Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), and NVIDIA (NASDAQ: NVDA) today announced a multi-part collaboration focused on building out the world's most scalable, on-demand artificial intelligence (AI) infrastructure optimized for training increasingly complex large language models (LLMs) and developing generative AI applications.
The joint work features next-generation Amazon Elastic Compute Cloud (Amazon EC2) P5 instances powered by NVIDIA H100 Tensor Core GPUs and AWS’s state-of-the-art networking and scalability that will deliver up to 20 exaFLOPS of compute performance for building and training the largest deep learning models. P5 instances will be the first GPU-based instance to take advantage of AWS’s second-generation Elastic Fabric Adapter (EFA) networking, which provides 3,200 Gbps of low-latency, high bandwidth networking throughput, enabling customers to scale up to 20,000 H100 GPUs in EC2 UltraClusters for on-demand access to supercomputer-class performance for AI.
We are excited to announce the support for Graviton3-based instances in Amazon EMR. You can now use Amazon EC2 C7g instances with EMR on EC2 and Amazon EKS. AWS Graviton3 processors are the latest in the AWS Graviton processor family.
They provide better compute performance, floating point performance and support DDR5 memory that provides 50% more memory bandwidth as compared to DDR4. Amazon EMR launches support for Amazon Elastic Cloud Compute C7g (Graviton3) instances which improve cost-performance for Apache Spark workloads by up to 13%.
In this post, they described how they estimated the cost-performance benefit from using Amazon EMR with C7g instances compared to using equivalent previous generation instances. Using these new instances with Amazon EMR improves cost-performance by an additional 7–13%.
SentinelOne is pleased to announce support for Amazon Linux 2023 (AL2023) with the latest agent 23.1, and achievement of the Amazon Linux 2023 Service Ready Designation. Amazon Linux 2023 Ready solutions are vetted by AWS Partner Solution Architects to ensure a consistent customer experience.
All modern ASIC-based network devices have separation between data-plane (hardware) and control-plane (software). But often the control-plane functions are on embedded CPUs with limited compute and RAM.
In contrast to popular commercial offerings, we have paired our own device with a Graviton2 based onboard controller for the base-features that a peering-router needs. We build our own devices in a hybrid, with some functions that make sense on the device (such as link-aggregation, route programming) but with BGP signaling separate from the physical device (Figure 9).
The Internet operates using the BGP routing protocol, and where we have millions of prefixes and paths to choose from, we centralize routing decisions to much higher performance compute outside of the network devices. Although we run this infrastructure ‘disaggregated’, this is transparent to our internet peers; they don’t need to do anything different to peer with us, even though their seemingly ‘direct’ BGP-sessions actually terminate logically in a high-performance compute cluster locally at the site.
Operating disaggregated in this manner also means that we can scale-out internet connectivity very wide, and we have many places where we’re doing multi-Tbps on a single internet peering session.
Discover how AWS Graviton’s optimized processors help provide a superior price-performance ratio. Available for AWS-managed services, you’ll gain insight on strategies, use cases, and insight on how to get the most out of AWS Graviton.
Up to a few years back, writing Dockerfiles was easy. In many cases, it still is - unless you are working with a mixed fleet of Intel and ARM-based processors. Are you familiar with this situation and you do not want to maintain two almost identical Dockerfiles? There is a solution
GitHub does not support any ARM GitHub Actions Runner. So what now? Build it within your AWS environment!The results are pretty cool: You have full control over the Runners and have no more time constraints like long-running workflows that consume Runners usage minutes.I will guide you through the basics of creating an AWS EC2 instance and installing the minimum requirements on the OS for having a running GitHub Actions Runner.
In this post, we share how the finance and engineering teams at Coupang have partnered together over the past few quarters to provide a roadmap to manage and optimize cloud expenditure. We will also detail how multiple engineering teams formed a Central team to further optimize the cloud spending for on-demand cost.
