re going to sum up all the big announcements from Jassy's 3-hour long keynote in this blog post. Unfortunately, if you're searching for the full video, it's not yet uploaded to YouTube, but it's available through pre-programmed re-broadcasts on the AWS re:Invent web portal (registration required). Keep on scrolling if you're only searching for a summary-you've found the right spot!

The annual re:invent conference organised by AWS this year was virtual, free and lasted three weeks. AWS unveiled innovative features, enhancements and cloud services during several keynotes and sessions. The official announcements concerning computing, databases, storage, networking, machine learning and development are reviewed below.



Amazon DevOps Guru

What's that?

It has been defined by AWS as a new machine learning-powered operations service that makes it easier for developers to improve the availability of applications by detecting operational problems automatically and providing customized feedback and detailed remediation actions.

How is it working?

In order to automatically capture and evaluate data such as application metrics, logs, incidents, and traces to detect activities that deviate from systematic management patterns (e.g. under-provisioned processing power, over-use of database I/O, memory leaks, etc.), it integrates machine learning guided by years of and AWS operations. As Amazon DevOps Guru detects anomalous application behavior (e.g. increased latency, error rates, resource constraints, etc.) that may cause possible outages or service disruptions, it informs developers through Amazon Simple Notification Service (SNS) and partner integrations such as Atlassian Opsgenie and PagerDD with problem information (e.g. resources involved, issue timeline, relevant events, etc.) It will also spit out particular remediation suggestions.

How is it helping?

Developers may use Amazon DevOps Guru remediation tips to reduce the time to fix problems when problems occur. With Amazon DevOps Guru, there are no upfront costs or obligations, and customers just pay for the analysis of Amazon DevOps Guru results.


AQUA (Advanced Query Accelerator)

What's that?

AWS announced AQUA (Advanced Query Accelerator) for Amazon Redshift, AWS Glue Elastic Views and Amazon QuickSight Q, three new analytics capabilities that the company says improve Amazon Redshift data warehouse efficiency, make it easier for people to transfer and integrate information throughout data stores, and make it easier for end users to get even more value from their business information using machine lea

How is it working?

With a new hardware-accelerated cache that carries the computer to the storage and provides up to 10 times better query output than any other cloud data warehouse, AQUA for Amazon Redshift speeds up querying, with general release arriving in January 2021.

AWS Glue Elastic Views lets developers construct applications with materialized views that use data from various data stores that automatically integrate and duplicate data through servers, data warehouses, and databases.

How is it helping?

Amazon QuickSight Q provides Amazon QuickSight with a machine learning-powered capability that allows users the ability to use natural language expressions in the Amazon QuickSight Q search bar to ask business questions and receive high precision responses in seconds.


AWS announces Mac instances for Amazon EC2

What's that?

For Amazon Elastic Compute Cloud, AWS announced new Mac instances (EC2 Mac instances) (Amazon EC2). EC2 Mac instances, based on Mac mini computers, enable customers for the first time ever to run on-demand macOS workloads in the AWS cloud. Developers developing apps for iPhone, iPad, Mac, Apple Watch, Apple TV, and Safari can now provide and navigate macOS ecosystems within seconds with EC2 Mac instances, dynamically scale capability as necessary, and benefit from the pay-as-you-go pricing of AWS.

How is it working?

This offers developers additional options so that they can use Mac as their trusted platform, on-site or in the cloud. The architecture of cross-platform Apple, Windows, and Android applications on AWS can also be consolidated by consumers, contributing to improved developer efficiency and improved time to market. Customers can easily use EC2 Mac instances along with AWS services and features such as Amazon Virtual Private Cloud (VPC) for network security, Amazon Elastic Block Storage (EBS) for expandable storage, and Amazon System Images (AMIs) for orchestration of OS images, similar to other Amazon EC2 instances. The usability of EC2 Mac instances often offloads the heavy lifting to AWS that comes with infrastructure management.

