Starting today, Amazon Elastic Compute Cloud C7g instances are available in AWS Region Europe (Frankfurt), AWS Region Asia Pacific (Sydney) and AWS Region Asia Pacific (Tokyo).
C7g instances are powered by AWS Graviton3 processors and built on the AWS Nitro System. AWS Graviton3 processors provide up to 25% better compute performance compared to
AWS Graviton2 processors. The AWS Nitro System is a collection of AWS designed hardware and software innovations that deliver efficient, flexible, and secure cloud services with isolated multi-tenancy, private networking, and fast local storage. C7g instances are built for workloads including batch processing, ad serving, video encoding, gaming, scientific modelling, data analytics, and CPU-based artificial intelligence and machine learning (AI/ML) inference.
Amazon DocumentDB (with MongoDB compatibility) continues to increase compatibility with MongoDB, and now offers added support for MongoDB 5.0 drivers with Amazon DocumentDB 5.0. Amazon DocumentDB is a fast, scalable, highly available, and fully managed document database service that supports MongoDB API based workloads. Amazon DocumentDB makes it easy and intuitive to store, index, and query JSON data.
Amazon DocumentDB 5.0 is available on Graviton instances in all regions where where DocumentDB is available.
Hyperscalers in 2022 provided their customers ARM architecture support (Google Cloud, AWS, and Azure) and there is also a great article written by Percona’s team doing an economical comparison of using different EC2 types in AWS, in the end, we can see how in terms of costs, Graviton (EC2 with ARM support) is a good choice in terms of pricing vs performance for database usage.
Amazon was the first company to bring an Arm-based processor to market, even though it only sold the processors to itself. AWS introduced its in-house designed Arm-based processor, Graviton, in late 2018, and the company has released a new generation of Graviton nearly every year since. AWS Graviton delivers value along three dimensions: cost, energy efficiency, and an architecture ideal for cloud-native applications.
The two companies also will continue “deepening product integrations” between their two technology portfolios in such areas as AI/machine learning, data governance, streaming data and other areas. Snowflake is also running data workloads on AWS Graviton instances.
Cost efficiency with AWS Graviton migration, made seamless and quick. Here’s an interesting EKS -Graviton migration use case from one of our customers, that we empowered with BuildPiper to achieve ~50% cost savings!
In this economic climate, every dollar counts. In this webinar, we will focus on how you can optimize your current AWS footprint with little to no architectural changes. These suggested modifications focus on improving price-to-performance without introducing engineering overhead, large planning cycles, and significant time investment. Many of these changes can save you between 10-20% overnight.
On this episode of The Cloud Pod, the team highlights the new Graviton3-based images for users of AWS, new ways provided by Google to pay for its cloud services, the new partnership between Azure and the Finops Foundation, as well as Oracle's new cloud banking, and the automation of CCOE.
In this session we will use an architectural lens to explore evolving the architecture of your applications, and the options available to you when deploying your .NET applications on AWS. We will focus on .NET containers and serverless services available in the AWS landscape to deploy your applications.
It's often said that “Porting to Arm is boring,” but how easy is it, really? We'll demonstrate top machine learning frameworks, HPC applications, and tools for data science on the NVIDIA Arm HPC DevKit. The DevKit is an on-ramp platform for NVIDIA Grace CPU that incorporates dual NVIDIA A100 GPUs, an NVIDIA BlueField DPU, and an 80-core Ampere Altra Arm CPU, in a standards-compliant Arm server. We'll walk through the complete installation process for key applications and their dependencies including codes like TensorFlow, OpenRADIOSS, WRF, GROMACS, BWA-MEM2, and Jupyter Notebook. We'll also show how codes incorporating x86 AVX and SSE SIMD instructions can be trivially ported to Arm with freely available tools. We'll conclude with a general guide to porting to NVIDIA Grace and links to downloadable resources and tutorials that fully replicate our demonstrations. This session is a strong starting point for anyone targeting NVIDIA Grace Hopper or the NVIDIA Grace CPU Superchips.
[WEBINAR] Optimizing Amazon EKS for Performance and Cost on AWS
This meetup is like a treasure hunt for customers who are eager to discover the magic of Karpenter and level up their EKS skills. So grab your compass and let's set sail on this exciting journey together!
What is Karpenter?
Karpenter simplifies Kubernetes infrastructure with the right nodes at the right time. Karpenter automatically launches just the right compute resources to handle your cluster’s applications. It is designed to let you take full advantage of the cloud with fast and simple compute provisioning for Kubernetes clusters.
Setup EKS with Karpenter aimed at Scale and Operational/Cost Efficiency
Understand value that Karpenter provides as an autoscaler
Understand EC2 Spot/spare-capacity with Karpenter and Graviton