In this episode, Emily and Dave chat with Jason Yee, Staff Technical Evangelist at Datadog. Datadog is an essential monitoring and security platform for cloud applications offering end traces, metrics, and logs to help make your applications, infrastructure, and third-party services entirely observable. Jason covers how developers can best think of observability, the helpful tenants of LIFT (latency, errors, traffic, and saturation), and how to get started today. Jason also gives an overview of Graviton processors, an analysis of cost and performance, and how Datadog has been able to generate massive cost savings through a service migration to ARM.
AWS Graviton processors are designed to provide the best performance per watt of energy use in Amazon EC2. To help customers reduce their carbon footprint, AWS Graviton processors are more energy efficient. Graviton-based instances use up to 60% less energy for the same workload performance than comparable non-Graviton based Amazon EC2 instances. In this session, you will learn how AWS designed Graviton-based instances for energy efficiency.
Java is one of the most popular languages when running applications on AWS. Aren you aware that AWS offers a no-cost, multiplatform, production-ready distribution of the Open Java Development Kit? Did you know that the kit runs on Graviton-based Amazon EC2 instances? During this session, the speaker will explain what Amazon Corretto, AWS version of a Java Development Kit, is and how to install it on Graviton-based Amazon EC2 instances.
In this session, Arthur gave a bit of background on Amazon Elastic Cloud Compute (EC2) and how the AWS Nitro System has been designed. Then, he proceeded to show how to launch a Graviton-based Amazon EC2 instance.
Most of the workloads running on Linux use a variety of Open-Source software. Sometimes they're installed from the package management system, and at other times they're from language or framework specific package management systems. Understanding whether a specific version is available for the AWS Graviton processors can be a challenge. In this session, the speaker will explain how to find your way among Open-Source software and find out which software version(s) to use.
AWS Graviton processors may be the first arm64-based processors you are using on a server. You might be wondering which operating system you should be using. In this session, the speaker will explain which OS support AWS Graviton processors and the various alternatives. The speaker will then show you how to launch a Graviton-based Amazon EC2 instance.
AWS Container Services, including Amazon Elastic Kubernetes Service (EKS), Amazon Elastic Container Service (ECS), and AWS Fargate, streamline the deployment and management of software applications on AWS. This leads to a significant reduction in operational workload during the development, testing, and large-scale deployment of enterprise software products. Additionally, these services fully support the use of AWS Graviton-based EC2 instances, which enables customers to benefit from the cost savings associated with Graviton instances. Graviton offers the best price performance of all EC2 instances, so you can accelerate growth while you improve operating margins. Join us to learn how customers have realized price-performance improvements by switching to AWS Graviton for their container workloads. We will share best-practices and considerations when moving workloads to AWS Graviton
Wednesday, April 12, 2023 at 5:30 PM to Wednesday, April 12, 2023 at 7:00 PM EDT
In this presentation, Lane Jennison, Distinguished Cloud / DevOps Engineer at Ippon Technologies USA, will demystify ARM computing in the cloud and focus on the opportunities available with AWS Graviton!
The session will provide executive-level and engineering-level explanations on how ARM has evolved to a server-class architecture, how the cost benefits are tangible, the performance parity graviton provides, and the practical paths your organization can refactor workloads to take advantage of this next era of cloud computing.
This talk is ideal for cloud architects, developers, and IT professionals who want to learn more about AWS Graviton and how it can help them optimize their cloud workloads.
RAI Amsterdam, Europaplein 24 1078 GZ Amsterdam Nederland
April 18th - April 21st, 2023, 9am - 6pm CEST
Future proof your Kubernetes cluster for cost optimization
Cost optimization is a common priority. In this session, learn about the many factors that can increase costs in your Kubernetes usage beyond compute, such as compute efficiencies at the node and pod level, scaling parameters, networking cost, multi-architecture image creation, security posture, and more. Discover how to change your application components and migrate from x86-based instances to AWS Graviton to achieve cost efficiency at higher performance. Also, learn how to use open-source tools and AWS services to optimize these costs and make your Kubernetes cluster more resilient to economic instability.