AWS Graviton Weekly # 16: Week from December 16th, 2022 to December 23th, 2022

Marcos Ortiz
11 min readDec 27, 2022


AWS Graviton Weekly # 16

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Issue # 16: December 16th, 2022 to December 23rd, 2022

Hey friend.

Welcome to Issue # 16 of AWS Graviton Weekly, which will be focused on sharing everything that happened in the past week related to AWS Silicon: from December 16th, 2022, to December 23rd, 2022.

Enjoy this week’s content.


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Amazon OpenSearch Service now supports Amazon Graviton2 (M6g, C6g, R6g, and R6gd) instances in four additional regions

We are excited to announce support for the Amazon Graviton2 instance family in four additional regions. Supported instance types include general purpose (M6g), compute-optimized (C6g), and memory-optimized (R6g and R6GD) instances. Support for C6g, M6g, R6g, and R6gd is available in the Europe (Paris) region. In addition, the Asia Pacific (Mumbai), South America (Sao Paulo), and Canada (Central) regions already supported C6g, M6g and R6g instance families, and we have now added support for R6gd in these regions.

Amazon OpenSearch Service Graviton2 instances support OpenSearch versions and Elasticsearch versions 7.9 and above. With Amazon OpenSearch Service, Graviton-based instances provide up to 30% better price-performance than comparable x86-based Amazon Elastic Compute Cloud instances. Further savings are available through reserved instance (RI) pricing for these instances.

Amazon’s new chip moves AWS into high-performance computing:

The newest chip is the latest piece of Amazon’s effort to build more of the hardware that fills the massive data centers that power AWS. Amazon says making its own chips will give customers more cost-effective computing power than they could get by renting time on processors built by the likes of Intel, Nvidia, or Advanced Micro Devices.

The move has put AWS in direct competition with those companies, which are also among its biggest suppliers. DeSantis said the chipmakers remain “great partners,” and that AWS plans to continue to offer high-performance computing services based on chips made by other companies.

AWS wins 5-year, $700m+ contract for cloud services to US Navy, by The Register:

Amazon Web Services has secured a five-year contract with the US Navy for cloud services, just weeks after scoring its share of a major US Department of Defense deal for cloud computing.

The cloud division of online marketplace Amazon has been awarded a contract worth $723.9 million by the Department of the Navy as a single-award fixed-price enterprise software license blanket purchase agreement. The details were disclosed in a contract notice posted on the Department of Defense website.

Articles and Tutorials

Tech predictions for 2023 and beyond, by Werner Vogels, CTO at Amazon:

Prediction 5: Custom silicon goes mainstream

Take machine learning workloads for example. Software engineers have traditionally relied on expensive, power-hungry GPUs to do everything from model building to inference.

However, this one-size-fits-all approach is not efficient — most GPUs aren’t optimized for these tasks. In the coming years, more engineers will see the benefits of moving workloads to processors specifically designed for things like model training (AWS Trainium) and inference (AWS Inferentia). As this happens, a new wave of innovation will begin. By realizing a 50% cost-to-train savings with a Trainium-based instance, or 50% better performance-per-watt on an Inferentia2-based instance, engineers and businesses alike will take notice, and we will begin to see a massive migration of workloads. The same will be true even for generalized applications, where there are still benefits to moving to custom silicon, such as Graviton3-based instances that use up to 60% less energy for the same performance than comparable EC2 instances.

Unlock the power of EC2 Graviton with GitLab CI/CD and EKS Runners, by Michael Fischer (Principal Specialist Solutions Architect at Amazon Web Services):

In this post, we’ve illustrated how you can quickly and easily construct multi-architecture container images with GitLab, Amazon EKS, Karpenter, and Amazon EC2, using both x86 and Graviton instance families. We indexed on using as many managed services as possible, maximizing security, and minimizing complexity and TCO. We dove deep on multiple facets of the process, and discussed how to save up to 90% of the solution’s cost by using Spot instances for CI/CD executions.

