Amazon EC2 has the cloud’s broadest and most capable portfolio of hardware-accelerated instances featuring GPUs, FPGAs, and our own custom ML inference chip, AWS Inferentia. G4dn instances offer the best price/performance for GPU based ML inference, training less-complex ML models, graphics applications others that need access to NVIDIA libraries such as CUDA, CuDNN and NVENC. 

Today, the Amazon Builders’ Library published a new article titled, Avoiding overload in distributed systems by putting the smaller service in control . AWS Senior Principal Engineer Joe Magerramov dives deep into the strategies for avoiding the larger service from overloading the smaller one by putting the smaller service in control of the pace of interactions.

Amazon Lumberyard 1.26 Beta is now available for download, bringing you a range of updates including major improvements to Dynamic Terrain and Landscape Canvas, the general availability (GA) of the PhysX Gem (now with joint support and samples), a full preview release of the new Lumberyard UI (“UI 2.0”), usability improvements to the White Box Tool, updated GameLift support, and new tutorial guides to help you get started with 1.26. 

When using CloudWatch Synthetics, you can now get a snapshot of the canary health with a prebuilt monitoring dashboard. The new monitoring dashboard provides canary data trends over time for latency, availability, and error counts. The dashboard also provides expected latency based on historical data of the previous canary runs. This helps you spot anomalies sooner which in turn allows you to respond faster to ensure a better end user experience.  

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). With a single click, data scientists and developers can quickly spin up SageMaker Studio Notebooks for exploring datasets and building models. Starting today, you can choose to launch SageMaker Studio in your Amazon Virtual Private Cloud (VPC) for fine-grained control on network access and internet connectivity of SageMaker Studio Notebooks. You can choose to completely disable public internet access for notebooks to add an additional layer of security.  

Distributed Load Testing on AWS helps you easily simulate thousands of users connecting to your application so that you can better understand your application performance under load. The solution launches and configures containers on AWS Fargate to generate a specified number of transactions per second without having to provision servers. 

Customers that use Amazon Simple Notification Service (Amazon SNS) to send text messages (SMS) to mobile users can now host their application in the US East (Ohio), South America (Sao Paulo), Europe (Stockholm), Europe (Paris), and Middle East (Bahrain) regions. Using Amazon SNS, customers can send a message directly to one phone number , or multiple phone numbers at once by subscribing those phone numbers to a topic and sending messages to the topic. Customers can send SMS text messages directly to mobile phone numbers in more than 200 countries.

You can now configure your Amazon Lex chat bot to improve engagement with customers who speak British English. Amazon Lex allows you to create intelligent conversational chatbots that can be used with Amazon Connect to automate high volume interactions without compromising customer experience. Customers can perform tasks such as changing a password, requesting a balance on an account, or scheduling an appointment using natural conversational language. Customers can say things like “I need help with my device” instead of having to listen through and remember a list of options like 1 for sales, or 2 for appointments. Pre-defined resources (‘slots ’), such as regional names and cities, are localized to the British English dialect to improve accuracy when capturing information, so customers can say things like “Book a hotel in London” and the Amazon Lex bot will recognize the city.  

You can now use Amazon Lex chatbots in the Asia Pacific (Tokyo) AWS region. Amazon Lex allows you to create intelligent conversational chatbots that turn your Amazon Connect contact flows into natural conversations. These can be used to automate high volume interactions without compromising customer experience. Customers connecting to your Amazon Connect contact center can interact with an Amazon Lex chatbot to perform tasks such as changing a password, requesting a balance on an account, or scheduling an appointment using natural conversational language. Customers can say things like “I need help with my device” instead of having to listen through and remember a list of options like 1 for sales, or 2 for appointments. 

You can now configure your Amazon Lex chat bot to improve engagement with customers who speak Australian English. Amazon Lex allows you to create intelligent conversational chatbots that can be used with Amazon Connect to automate high volume interactions without compromising customer experience. Customers can perform tasks such as changing a password, requesting a balance on an account, or scheduling an appointment using natural conversational language. Customers can say things like “I need help with my device” instead of having to listen through and remember a list of options like 1 for sales, or 2 for appointments. Pre-defined resources (‘slots ’), such as regional names and cities, are localized to the Australian English dialect to improve accuracy when capturing information, so customers can say things like “Book a hotel in Perth” and the Amazon Lex bot will recognize the city.