Today, AWS Migration Hub makes it even easier to manage multiple migrations in one central location with the addition of RiverMeadow Server Migration SaaS. RiverMeadow is designed and built specifically for enterprise AWS customer migrations. This migration tool doesn’t require an agent and it performs live workload migrations, without impacting the source production environment.
New AWS Public Datasets Available from Allen Institute for Brain Science, NOAA, Hubble Space Telescope, and Others
11 new AWS Public Datasets are now available in the following categories:
Life sciences:
- The Allen Brain Observatory – Visual Coding from the Allen Institute for Brain Science
Financial:
- Eurex and Xetra Trading Data from Deutsche Börse
Environmental:
- Cornell EAS Data Lake provided by the Department of Earth and Atmospheric Sciences (EAS) at Cornell
- ECMWF’s ERA5 Reanalysis Data provided by PlanetOS
- GEOS-Chem Input Data provided by Harvard University Atmospheric Chemistry Modeling Group
- NOAA Global Historical Climatology Network Daily provided through the NOAA Big Data Project
- NOAA National Water Model Short-Range Forecast provided through the NOAA Big Data Project
- NOAA National Water Model Reanalysis provided through the NOAA Big Data Project
Astronomical:
- Hubble Space Telescope Public Data provided by the Space Science Telescope Institute
Audio:
- Voices Obscured in Complex Enrivonmental Settings (VOiCES) from SRI International and Lab41
Geospatial
- USDA National Aerial Imagery Program provided by Esri
The AWS Public Dataset Program covers the cost of storage for publicly available high-value cloud-optimized datasets. We work with data providers who seek to:
- Democratize access to data by making it available for analysis on AWS.
- Develop new cloud-native techniques, formats, and tools that lower the cost of working with data.
- Encourage the development of communities that benefit from access to shared datasets.
Learn how to propose your dataset to the AWS Public Dataset Program .
Amazon EFS Now Supports Provisioned Throughput
Today we are announcing Provisioned Throughput for Amazon Elastic File System (Amazon EFS).
Amazon ECR Achieves PCI DSS Compliance in AMER, EMEA, and APAC
Amazon Elastic Container Registry (ECR) now meets the criteria for PCI compliance in AMER, EMEA, and APAC. ECR PCI DSS compliance in China is pending approval. You can now use ECR to store, manage, and deploy Docker container images that are subject to Payment Card Industry Data Security Standard (PCI DSS) compliance. In addition to Amazon ECR, Amazon Elastic Container Service (ECS) also already meets the criteria for PCI compliance in AMER, EMEA, and APAC.
PCI DSS is a proprietary information security standard administered by the PCI Security Standards Council and applies to all entities that store, process or transmit cardholder data and/or sensitive authentication data including merchants, processors, acquirers, issuers, and service providers.
Amazon ECR is a fully-managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images. Amazon ECR is integrated with Amazon Elastic Container Service (ECS), simplifying your development to production workflow. Amazon ECR eliminates the need to operate your own container repositories or worry about scaling the underlying infrastructure. Amazon ECR hosts your images in a secure, highly available, and scalable architecture allowing you to reliably deploy containers for your applications. For more information, visit the Amazon ECR product page.
Visit the AWS global region table for a full list of AWS Regions where Amazon ECR is available.
To learn more about PCI DSS certification, visit the PCI DSS Compliance site
.
Publish Logs from Amazon RDS for Oracle to Amazon CloudWatch Logs
You can now publish logs from your Amazon RDS for Oracle databases to Amazon CloudWatch Logs. Supported logs include alert log, trace log, audit log, and listener log.
Amazon SageMaker Now Supports Resource Tags for More Efficient Access Control
Amazon SageMaker now supports resource tags for more efficient access control. Tags can be attached to resources such as notebook instances, training jobs, models, endpoint configurations, and endpoints within SageMaker.
The AWS Systems Manager Agent is Now Pre-Installed on Ubuntu 16.04 LTS and 18.04 LTS AMIs
The AWS Systems Manager Agent is now installed by default on Ubuntu 16.04 LTS, in the 2018.07 version and later, and in all 18.04 LTS AMIs.
Amazon EKS AMI Build Scripts Available on GitHub
Build scripts for the optimized Amazon Machine Image (AMI) for Amazon Elastic Container Service for Kubernetes (Amazon EKS) worker nodes are now available on GitHub.com.
Amazon EC2 F1 Instances Adds New Features and Performance Improvements
Since we made Amazon EC2 F1 instances generally available last year, we have seen exciting adoption by customers, partners and the developer and research community. Customers are using F1 for accelerating a diverse set of applications such as genomic processing, data analytics, security, image and video processing and machine learning.
Today we are announcing new features and updated capabilities that allow developers to create more performant and feature-rich hardware accelerators using Amazon EC2 F1 instances.
For software developers looking to harness the power of FPGAs and build custom hardware accelerations, we have upgraded the Amazon FPGA software defined development flow with a new FPGA Developer AMI version . The new development tools now support up to 60 kernels (compared to 16 in previous versions) enabling more compute for C /C++ based accelerators.
In addition, based on customer feedback, the direct memory access (DMA) performance has been improved by 5x, allowing the FPGA acceleration engine to stream data to/from the CPU at high speed and increase application performance.
To help offload the non-differentiated tasks of building an FPGA application such as transferring data to/from the host CPU and accessing onboard DRAM from the FPGA, we provide an Amazon FPGA Shell that provides pre-configured, pre-tested, and secure I/O components. With this release we are making the new Amazon FPGA v1.4 Shell reconfigurable, allowing developers to have future-proof designs. Simply put, this means that developers can decide if they’d like to upgrade Shell versions as they become available, compared to previous Shells that were mandatory upgrades. We also added a new capability that allows developers to retain data in the FPGA attached DRAM while swapping Amazon FPGA Images (AFIs) at runtime, which effectively decreases load times of certain AFIs, as there is no need to move data to/from the host into the FPGA DRAM when a new AFI is loaded.
Developers can also take advantage of the growing marketplace of F1 instances based offerings from AWS Partners and other developers, ranging from video encoding to data analytics. All of these new features and upgrades are available for F1 instances in 4 AWS regions – US East (N. Virginia), US West (Oregon), EU (Ireland) and AWS GovCloud (US) regions.
For a complete list of new feature and upgrades, please click here .
AWS Glue now supports reading from Amazon DynamoDB tables
You can now crawl your Amazon DynamoDB tables, extract associated metadata, and add it to the AWS Glue Data Catalog. You can also create Glue ETL jobs to read, transform, and load data from DynamoDB tables into services such as Amazon S3 and Amazon Redshift for downstream analytics. To learn more, please visit our documentation .