The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now support distributed training of TensorFlow deep learning models with near-linear scaling efficiency up to 256 GPUs. The AWS Deep Learning AMIs come pre-built with an enhanced version of TensorFlow that is integrated with an optimized version of the Horovod distributed training framework to provide this level of scalability. With this enhancement, you can now train the ResNet50 model with TensorFlow-Horovod in just under 15 minutes.
Announcing the Public Preview of Amazon RDS on VMware
Amazon RDS on VMware is a service, now in preview, that delivers Amazon RDS managed relational databases in VMware vSphere on-premises data centers. RDS on VMware automates database provisioning, operating system and database patching, backup, point-in-time restore, storage and compute scaling, instance health monitoring, and failover.
Amazon Lightsail Now Supports Resource Tagging
Starting today, you can now add tagging to your Lightsail resources, including virtual servers, managed databases, load balancers, block storage, snapshots, and DNS zones. Lightsail tags allow you to easily organize your projects, create cost allocation reports for billing, and enable access control for your resources.
Introducing AWS DeepRacer
Developers, start your engines. We are excited to introduce the preview of AWS DeepRacer, the fastest way to get rolling with machine learning, literally. Get hands-on with a fully autonomous 1/18th scale race car driven by reinforcement learning, 3D racing simulator, and global racing league. You can pre-order your AWS DeepRacer now on amazon.com.
AWS IoT Greengrass Now Supports Amazon SageMaker Neo and ML Inference Connectors on Edge Devices
AWS IoT Greengrass now supports Amazon SageMaker Neo. Neo enables machine learning models to train once and run anywhere in the cloud and at the edge. Neo automatically optimizes TensorFlow, MXNet, PyTorch, ONNX, and XGBoost models for deployment on ARM, Intel, and Nvidia processors. Optimized models run up to twice as fast and consume less than a tenth of the memory footprint. Neo will also be available as open source code under the Apache Software License soon, enabling hardware vendors to customize it for their processors and devices. Using Neo with AWS IoT Greengrass, you can retrain these models in Amazon SageMaker, and update the optimized models quickly to improve intelligence on these edge devices. You can use a broad range of devices based on the Nvidia Jetson TX2, Arm v7 (Raspberry Pi), or Intel Atom platforms.
Amazon Lightsail Now Provides an Upgrade Path to EC2
Starting today, you can easily export Lightsail instances and volumes to EC2 with a simple, guided experience. With this feature, Lightsail offers an additional way to grow your applications and scale your cloud deployments by utilizing the full selection and configurability of EC2.
Introducing AWS App Mesh – Service Mesh for Microservices on AWS
AWS App Mesh is a service mesh that allows you to easily monitor and control communications across microservices applications.
Amazon EC2 Now Lets you Pause and Resume Your Workloads
You can now hibernate your Amazon EC2 instances backed by Amazon EBS and resume them at a later time. Applications can pick up exactly where they left off instead of rebuilding the memory footprint all over again. For example, applications that rely on caches and other memory-centric components can take tens of minutes to preload or warm up. These factors impose a delay and can force you to over-provision in case you need incremental capacity very quickly. Using hibernate, you can maintain a fleet of pre-warmed instances with memory footprint that can get to a productive state faster. You can do this without modifying your existing applications. Hibernate is just like closing and opening your laptop lid, with your application starting up right where it left off.
Upon hibernation, your instance’s EBS root volume and any other attached EBS data volumes are persisted between sessions. Additionally, data from memory (RAM) is also saved to your EBS root volume. Upon resume, your EBS root device is restored from its prior state, including the RAM content. Previously attached data volumes are reattached and the instance retains its instance ID. While the instances are in hibernation, you pay only for the EBS volumes and Elastic IP addresses attached to it.
This feature is available for On-Demand and Reserved Instances running on freshly launched M3, M4, M5, C3, C4, C5, R3, R4, and R5 instances running Amazon Linux 1. The AMI snapshot used to launch the instance must be encrypted. This ensures protection of sensitive contents in memory (RAM) as they get copied to the root volume.
You can enable hibernation for your EBS-backed instances at launch. You can then hibernate and resume your EBS-backed EC2 instances through the AWS Management Console , or though the AWS SDK and CLI using the existing stop-instances and start-instances commands.
EC2 Instance Hibernation is now available in the US East (N. Virginia, Ohio), US West (N. California, Oregon), Canada (Central), South America (Sao Paulo), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Tokyo), and EU (Frankfurt, London, Ireland, Paris) Regions.
To learn more about hibernation, visit this blog . For information about enabling hibernation for your EC2 instances, visit our FAQs or technical documentation .
Introducing AWS License Manager
AWS License Manager makes it easier to manage licenses in AWS and on premises servers from software vendors such as Microsoft, SAP, Oracle, and IBM. AWS License Manager lets administrators create customized licensing rules that emulate the terms of their licensing agreements, and then enforces these rules when an instance of EC2 gets launched. Administrators can use these rules to limit licensing violations, such as using more licenses than an agreement stipulates or reassigning licenses to different servers on a short-term basis. The rules in AWS License Manager enable you to limit a licensing breach by physically stopping the instance from launching or by notifying administrators about the infringement. Administrators gain control and visibility of all their licenses with the AWS License Manager dashboard and reduce the risk of non-compliance, misreporting, and additional costs due to licensing overages.
WS License Manager integrates with AWS services to simplify the management of licenses across multiple AWS accounts, IT catalogs, and on premises, through a single AWS account. License administrators can add rules in AWS Service Catalog, which allows them to create and manage catalogs of IT services that are approved for use on all their AWS accounts. Through seamless integration with AWS Systems Manager and AWS Organizations, administrators can manage licenses across all the AWS accounts in an organization and on-premises environments. AWS Marketplace buyers can also use AWS License Manager to track bring your own license (BYOL) software obtained from the Marketplace and keep a consolidated view of all their licenses.
To learn more access the AWS License Manager page.
Introducing AWS Cloud Map
AWS Cloud Map is service discovery for all your cloud resources. With Cloud Map, you can define custom names for your application resources, and it maintains the updated location of these dynamically changing resources. This increases your application availability because your web service always discovers the most up-to-date locations of its resources.