Amazon EC2 R6g Instances
Best price performance for memory-intensive workloads in Amazon EC2
Amazon EC2 R6g instances are powered by Arm-based AWS Graviton2 processors. They deliver up to 40% better price performance over current generation R5 instances1 and are ideal for running memory-intensive workloads such as open-source databases, in-memory caches, and real time big data analytics. Developers can also use these instances to build Arm-based applications natively in the cloud, eliminating the need for cross-compilation and emulation, and improving time to market.
R6g instances will also be available with local NVMe-based SSD block-level storage option (R6gd) for applications that need high-speed, low latency local storage.
Best price performance for memory-intensive workloads
With R6g instances, customers can optimize for both higher performance and lower cost per GiB. R6g instances deliver up to 40% better price performance over current generation R5 instances1 for a large number of applications built on open-source software utilizing Linux distributions.
Flexibility and choice
R6g instances add to the broadest and deepest selection of EC2 instances and enable customers to run a broad set of memory-intensive workloads such as open-source databases, in-memory caches, and real time big data analytics. Developers can also build Arm applications natively in the cloud while leveraging the flexibility, security, reliability, and scalability of running on EC2.
Enhanced security and maximized resource efficiency
R6g instances are powered by AWS Graviton2 processors and built on the AWS Nitro System. AWS Graviton2 processors feature always-on 256-bit DRAM encryption and 50% faster per core encryption performance compared to first-generation AWS Graviton. The AWS Nitro System is a combination of dedicated hardware and lightweight hypervisor which delivers practically all of the compute and memory resources of the host hardware to your instances for better overall performance and security. R6g instances also support encrypted EBS storage volumes by default.
Extensive ecosystem support
AWS Graviton2-based EC2 instances are supported by popular Linux operating systems including Amazon Linux 2, Red Hat, SUSE, and Ubuntu. Many popular applications and services from AWS and Independent Software Vendors also support AWS Graviton2-based instances, including Amazon ECS, Amazon EKS, Amazon ECR, Amazon CodeBuild, Amazon CodeCommit, Amazon CodePipeline, Amazon CodeDeploy, Amazon CloudWatch, Crowdstrike, Datadog, Docker, Drone, GitLab, Jenkins, NGINX, Qualys, Rancher, Rapid7, Tenable, and TravisCI.
Powered by AWS Graviton2 processors
AWS Graviton2 Processors are based on 64-bit Arm Neoverse cores and custom silicon designed by AWS for optimized performance and cost. AWS Graviton2 Processors deliver 7x more performance, 4x more compute cores, 5x faster memory, and 2x larger caches versus first-generation AWS Graviton Processors.
High performance networking and storage
Next generation Elastic Network Adapter (ENA) and NVM Express (NVMe) technology provide R6g instances with high throughput, low latency interfaces for networking and Amazon Elastic Block Store (Amazon EBS). R6g instances will also soon be available with local instance storage option (R6gd).
Built on AWS Nitro System
The AWS Nitro System is a rich collection of building blocks that offloads many of the traditional virtualization functions to dedicated hardware and software to deliver high performance, high availability, and high security while also reducing virtualization overhead.
|Instance Size||vCPU||Memory (GiB)||Instance Storage||Network Bandwidth (Gbps)||EBS Bandwidth (Mbps)|
|r6g.medium||1||8||EBS-Only||Up to 10||Up to 4,750|
|r6g.large||2||16||EBS-Only||Up to 10||Up to 4,750|
|r6g.xlarge||4||32||EBS-Only||Up to 10||Up to 4,750|
|r6g.2xlarge||8||64||EBS-Only||Up to 10||Up to 4,750|
|r6g.4xlarge||16||128||EBS-Only||Up to 10||4,750|
Blog Posts & Articles
Mar 10, 2020
Jan 14, 2020
Dec 3, 2019
1 20% lower cost and up to 40% higher performance over Amazon EC2 R5 instances, based on internal testing of workloads with varying characteristics of compute and memory requirements