How is it helping?

In the US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Singapore) regions, EC2 Mac instances are available to be bought on demand or with savings plans, with other regions coming soon.


New Gravitron c6gn instances

What's that?

Gravitron is taking on AWS to create their own CPUs. Jassy himself stated that on their EC2 side, he did not anticipate the amount of interest they had seen in this chip.

How is it working?

Jassy confirmed today the c6gn series of EC2 instances that provide 100 Gbps network bandwidth, 38 Gbps EBS (Elastic Block Store Bandwidth), network enhancements, and a price/performance model that is more attractive. This is a major step up (over 4x more output in some instances!) from the classic c6g instances.

How is it helping?

To match your operational needs, C6gn instances will be available in a range of sizes. These examples are likely to be available in the second half of this month (December 2020). AWS Graviton2-powered instances of C6gn, a compute-heavy instance that the company said could provide 100 Gbps networking efficiency over equivalent current generation x86-based instances, and provide 40 percent better price performance. For cloud-native applications, Graviton2 is configured and is based on 64-bit Arm Neoverse cores and a customized AWS-designed chip framework.


ECS and EKS Anywhere

What's that?

In the AWS ecosystems, ECS (Elastic Container Service) and EKS (Elastic Kubernetes Service) are two services which provide support for container management. The most common containerization product currently is Docker, where designers can use an easy-to-design Dockerfile to customize and release their instances.

How is it working?

AWS closes the difference between cloud-based and on-premise workforces with ECS and EKS everywhere. The concept of this service is to enable you to use your own hardware and in your own data centers to run the ECS and EKS frameworks.Based on the strengths of Amazon EKS Distro (the same Kubernetes that power EKS on AWS), EKS Anywhere introduces a reliable AWS management experience to your data centre, building on the strengths of Amazon EKS Distro (the same Kubernetes that power EKS on AWS). EKS Anywhere prevents you from the complexity of purchasing or building your own management tools to construct EKS Distro clusters, customize the operating system, upgrade applications, and handle backup and recovery.

How is it helping?

EKS Anywhere helps you to simplify the management of clusters, lower the cost of support and remove the redundant effort of using several open source or third party software to run Kubernetes clusters. EKS Everywhere is provided in full by AWS. Moreover, you can use the EKS console to display all of your Kubernetes clusters, running anywhere.

A challenge many programmers can relate to, security, has been solved by these new products. Companies can now store their data on the spot and lock it in their data center. In the cloud, less critical workloads can still be run at all times.


Sagemaker Data Wrangler

What's that?

The data prep issue that comes with machine learning is solved by Sagemarker Data Wrangler. Designers also need to obtain, clean, modify, and integrate data in their data storage before Machine Learning applications can consume it.

How is it working?

Data Wrangler enables developers to quickly point information to a data store and observe data wrangler understand the range of data types in their database.

What's more, programmers get a UI for their dataset to merge, build, preview, and apply transformations. The infrastructure needed to transform your dataset is instantly provisioned and implemented on top of this.

With Data Wrangler, developers no longer need to think about the semantics of infrastructure provisioning and deployment to prepare their data, but can instead leverage easy-to-use tools from AWS.

How is it helping?

With over 300 pre-configured data processing built-in, Data Wrangler supports users to convert column types or ascribe missing data with mean or median values. Some built-in simulation tools are also available to help detect possible errors, as well as tools to verify whether data discrepancies occur and to analyze them before the designs are launched.

In addition, the company is also introducing the SageMaker Feature Shop, a new service that makes things simpler to mark, coordinate, locate and exchange machine learning capabilities in the SageMaker Studio.

Sagemaker Pipelines, a new service incorporated with the rest of the platform that offers a CI/CD service for machine learning to build and automate workflows, as well as an audit trail for model elements such as training data and parameters, is also being introduced by AWS.


AWS Protons

What's that?

