AWS This Week

AWS This Week: AWS re:Invent 2021 special episode wrap-up

Episode description

Faye and Ryan are back with your AWS news! This week, they’ve been soaking up AWS re:Invent 2021 live from Las Vegas and are ready to wrap up with all their favorite announcements (spoiler: there’s a lot!) including EC2 C7g Instances Powered by New AWS Graviton3 Processors, the new DynamoDB table class, Amazon Inspector relaunch, so many S3 updates plus a new S3 Glacier storage class, and many more!

Introduction (0:00)
AWS Graviton3 processors to power C7g instances (0:29)
So many SageMaker updates! (0:57)
DevOps Guru for RDS & Trn1 chips for ML models (2:40)
AWS Private 5G lets you build your own private cell network (3:24)
New serverless and on-demand analytics options (3:56)
New open-source Kubernetes autoscaler Karpenter (4:26)
An avalanche of S3 updates  (4:56)
New DynamoDB Standard-Infrequent Access table class (5:58)
Amazon Inspector gets a relaunch (6:35)
ECR Pull Through Caching (7:05)
Greengrass integrated with AWS SSM (7:35)
Ryan Kroonenburg’s favorite announcements (8:04)
Faye Ellis’s favorite announcements (8:25)

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Series description

Join our ACG hosts as they recap the most important developments in the AWS world from the past week. Keeping up with ever-changing world of cloud can be difficult, so let us do the hard work sifting through announcements to bring you the best of what's new with AWS This Week.

Hello Cloud Gurus and welcome to a very special edition of AWS. This week live from reinvent 2021 in Las Vegas. This week has been jam packed with exciting AWS news, and there's so much to cover, but we will give you the rundown of our favorite announcements from the show. I'm Faye Ellis and I'm Ryan Kroonenberg, and you're watching AWS this week, reinvent special for 2021. So this week Amazon announced its next generation arm-based graviton3 processors.

They boast 25% better performance and 60% less power usage. And these chips will power the new Amazon EC2 C7g instances, which are now in preview and are ideal for compute intensive workloads like high performance computing, scientific modeling and CPU-based machine learning inferencing. Speaking of machine learning, there's been a big focus on data and machine learning this year. And there's so much to cover here. So starting with SageMaker. First up SageMaker Canvas is now in general availability and canvas is designed to help business users and analysts generate machine learning predictions using a visual, no code interface.

And this allows people like business analysts who may have little or no machine learning experience to get valuable insights from their data. Next SageMaker Ground Truth Plus is also in general availability and this new turnkey service lets you tap into a team of experts to create training data sets without having to build and manage labeling applications on your own. And you provide the data and labeling requirements and your data labeling workflows, get set up and manage for you and Amazon claims that this can reduce your cost by up to 40%, which isn't bad at all. AWS also announced Amazon SageMaker Serverless Inference, and this lets you easily deploy machine learning models for inference without the need to configure or manage underlying infrastructure. And this is ideal for applications with intermittent or unpredictable traffic and you pay only for however long you run the inference code and the amount of data processed, not for idle time.

So next up AWS announced SageMaker studio lab, which is now in preview and this free service is designed to help anyone learn and experiment with machine learning without the need for an AWS account credit card or cloud configuration knowledge. The machine learning curve can be a steep one. So with a predictable and controlled environment for hosting for your Jupiter notebooks, you can ensure you won't be racking up huge bills when you're trying to learn . Moving on from SageMaker the new AWS trainium-based EC2 TRN1 instances are now in preview and these instances are optimized for training deep learning models in the cloud and offer the best price performance for model training and 800 gigs per second, networking bandwidth. And these are ideal for use cases like language processing or image recognition.

And finally Amazon announced Amazon DevOps guru for RDS, and this is a new capability for DevOps guru and it makes it easier for developers to detect, diagnose and resolve issues in Aurora. And it's available in all regions where DevOps guru is available. So AWS private 5g will let you build your own private 5g cell network. And this service, which is in preview in the us could be ideal for use cases like a warehouse or large campuses where you're looking to help increase bandwidth and coverage or an increasing number of devices while maintaining the security and control of a private network and AWS ship, everything you need including SIM cards and there's no upfront or per device cost. Customers just pay for the network capacity and throughput that they request.