Say Hello to 120 New AWS Competency, Service Delivery, Service Ready, and MSP Partners Added in November

Optimize AWS costs without architectural changes or engineering overhead, by Ryan Doty (Solutions Architect at AWS)

These modifications can help you optimize your AWS costs without having to introduce any application re-architecture, system re-architecture, or engineering overhead.

To ensure cost proper prioritization, here are the proposed changes in order of required effort:

- Upgrading Amazon EBS Volumes from GP2 to GP3

- Swapping Amazon RDS/Amazon Aurora underlying compute to Graviton-based instances or latest generation instances depending on your DB engine

- Migrating existing Linux-based workloads to run on Graviton 64-Bit Arm-based Amazon EC2 instances.

Driving Price Performance Benefits with AWS Graviton, by Tim Lockyear (SVP Platforms, NA at AllCloud)

AWS Graviton processors are custom-built to deliver the best price-performance for an organization’s cloud workloads. While providing significant price performance benefits, AWS Graviton processors help customers reinvent their businesses by innovating quickly and gaining better performance for a variety of workloads.

CircleCI(Arm Executor) + AWS Graviton2 on Fargate Demo, by Tadashi Nemoto (Solutions Engineer at CircleCI):

Improve efficiency of microservices with AWS Graviton, by Mongkol Thongkraikaew (Head of Platform Engineering at Ascend Money):

When and How to Use AWS Graviton, by Michael Langford (Product Marketing Manager at Trend Micro)

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.

Boost your ML Workload Performance with Migration to Graviton-Powered Instances, by Artem Kobrin (Solutions Architect at NTT Data)

In a quest for lower energy consumption and higher performance in CPU-based machine learning workloads, Graviton3 is AWS’s next-generation ARM-compatible server processor range.

However, is the hype with Graviton3 processors and their core differential benefits really worth it? This article will help find the answers.

On Amazon EKS and Cost Optimisation, by Dirk Michel (SVP — SaaS and Digital Technology at MYCOM OSI)

Transitioning an application to support Graviton depends on the bytecode-compiled language and can involve many steps. But the motivation to move towards Graviton support can be quite strong when optimising for cost.

Depending on the state of the containerised application, adopting Graviton may be as simple as replacing x86-based instances with Graviton instances.

Run Arm workloads in Anthos clusters on AWS, by Google Cloud

Anthos clusters on AWS lets you run Arm workloads built for Arm-based AWS Graviton processors

Slides, Videos and Audio

[VIDEO] [AWS FEST] re:Invent recap — AWS Cost Optimization, by Jon Myer (Chief Content Officer from Myer Media) and Cristian Măgherușan-Stanciu (founder of LeanerCloud, the company behind AutoSpotting)

In this interesting conversation, you will learn:

1️⃣ A feature that allows you to configure instances in order of lowest cost more easily

2️⃣ The new AWS Graviton instance types and how they compare

3️⃣ What is the new release from Amazon RDS (and how does it help)?

4️⃣ Community expectations and feedback from AWS re:Invent 2022

Cristian explains the differences between Graviton3 and Graviton3E. Highly recommended !!!​

[VIDEO] Graviton CPU Variant for HPC | Gestalt IT Rundown: November 30, 2022, by Tom Hollingsworth and Stephen Foskett from Gestalt IT

Graviton 3E is finally here.

What does that mean? It’s a CPU that is designed to accelerate floating point and vector math. That may not sound exciting to you but for high-performance computing environments, that’s exactly what the doctor ordered.​

This custom unit is going to be aimed at giants that are looking to eake out the last drop of performance from those life sciences models. At the same time, Amazon introduced the Nitro version 5, the latest in their groundbreaking DPU family.

[VIDEO] AWS re:Invent 2022 — HPC on AWS: Solve complex problems with pay-as-you-go infrastructure, Ian Colle (General Manager, HPC at AWS) and Dr. Chen Su (Senior Director, Enterprise High-Performance Computing at Eli Lilly and Company).

