Amazon Forecast – Now Generally Available

Getting accurate time series forecasts from historical data is not an easy task. Last year at re:Invent we introduced Amazon Forecast, a fully managed service that requires no experience in machine learning to deliver highly accurate forecasts. I’m excited to share that Amazon Forecast is generally available today!
With Amazon Forecast, there are no servers to provision. You only need to provide historical data, plus any additional metadata that you think may have an impact on your forecasts. For example, the demand for a particular product you need or produce may change with the weather, the time of the year, and the location where the product is used.
Amazon Forecast is based on the same technology used at Amazon and packages our years of experience in building and operating scalable, highly accurate forecasting technology in a way that is easy to use, and can be used for lots of different use cases, such as


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Amazon Polly Introduces Neural Text-To-Speech and Newscaster Style

From Robbie the Robot to Jarvis, science fiction writers have long understood how important it was for an artificial being to sound as lifelike as possible. Speech is central to human interaction, and beyond words, it helps us express feelings and emotions: who can forget HAL 9000’s haunting final scene in 2001: A Space Odyssey?
In the real world, things are more complicated of course. Decades before the term ‘artificial intelligence’ had even been coined, scientists were designing systems that tried to mimic the human voice. In 1937, almost 20 years before the seminal Dartmouth workshop, Homer Dudley invented the Voder, the first attempt to synthesize human speech with electronic components: this video has sound samples and extra information on this incredible device.
We’ve come a long way since then! At AWS re:Invent 2016, we announced Polly, a managed service that turns text into lifelike speech, allowing customers to create


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OpsCenter – A New Feature to Streamline IT Operations

The AWS teams are always listening to customers and trying to understand how they can improve services to make customers more productive. A new feature in AWS Systems Manager called OpsCenter exemplifies this approach by enabling customers to aggregate issues, events and alerts, across services. So customers can go to one place to view, investigate, and remediate issues reducing the need to navigate across multiple different AWS services.
Issues, events and alerts appear as operations items (OpsItems) in this new console and provide contextual information, historical guidance, and quick solution steps. The feature aims to improve the mean time to resolution, making engineers more productive by ensuring key investigation data is available in one place.
Engineers working on an OpsItem get access to information such as:
Event, resource and account details
Past OpsItems with similar characteristics
Related AWS Config changes and relationships
AWS CloudTrail logs
Amazon CloudWatch


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EC2 Instance Update – Two More Sizes of M5 & R5 Instances

When I introduced the Nitro system last year I said:

The Nitro system is a rich collection of building blocks that can be assembled in many different ways, giving us the flexibility to design and rapidly deliver EC2 instance types with an ever-broadening selection of compute, storage, memory, and networking options. We will deliver new instance types more quickly than ever in the months to come, with the goal of helping you to build, migrate, and run even more types of workloads.

Today I am happy to make good on that promise, with the introduction of two additional sizes of the Intel and AMD-powered M5 and R5 instances, including optional NVMe storage. These additional sizes will make it easier for you to find an instance size that is a perfect match for your workload.
M5 Instances These instances are designed for general-purpose workloads such as web servers, app servers,


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New – UDP Load Balancing for Network Load Balancer

The Network Load Balancer is designed to handle tens of millions of requests per second while maintaining high throughput at ultra low latency, with no effort on your part (read my post, New Network Load Balancer – Effortless Scaling to Millions of Requests per Second to learn more).
In response to customer requests, we have added several new features since the late-2017 launch, including cross-zone load balancing, support for resource-based and tag-based permissions, support for use across an AWS managed VPN tunnel, the ability to create a Network Load Balancer using the AWS Elastic Beanstalk Console, support for Inter-Region VPC Peering, and TLS Termination.
UDP Load Balancing Today we are adding support for another frequent customer request, the ability to load balance UDP traffic. You can now use Network Load Balancers to deploy connectionless services for online gaming, IoT, streaming, media transfer, and native UDP applications. If you are hosting


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Amazon Managed Streaming for Apache Kafka (MSK) – Now Generally Available

I am always amazed at how our customers are using streaming data. For example, Thomson Reuters, one of the world’s most trusted news organizations for businesses and professionals, built a solution to capture, analyze, and visualize analytics data to help product teams continuously improve the user experience. Supercell, the social game company providing games such as Hay Day, Clash of Clans, and Boom Beach, is delivering in-game data in real-time, handling 45 billion events per day.
Since we launched Amazon Kinesis at re:Invent 2013, we have continually expanded the ways in in which customers work with streaming data on AWS. Some of the available tools are:
Kinesis Data Streams, to capture, store, and process data streams with your own applications.
Kinesis Data Firehose, to transform and collect data into destinations such as Amazon S3, Amazon Elasticsearch Service, and Amazon Redshift.
Kinesis Data Analytics, to continuously analyze data using SQL or Java (via Apache


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New – Amazon S3 Batch Operations

AWS customers routinely store millions or billions of objects in individual Amazon Simple Storage Service (S3) buckets, taking advantage of S3’s scale, durability, low cost, security, and storage options. These customers store images, videos, log files, backups, and other mission-critical data, and use S3 as a crucial part of their data storage strategy.
Batch Operations Today, I would like to tell you about Amazon S3 Batch Operations. You can use this new feature to easily process hundreds, millions, or billions of S3 objects in a simple and straightforward fashion. You can copy objects to another bucket, set tags or access control lists (ACLs), initiate a restore from Glacier, or invoke an AWS Lambda function on each one.
This feature builds on S3’s existing support for inventory reports (read my S3 Storage Management Update post to learn more), and can use the reports or CSV files to drive your batch operations.


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In the Works – EC2 Instances (G4) with NVIDIA T4 GPUs

I’ve written about the power and value of GPUs in the past, and I have written posts to launch many generations of GPU-equipped EC2 instances including the CG1, G2, G3, P2, P3, and P3dn instance types.
Today I would like to give you a sneak peek at our newest GPU-equipped instance, the G4. Designed for machine learning training & inferencing, video transcoding, and other demanding applications, G4 instances will be available in multiple sizes and also in bare metal form. We are still fine-tuning the specs, but you can look forward to:
AWS-custom Intel CPUs (4 to 96 vCPUs)
1 to 8 NVIDIA T4 Tensor Core GPUs
Up to 384 GiB of memory
Up to 1.8 TB of fast, local NVMe storage
Up to 100 Gbps networking
The brand-new NVIDIA T4 GPUs feature 320 Turing Tensor cores, 2,560 CUDA cores, and 16 GB of memory. In


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Now Available – Five New Amazon EC2 Bare Metal Instances: M5, M5d, R5, R5d, and z1d

Today we are launching the five new EC2 bare metal instances that I promised you a few months ago. Your operating system runs on the underlying hardware and has direct access to the processor and other hardware. The instances are powered by AWS-custom Intel® Xeon® Scalable Processor (Skylake) processors that deliver sustained all-core Turbo performance.
Here are the specs:
Instance Name
Sustained All-Core Turbo
Logical Processors
Memory
Local Storage
EBS-Optimized Bandwidth
Network Bandwidth
m5.metal
Up to 3.1 GHz
96
384 GiB

14 Gbps
25 Gbps
m5d.metal
Up to 3.1 GHz
96
384 GiB
4 x 900 GB NVMe SSD
14 Gbps
25 Gbps
r5.metal
Up to 3.1 GHz
96
768 GiB

14 Gbps
25 Gbps
r5d.metal
Up to 3.1


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