CTT Big4 News AWS Recently #AWS022

CTT Big4 News AWS Recently #AWS022

Hello Friends, welcome to Big4 Recently

AWS, IBM, Google & Azure – the Big4 Cloud Service providers. In this article, we will explore latest AWS Recently.

Announcing the New Amazon DynamoDB Key Diagnostics Library

Today, AWS released the Amazon DynamoDB key diagnostics library, which provides near-real-time key usage information for DynamoDB. This library is a lightweight, client-side utility that can help you to analyze your table’s traffic and display visualizations that show the number of reads and writes to each partition key. By using the library, you can adjust to unpredictable and uneven workloads in near-real time. 

New in AWS Deep Learning AMIs: PyTorch 1.0, MXNet 1.3.1, Chainer 5.1, and CUDA 10

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with newer versions of the following deep learning frameworks: PyTorch 1.0, MXNet 1.3.1, and Chainer 5.1. This release also includes upgrades of the NVIDIA stack, including CUDA 10, cuDNN 7.4.1, and NCCL 2.3.7. For GPU-based training, PyTorch 1.0 in the AMIs is fully configured to take advantage of performance improvements in CUDA 10.

AWS Deep Learning AMIs also support other popular frameworks and interfaces including TensorFlow, Keras, Gluon, and Microsoft Cognitive Toolkit (CNTK) — pre-installed and fully-configured for you to start developing your deep learning models in minutes while taking full advantage of the computational power of Amazon EC2 instances. When you activate a Conda environment, the Deep Learning AMIs automatically deploy higher-performance builds of frameworks, optimized for the EC2 instance of your choice. For a complete list of frameworks and versions supported by the AWS Deep Learning AMI, see the release notes.

AWS Step Functions Now Available in EU (Paris) , South America (Sao Paulo) 

AWS Step Functions is now available in the Paris & Sao Paulo region. AWS Step Functions is a workflow automation service that allows you to build and update applications quickly.

Using Step Functions, you can create application workflows that connect and coordinate multiple AWS services. For example, your workflow can invoke AWS Lambda functions, submit AWS Batch jobs and wait for them to complete, run AWS Fargate tasks, start AWS Glue jobs, create Amazon SageMaker jobs, and more. Step Functions workflows can also run any application that can make an HTTPS connection, regardless of where it is hosted.

AWS Step Functions automatically triggers and tracks each step, and retries when there are errors, so your application executes in order and as expected. It includes built-in error handling, parameter passing, least privilege security settings, and state management, significantly reducing the amount of code you have to write and maintain.

AWS Systems Manager Automation Now Supports at Scale Action

AWS Systems Manager now enables customers to use Automation at scale using a pay-per-use model. The existing limit of 25,000 basic steps will be increased to a new free tier of 100,000 basic steps per account per month.

Previously, there was a service limit of 25,000 steps in account executions per month. Now, this limit is removed so you can scale the number of actions. Pricing for steps beyond the free tier is $0.002 per basic step. A basic step is an action performed in the Automation workflow execution in the local account and Region. Multi-account and multi-Region actions are considered special steps and are priced separately. See the Pricing page for details.

Systems Manager Automation is a platform with curated runbooks for AWS resource management. You can perform common IT tasks such as creating backups and starting/stopping Amazon EC2 and Amazon RDS instances at scale with velocity controls. You can also implement complex tasks such as Amazon Machine Image (AMI) building, EC2 rescue, and patching Auto Scaling groups. Systems Manager is available in all commercial Regions and GovCloud (US).

Deploy TIBCO Data Science on AWS with New Quick Start

This Quick Start automatically deploys TIBCO Data Science on the Amazon Web Services (AWS) Cloud in about 80 minutes. This deployment guide is for infrastructure architects and TIBCO administrators who want to quickly deploy a TIBCO Data Science system in a fault-tolerant configuration across AWS Availability Zones.

TIBCO Data Science is a big data analytics platform for enterprises that provides an array of tools (from visual workflows to Jupyter Python Notebooks) and connects natively to most data sources, including Apache Hadoop, Spark, Hive, and relational databases.

The collaborative user interface enables data scientists, data engineers, and business users to work together and build machine learning workflows in an intuitive web interface with a minimum of code. The advanced analytics platform provides security and governance. It also enables the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization.

That’s it friends in this week for AWS Recently, however please visit specific Cloud provider news that you are interested in from below links.

Author: Debashree

A Technical writer and passionate about digital life. Always eager to learn and share knowledge.

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