[1] This week, Amazon's Web Services (AWS) kicked off its 10th re:Invent conference, an event where it typically announces the
biggest changes in the cloud computing industry's dominant platform. This year's news includes faster chips, more aggressive artificial intelligence, new developer-friendly tools, and even a bit of quantum computing for those who want to explore its ever-growing potential.
Amazon is working to
lower costs by boosting the performance of its hardware. Its new generation of machines powered by the third generation of AMD's EPYC processors, the M6a, is touted as offering a 35% boost in price/performance over the previous generation of M5a machines built with the second generation of the EPYC chips.
In addition to addressing price-performance ratios, Amazon is looking to please developers by simplifying the process of building and running more complex websites. A number of the announcements focus on enhancing tools that automate many of the small tasks that take up developer resources.
Developers who base their workloads on containers will find things a bit faster because AWS is building a pull-through cache for the public containers in the Elastic Container Registry. This will simplify and speed up the work of deploying code built on top of these public containers.
Amazon also anticipates that it could improve security by providing a more trustworthy path for the code.
Additionally, for those with an eye toward the deepest part of the future where
quantum computers may dominate, AWS is expanding and simplifying its cloud quantum offering called Braket.
>> Read more.
[2] During a keynote address today at its re:Invent 2021 conference,
Amazon announced SageMaker Canvas, which enables users to create machine learning models without having to write any code. Using SageMaker Canvas, Amazon Web Services (AWS) customers can run a
machine learning workflow with a point-and-click user interface to generate predictions and publish the results.
"Now, business users and analysts can use Canvas to generate highly accurate predictions using an intuitive, easy-to-use interface," CEO of AWS, Adam Selipsky said onstage. "Canvas uses terminology and visualizations already familiar to [users] and complements the data analysis tools that [people are] already using."
With Canvas, Selipsky says that customers can browse and access petabytes of data from both cloud and on-premises data sources, such as Amazon S3, Redshift, and local files. Canvas uses
automated machine learning technology to create models, and once the models are created, users can publish results, explain and interpret the models, and share dashboards and the models with each other to collaborate and enrich insights.
>> Read more.
[3] In response to evolving security requirements in the cloud, Amazon Web Services (AWS) today announced several new features for improving and
automating the management of vulnerabilities on its platform. Newly added capabilities for the
Amazon Inspector service will meet the "critical need to detect and remediate at speed" in order to secure cloud workloads, according to a post on the AWS blog, authored by developer advocate Steve Roberts. The announcement came in connection with the AWS re:Invent conference, which began today.
In a second security announcement, AWS unveiled a new secrets
detector feature for its Amazon CodeGuru Reviewer tool, aimed at automatically detecting secrets such as passwords and API keys that were inadvertently committed in source code.
The security updates from AWS come as enterprises continue their accelerated shift to the cloud, and as security teams have struggled to keep up.
>> Read more.
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