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    Home Cloud
    • Cloud

    AWS Pushes Forward on Cloud Security, Database and AI Initiatives

    By
    SEAN MICHAEL KERNER
    -
    March 28, 2019
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      AWS Deep Learning Containers

      Amazon Web Services (AWS) is the leader in the public cloud market and it shows no signs of slowing down anytime soon.

      At the AWS Summit in Santa Clara on March 27, the public cloud provider announced several new services and capabilities, while reinforcing core elements of its platform growth including artificial intelligence and security. Among the new services is a concurrency service for the Redshift data warehouse, deep learning containers and the general availability of the App Mesh service mesh. Across all aspects of the cloud however, AWS sees security as being a foundational element.

      “I really want to emphasize that security is everyone’s job,” Amazon CTO Werner Vogels said during his keynote. “Because in the future, it is us as technologists that are responsible for protecting our customers and our businesses.”

      Among the core areas of innovation that Vogels spent time discussing is AWS’ expanding database capabilities in the cloud, which he sees as a key differentiator against rivals, including Oracle. Vogels said that because AWS has a new architecture that isn’t reliant on legacy models for database deployment, it has been able to apply distributed systems techniques that have improved overall reliability and performance.

      “Everyone is looking to get more value out of their data,” Vogels said. “One of the things that cloud has done is make the whole IT landscape egalitarian, where everybody has access to the same storage, the same compute, the same databases, the same analytics tools and the same IoT tools.”

      As such, Vogels argued that IT capabilities are no longer a competitive differentiator. In his view, the differentiator is the kind of data that organizations have and how they make use of that data.

      Amazon Redshift

      Amazon’s Redshift is a cloud data warehouse service and is a key part of AWS’ strategy for helping organizations to get the most value out of their data. Vogels said that over the past two years, AWS has made Redshift ten times faster with various improvements. At AWS Summit Santa Clara, Vogels announced a new concurrency scaling feature for Redshift hat automatically adds and removes capacity to handle unpredictable demand from concurrent users.

      “We basically make burst clusters available for you, so if we queries  rising to the point where you actually have to wait to execute the query, we can fire up additional clusters for you such that your customers never have to wait,” Vogels said.

      Artificial Intelligence: Deep Learning Containers

      AWS has also been investing heavily in artificial intelligence capabilities, with multiple services, including Sagemaker which was first announced at the AWS re:invent conference in 2017. At the Santa Clara Summit AWS announced a new effort called AWS Deep Learning Containers.

      Matt Wood, General Manager of Deep Learning and AI at AWS said that with Sagemaker, AWS has provided a fully managed service, but there is also a need for those that want a Do-It-Yourself (DIY) approach, which is where the Deep Learning Containers fit in.

      “Deep Learning Containers allow you to quickly set up deep learning environments up on EC2 using Docker containers and they can run on Kubernetes, ECS (Elastic Container Service) or EKS (ECS for Kubernetes Service),” Wood said. 

      App Mesh

      The other big announcement at AWS Summit Santa Clara was the general availability of AWS App Mesh, which was first announced in preview at the AWS re:invent conference in 2018. 

      App Mesh is based on the open-source Envoy network project, which is a project that was first started by ride sharing company Lyft and contributed to the Cloud Native Computing Foundation (CNCF) in 2017. The App Mesh is AWS’ approach for enabling what is known as a service mesh.

      “App Mesh gives you a simple, declarative approach to model service communication,” Vogels explained. “You can define rules for service-to-service communication and everything else is handled automatically. Use it as a single point of control for all the communications between services in an application.”

      Sean Michael Kerner is a senior editor at eWEEK and InternetNews.com. Follow him on Twitter @TechJournalist.

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