At that exact moment, Ian explained the incredible features behind the HPC7g, the new Amazon EC2 instances, focused on High-Performance Computing, based on the new Graviton3E processor.

[VIDEO] AWS re:Invent 2022 — Run high-perf storage workloads on EC2 storage optimized instances, by Amit Shah (Principal Product Manager at AWS) and Shruti Gupta (Senior Product Manager at AWS)

Are you looking for Amazon EC2 instances to deploy low-latency workloads that also require high-performance storage capacity (for example, MySQL, MongoDB, Hadoop, ElasticSearch, or Apache Kafka)?

This session dives deep into the different Amazon EC2 storage-optimized instance offerings, including a discussion of SSD performance, AWS Nitro SSD advantages, price performance, and ways to optimize your clusters using Amazon EC2 storage-optimized instances with Intel and AWS Graviton. Learn when to pick Amazon EC2 storage-optimized instance offerings and/or Amazon EBS to run your high-performance storage workloads, based on your workload requirements.

[VIDEO] AWS re:Invent 2022 — Optimizing Amazon EKS for performance and cost on AWS, by Alex Kestner (Sr. Product Manager at AWS) and Raghav Tripathi (Engineering Manager, Kubernetes Compute & Networking at Amazon Web Services at AWS)

Want to minimize costs on Amazon EKS without affecting the performance of your applications? Then this session is for you. Learn how to manage an efficient infrastructure on Kubernetes and optimize costs on AWS using Amazon EC2 Spot Instances, AWS Graviton, and Auto Scaling policies. EC2 Spot Instances allow you to run your applications in containers, obtaining an average savings of 65 percent on infrastructure without impact on your application.

Graviton-based processors are designed by AWS to deliver up to 40 percent better price performance over comparable x86-based instances. Finally, hear about other techniques and methods to further optimize Amazon EKS node groups.

[VIDEO] AWS re:Invent 2022 — Kubernetes virtually anywhere, for everyone

In this exact moment of the keynote by Barry Cooks (VP of Kubernetes at AWS), you can see a demo provided by Sheetal Joshi (Senior Developer Advocate at AWS) where she explains how Karpenter first bin packs, then shifts to Graviton and then uses spot to bring cost down by 70% all while respecting pod disruption budgets!

[PODCAST] How Arm Neoverse is Redefining the Global Computing Infrastructure: Part I, and Part II with Dermot O’Driscoll (Vice President Product Solutions at Arm) and Geof Wheelwright (host of the ARM podcast)

Rising energy prices and worries about the infrastructure’s contributions to climate change mean the traditional approach to delivering more performance in the data center is proving too costly and energy-inefficient.

Arm and its partners are delivering an increasingly popular alternative to the old-school approach: World-leading silicon that achieves unparalleled performance efficiency along with an ecosystem of innovation that makes solutions more available to OEMs, software developers, and end users than ever. In the first of a two-part series, Dermot O’Driscoll, VP of Arm’s Infrastructure Line of Business, sits down with host Geof Wheelwright to discuss how Arm technology is helping overcome these challenges.

In the second of a two-part series, Dermot O’Driscoll, VP of Arm’s Infrastructure Line of Business, chats with host Geof Wheelwright to change design requirements in the data center and infrastructure.


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Quote of the week

With Graviton, we saw that the industry is moving in a direction of utilizing ARM chipsets and we understood that for a long-term investment in terms of savings, we need to be able to support that.

We didn’t necessarily move our entire platform, in fact we use a mix of both ARM and AMD Spot Instances, we just understood that we didn’t we wanted the option to use ARM when available.

We first moved our MySQL databases on RDS to Graviton without any kind of impact that we could perceive and so the next step was to move our applications to Graviton.

There was really no change needed in our application it was just a matter of getting the Docker containers to be able to run on either type of node .

Uh, it’s slightly less expensive in the Spot Instances type, of course spot instances price fluctuate so you keep an eye on that but it gave us about a couple of percentage points like 5 to 10 percent of savings on the Spot instances.

Noah Zucker, Head of Platform at SEI Novus. Source: Caylent