AWS Sydney Summit

This conference focus was machine learning. There are some highlight points.

  1. Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models. You can now use TensorFlow version 1.6 and Apache MXNet version 1.1 with the Amazon SageMaker pre-built deep learning framework containers.

  2. Amazon Translate and Amazon Transcribe are now generally available.

  3. AWS DeepLens is the world’s first deep-learning enabled video camera for developers of all skill levels to grow their machine learning skills through hands-on computer vision tutorials, example code, and pre-built models. You can train your models in Amazon SageMaker, a machine learning platform to train and host your models. AWS DeepLens offers a simple 1-click deploy feature to publish trained models from Amazon SageMaker. You can run the models that you have deployed to AWS DeepLens without being connected to the internet.

  4. AWS Greengrass is software that lets you run local compute, messaging, data caching, sync, and ML inference capabilities on connected devices in a secure way. With AWS Greengrass, connected devices can run AWS Lambda functions, execute predictions based on machine learning models, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet.

  5. AWS AppSync is a new service that enables developers to manage and synchronize mobile app data in real time across devices and users, but still allows the data to be accessed and altered when the mobile device is in an offline state. The service further allows developers to optimize the user experience by selecting which data is automatically synchronized to each user’s device when changes are made, minimizing storage and bandwidth requirements, with a query language called GraphQL.

  6. AWS Cloud9 is a cloud-based integrated development environment (IDE) that lets you write, run, and debug your code with just a browser. It combines the rich code editing features of an IDE such as code completion, hinting, and step-through debugging, with access to a full Linux server for running and storing code.

  7. AWS CodeStar is a cloud‑based development service that provides the tools you need to quickly develop, build, and deploy applications on AWS. Use GitHub directly within AWS CodeStar’s continuous integration and continuous deployment (CI/CD) toolchains, and manage your software release workflow including code commits, builds, and deployments for AWS applications in one place.

  8. The AWS Serverless Application Model (AWS SAM) is a model to define serverless applications. AWS SAM is natively supported by AWS CloudFormation and defines simplified syntax for expressing serverless resources. Based on AWS SAM, SAM Local is an AWS CLI tool that provides an environment for you to develop, test, and analyze your serverless applications locally before uploading them to the Lambda runtime.