AWS re:Invent 2017, chapter 17 was one of the most exuberant experience for all its attendees. The thought leadership team of Botmetric not only had the opportunity to be part of the event but also create their own wave of magic at booth #329.
Here is a quick recap of all the exciting releases that AWS announced this year, targeting Cybersecurity, Machine learning, Serverless computing, Automation and its flavours.
- Amazon EC2 Bare Metal instances : This new addition in the family of EC2 machines provide your applications with direct access to the processor and memory of the underlying server. These instances are ideal for workloads that require access to hardware feature sets (such as Intel VT-x), or for applications that need to run in non-virtualized environments for licensing or support requirements.
- Guard duty : “Security is everyone’s job”, commented Amazon CTO Werner Vogels. Amazon GuardDuty gives you intelligent threat detection by collecting, analyzing, and correlating billions of events from AWS CloudTrail, Amazon VPC Flow Logs, and DNS Logs across all of your associated AWS accounts. GuardDuty uses machine learning to detect anomalous account and network activities.
- AWS Sagemaker : Easily build ML models and get them ready for training by providing everything you need to quickly connect to your training data, and to select and optimize the best algorithm and framework for your application. Sagemaker allows you to learn, build and deploy machine learning models in the simplest of manner.
- Amazon MQ : The messaging middleware that simplifies and accelerates the integration of diverse applications and business data across multiple platforms. It uses message queues to facilitate the exchange of information and offers a single messaging solution for cloud, mobile, IoT, and on-premises environments.
- Amazon Aurora Serverless : Designed for workloads that are highly variable and subject to rapid change, this new configuration allows you to pay for the database resources you use, on a second-by-second basis. This serverless model builds on the clean separation of processing and storage that’s an intrinsic part of the Aurora architecture.
- Deep lens : A machine learning technique that uses neural networks to learn and make predictions – through computer vision projects, tutorials, and real world, hands-on exploration with a physical device. AWS DeepLens lets you run deep learning models locally on the camera to analyze and take action on what it sees.
- Amazon Rekognition : Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API, and the service can identify the objects, people, text, scenes, and activities, as well as detect any inappropriate content. It is a simple and easy to use API that can quickly analyze any image or video file stored in Amazon S3.
- Cloud 9 : AWS Cloud9 is a cloud-based integrated development environment (IDE) that lets you write, run, and debug your code with just a browser. Cloud9 provides a seamless experience for developing serverless applications allowing you to easily define resources, debug, and switch between local and remote execution of serverless applications. With Cloud9, you can quickly share your development environment with your team, allowing you to pair program and track each other’s inputs in real-time.
- S3 Select : S3 Select, launching in preview, enables applications to retrieve only a subset of data from an object by using simple SQL expressions. By using S3 Select to retrieve only the data needed by your application, you can achieve drastic performance increases – in many cases, you can get as much as a 400% improvement.
While the re:Invent was an exhilarating experience for all the attendees Botmetric seized the opportunity to release their public cloud usage report that stirred a wave of magic amongst cloud enthusiasts.