AWS Proton is a new service intended to help companies simplify and maintain serverless and container-based software for infrastructure provisioning and code deployments. In order to link and organize all the various skills required for infrastructure provisioning, code deployment, monitoring, and updates, platform teams may use Proton. 

How is it working?

The method of describing a service template includes the concept of cloud resources, continuous integration, and continuous delivery (CI/CD) pipelines, and observability tools for the more analytically competent. With widely used CI/CD pipelines and observability tools such as CodePipeline and CloudWatch, AWS Proton can incorporate. It also includes tailored models for daily use cases, such as web services running on AWS Fargate or stream analysis apps built on AWS Lambda, following AWS best practices.

How is it helping?

AWS Proton provides platform teams with the tools that provide developers with a simple way to use containers and serverless technology to deploy code.

The framework team will create a stack consisting of templates that use a microservice to identify and configure AWS services, including identity, tracking, a CI/CD pipeline framework that sets the code compilation, and the process of testing and deployment. Except for the actual application code, this is all that is required to launch a microservice. The platform team will release stacks on the Proton console describing different use cases for microservices.


Amazon Monitron

What's that?

Amazon Monitron is a condition monitoring service system to detect infrastructure and send signals when the facilities can break down to the engineering team. It helps them to incorporate a predictive management system if industrial businesses know when machinery is breaking.

AWS has a new hardware unit, the AWS Panorama Appliance, which, in addition to the AWS Panorama SDK, can convert "dumb" existing on-site cameras into super-powered visio computer surveillance systems.

The new Panorama Appliance will run those models on video feeds from interconnected or network-enabled cameras alongside computer vision models that businesses can build using Amazon SageMaker.

How is it working?

For industrial companies which want to conduct proactive analytics and save money, they list them as game-changers.

Manufacturing and processing businesses may use machine learning to improve the consumer relationship and plant operations, but often lack the equipment or talent to make it possible. Manufacturing firms realize that repairing something before it fails is much less costly, saving the risk of cash downtime. Many businesses do not know how to take data from sensors, submit it to the cloud, and draw conclusions for machine learning.

How is it helping?

Monitron offers a gateway device for these customers to send information to AWS, who will create custom machine-learning models in turn. The model of machine learning will generate an image of what "normal" looks like and highlight deviations delivered back via a mobile app. Corporations then know when planned analytics is to be performed. It is a huge deal.


Amazon Connect Improvements

The need for call center agents to operate from home is greater than ever with the Covid pandemic. Technology has generally neglected this area and is ripe for re:invention. In order to make call centers much easier to build, maintain, and run, AWS has invested heavily in this area and introduced some new improvements.

Amazon Connect Wisdom is the first ad. This function aggregates data for your agents on the fly from your data store as the call occurs. To collect specific customer information, operators no longer need to struggle with various resources and databases and can instead have the information automatically presented to them.

Second comes Amazon Customer Profiles Bind. Through this enhancement, it is possible to proactively gain more context into your clients before and while a call takes place. This means drawing up a history of past calls and gathering your agents with all that data.

Amazon Link Tasks came seventh. I think of this as an Asana feature for call centers. This allows administrators to build, delegate, and monitor tasks for their agents. Depending on how active their agents are, or how much time remaining they have in their shift, they can also delegate tasks. Uh, sweet!

Amazon Connect Voice Id. is finally coming. Don't you hate calling and memorizing your name, email, and everything else in some place? I certainly do. Connect Voice ID is designed to establish the audio imprint of your voice so that the agent can instantly recognise you. When calling in, no more irritating questions!


While a huge event such as AWS re: Invent in a single article is hard to do justice, I hope I've benefited you by illustrating my top list of most effective non-compute announcements and the value of each. The commentary by Andy Jassy is an impressive kick-off to the event this year, clearly demonstrating the push of AWS that provides consumer services that help encourage invention and promote cloud adoption. There are still more major announcements in store with three weeks of keynote speeches and workshops for re:Invent this year that we will continue to highlight here.

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