AWS Announcements at a Glance: The Highlights from AWS in June 2020

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The AWS EMEA summit took place on June 17, 2020. Thanks to the increased requirement for events to be virtual, the EMEA summit was more global in reach than ever. Another great virtual conference for new and existing AWS customers. If you missed it, do not worry as you can get the on-demand presentations by registering here. This summit focused on machine learning, application and architecture modernization, security, and of course the deep racer league!

June saw a fair share of exciting announcements and service updates from AWS. This blog post is not intended to be an exhaustive list of all the AWS announcements in June, but is instead a curated selection that we believe will benefit enterprise thought leaders working to drive cloud adoption and efficiency within their organizations. Some of the highlights from June include the release of new Well-Architected Lenses, AWS CodeArtifact, 3D Point Cloud Labeling using Amazon SageMaker Ground Truth, a Shared File System for AWS Lambda Functions, AWS Snowcone, and the new C6g and R6g instances powered by AWS Graviton 2 processors.

New AWS Well-Architected Lenses

In just three short months, companies have evolved from just planning for remote work to fully working remotely. With the need to accommodate a fully remote workforce, organizations are increasingly turning to the scalable power of the Cloud as a means of supporting the shift in usage patterns. Now, the most asked question is: are you well architected? AWS developed and published the first version of the Well Architected Framework back in 2015 to guide cloud architects in building secure, high-performing, resilient, and efficient infrastructure. In addition, AWS also introduced well-architected lenses that focus on specific workload types from the well-architected perspective. Recently, they have released two new lenses:

1.) Financial Services Industry Lens which focuses on common use cases and best practices for the Financial Services industry

2.) Analytics Lens which focuses on companies who want to design and build analytics applications.

AWS CodeArtifact

A fully managed artifact repository service for developers and DevOps engineers, AWS CodeArtifact helps to securely store, publish, and share software packages used in their development, build, release, and deployment processes. AWS CodeArtifact eliminates the need for you to set up, operate and scale the infrastructure required to manage your artifacts. At launch, AWS CodeArtifact supports Java using Maven and Gradle, Javascript using npm and yarn, and lastly Python using pip and twine, which makes it easy to integrate into your existing development workflows.

AWS CloudFormation support for AWS CodeArtifact is coming soon.

For more information on AWS CodeArtifact and to get started, check out this post.

Amazon SageMaker Ground Truth for 3D Point Cloud Labeling

Amazon SageMaker Ground Truth is a fully managed data labeling service already in wide-use, that makes it easy to build highly accurate training datasets for machine learning. Data samples are automatically distributed for classification to a designated workforce (private, 3rd party vendors, or Mechanical Turk). Customers from the automotive industry expressed interest in labeling three dimensional (3D) datasets (3D Point Cloud) captured by LIDAR sensors. It is time consuming to label these large datasets (which can each be terabytes in size). Amazon SageMaker Ground Truth now comes with a built-in editor, and state-of-the-art assistive labeling features which make 3D point cloud labelling easier.

For more information visit here. In addition to this, watch a deep dive video clip that explains this further.

EFS for AWS Lambda

Traditionally, AWS lambda has internal storage space in the location /tmp, however it can only store up to 512 MB of data and doesn’t persist beyond the life of the function. Now, AWS Lambda can mount an Amazon Elastic File System (EFS). Once mounted you can use a familiar file system interface to store and retrieve data across multiple concurrent execution environments such as other lambdas, AWS EC2, AWS ECS or AWS Fargate. With this new change, it also simplifies a lot of functions that previously had to pull temporary data from Amazon S3, process the data and push it back to Amazon S3.

For more information visit here.

AWS Snowcone

A new member of the AWS Snow Family, introducing AWS Snowcone! It is like other Snow Family devices which contain services such as AWS KMS, AWS IAM, Amazon EC2, Amazon ECS, and most importantly AWS IoT Greengrass. AWS Snowcone can be used as an IoT edge computing device, a data migration tool as well as for content distribution. It is built to operate under harsh environments and with a rugged, small form factor (9″ long, 6″ wide, and 3″ tall), it is the perfect candidate for an IoT device. Data can be transferred back to your AWS environment either by shipping the device back to AWS or through the internet using AWS data sync. It has 2 CPU, 4GB of RAM, 8TB of usable storage, and has both wifi and wired networking. Users can plug in a battery for mobility.

For more information, visit here.

C6g and R6g instances powered by AWS Graviton2

Following the release of the M6g instance, which is also based on AWS Graviton 2 processors, C6g and R6g instances are now available to power compute and memory intensive workloads. Both instance types provide up to 40% better price to performance over their x86-based Amazon EC2 C5 and R5 relatives. AWS Graviton2 processors are custom-built by AWS using 64-bit ARM Neoverse N1 cores, which are optimized for running workloads in the cloud. Furthermore, with the upgraded network bandwidth, it allows workloads requiring heavy compute to be performed faster and cheaper.

For more information visit here.

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