We’re excited to announce the availability of Lumberyard Beta 1.15. With over 270 improvements, fixes, and new features, we’re focusing on how Lumberyard’s integration with AWS enables game developers of all sizes to connect their games and accelerate game development. Some highlights include: 

Commercially-available luminaires sold with efficacy claims in the 200-lm/W range deliver mixed results in US Department of Energy testing at PNNL, with glare being a recurring issue and most products falling short of efficacy specifications.

CEO Eric Rondolat reverses his outlook from three months ago, while Signify’s second-quarter results fall. There are bright spots, though, as lighting’s transition fights on.

Now, you can use Amazon DynamoDB global tables to replicate table data to three additional Asia Pacific AWS Regions. Global tables is now available in the Asia Pacific (Tokyo), Asia Pacific (Seoul), and Asia Pacific (Sydney) Regions.

Global tables builds upon the global footprint of DynamoDB to provide you a fully managed, multi-region, multi-master database. It enables you to replicate table updates automatically across the AWS Regions you select. With global tables, you can give massively scaled, global applications local access to Amazon DynamoDB tables for fast read and write performance. You can also use global tables to replicate DynamoDB table data to additional AWS Regions for higher availability.

With this launch, DynamoDB global tables is now available in the Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Sydney), Asia Pacific (Singapore), EU (Frankfurt), EU (Ireland), US West (Oregon), US East (Ohio), and US East (N. Virginia) Regions.

For global tables pricing in the Asia Pacific (Tokyo), Asia Pacific (Seoul), and Asia Pacific (Sydney), see Global Tables Pricing .

AWS Elemental MediaTailor is a content personalization and monetization service that lets you serve video with targeted ads to viewers while maintaining broadcast quality-of-service in multiscreen video applications.

AWS Service Catalog , used by enterprises, system integrators, and managed service providers to organize, govern, and provision cloud resources on AWS, now supports CloudFormation Change Sets. This also includes CloudFormation Transforms, which provides capability for the Serverless Application Model (SAM).

Amazon RDS now provides automated recommendations for your database resources. Amazon RDS recommendations provide best practice guidance for customers by analyzing configuration and usage metrics from database instances. The resulting recommendations are presented in the AWS Console in an easy-to-use interface.  

Now, you can use Amazon DynamoDB Accelerator (DAX) r4 instance types in the Asia Pacific (Tokyo) Region. r4 instance types are the latest generation of DAX nodes and are designed to support production applications and workloads.

DAX provides you a fully-managed, highly available, in-memory cache for DynamoDB that is capable of accelerating reads from Amazon DynamoDB tables by up to 10x, even at millions of requests per second. You can use DAX without making changes to your existing application logic and using your current DynamoDB API calls. DAX manages cache invalidation and data population on your behalf.

DAX is available in the US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), South America (São Paulo), EU (Ireland), Asia Pacific (Singapore), Asia Pacific (Tokyo), Asia Pacific (Sydney), and Asia Pacific (Mumbai) Regions.

For DAX r4 instance type pricing in the Asia Pacific (Tokyo) Region, see DAX Pricing .

AWS Deep Learning AMIs now come pre-installed with Open Neural Network Exchange (ONNX), an open source format for neural network computational graph supported by popular deep learning frameworks , including Apache MXNet, TensorFlow, PyTorch, Chainer, and Cognitive Toolkit (CNTK). ONNX gives developers the flexibility to migrate between frameworks. For example, developers can use PyTorch for prototyping, building and training their models, and then use ONNX to migrate their models to MXNet to leverage its scalability for inference. To learn more about using ONNX, see our blog post and tutorials .  

AWS Greengrass now allows you to deploy executables written in C, C++ and any other language that supports importing of C libraries. Executable code has the benefits of greater legacy support as customers can more easily re-use code that is already written in C or C++, minimal resource footprint as no language interpreter is required, and an absolute minimum of compute latency for very high-performance use cases such as computer vision or algorithmic trading. Starting today, your executable code acts much like an AWS Lambda function, can be invoked by events or invoke other Lambdas, and can take advantage of other Greengrass functionality such as Local Resource Access. You can mix and match executable code together with Lambda functions written in interpreted languages such as Python or Node.js.