AWS announced serverless and on-demand options, which on now available for Redshift Elastic Map Reduce, manage streaming for Kafka and Kineses in preview. This means no configuration or scaling of clusters or servers, just fire them up and the services scale up when you're busy and scale down when you are not. And you pay only for when the service is in use. Check out the links in the resources below, if you would like to dig deeper into each one. So to help simplify Kubernetes infrastructure, AWS has announced Karpenter (with a K) because, you know, Kubernetes and this open source auto scaling tool is aimed at improving application availability and cluster efficiency and Karpenter automatically launches needed compute resources as application loads change. And this is welcome news to many as AWS says about half of its Kubernetes customers report that Kubernetes clusters auto scaling is challenging and restrictive.

Reinvent 2021 has given us a slew of S3 updates, including AWS backup support for S3, which is in preview, S3 event notifications with event bridge and a couple of new features that simplify access management for data stored in S3. But one of the announcements that stands out to me is the new Amazon S3 glacier instant retrieval storage class. And this new storage class will give the lowest cost storage for data that is really accessed up to 68% cheaper than the S3 standard infrequent access while also offering millisecond retrieval, which is perfect for use cases like media archives or medical images and the existing S3 glacier storage class has now been renamed to S3 glacier, flexible retrieval and offers free bulk retrievals in five to 12 hours. And the storage price has also been reduced by 10% in all regions. So how does saving 60% on DynamoDB cost sound? Well, the new standard infrequently access table class for DynamoDB aims to let you do just that DynamoDB standard infrequently access is ideal for long term storage data that is infrequently accessed, such as application logs or, or e-commerce order history.

And this table class is designed to cut storage costs while delivering the same performance durability and scaling. So DynamoDB infrequently access is now available in all regions except for China and AWS gov cloud. For more on pricing, please see the pricing page link below. Amazon announced a relaunch of Amazon inspector, which debuted originally in 2015. And this service can be used to automate security assessment and management to help organizations with security and compliance requirements for workloads deployed to AWS. Vulnerability management has changed a lot in the last six years, so AWS has built Amazon Inspector back up from scratch to do what people actually need in an enterprise environment.

So earlier in the week, Amazon announced pull through case repository support in Amazon elastic container registry and this solds another point of security friction in enterprises. So many big customers have hard rule around things like using code from outside or private systems. So AWS came up with a solution for container images instead of needing to write scripts and manage them to keep copies of public images up to date. AWS now does it automatically for you, which is pretty cool. Finally, last year, AWS launched IOT Greengrass 2.0,

an open source edge runtime and cloud service for building deploying and managing device software and applications. Now AWS has rolled out the ability to securely manage your green grass edge devices using systems manager. And this means that you can manage both your and IOT devices at scale using the same tooling. So Ryan, I have to ask, what is your favorite announcement from this year? Well, that's a really good question. It's gotta be all the new serverless offerings.

So serverless Elastic Map Reduce serverless Redshif, serverless managed streaming for Kafta. This is gonna be very cool for startups in particular. I mean we built A Cloud Guru using serverless technology, so it's always gonna have a special place in my heart. So what's your favorite Faye? Well, it's definitely SageMaker canvas drag and drop for building machine learning models and SageMaker studio lab. And I just think it's so cool that they're democratizing machine learning and making it easier for everyone to get on board.

And I'm looking forward to playing with the both of those. Yeah, that sounds pretty good too. Well, that's all we have time for now. Check out the links below for a deeper dive into many of these announcements and links to our daily video recaps. So on behalf of the team here, we'd like to thank everyone who managed to stop by our booths to say hello. It was great seeing all your faces, at least half of them anyway, in person again.

So thanks for watching and we'll see you next time on AWS this week. Keep being awesome Cloud Gurus.

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