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Marcos Ortiz

AWS Graviton Weekly # 21: Week from January 20th, 2023 to January 27th, 2023

Published about 1 year ago • 6 min read

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Issue # 21: January, 20th, 2023 to January 27th, 2023

Hey Reader

Welcome to Issue # 21 of AWS Graviton Weekly, which will be focused on sharing everything that happened in the past week related to AWS Silicon: from January 20th, 2023 to January 27th, 2023.

This week we saw the amazing announcement of Porting Advisor for Graviton , a CLI tool that could help your company to accelerate dramatically the move to AWS Graviton-based infrastructure.

Fantastic work from Jose Arturo Molina from the AWS team, and of course we have to thank as well to Chris January , Eric Van Hensbergen and Richard Henwood; the incredible engineers from the High-Performance Computing team at Arm who set the foundation for this tool .

If you were waiting for the perfect moment to move to Graviton, this is it.

Read more about this in the News section and more good stuff in the AWS Silicon universe.

Enjoy.


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News

Announcing Porting Advisor for Graviton

AWS announces the general availability of Porting Advisor for Graviton.
The Porting Advisor for Graviton is an open-source command line tool that analyzes source code and generates a report highlighting missing and outdated libraries and code constructs that may require modification along with recommendations for alternatives.
It accelerates your transition to AWS Graviton-based instances by reducing the iterative process of identifying and resolving source code and library dependencies.
The Porting Advisor for Graviton is freely available on the AWS GitHub Repository to be built from source.
This tool scans source code, however, it does not scan binary files. The Porting Advisor for Graviton does not make any code modifications, or API-level recommendations.
Finally, it does not send any data back to AWS.
The tool supports C/C++, Fortran, Go 1.11+, Java 8+, and Python 3+ and can run on x86-based and Arm64-based machines.
To learn more, see the Porting Advisor for Graviton GitHub Repository. To learn how to migrate your workloads to AWS Graviton-based instances, see the AWS Graviton Technical Guide GitHub Repository and AWS Graviton Transition Guide.

Amazon-Stripe partnership accelerates ecommerce and streamlines online payments

Amazon and Stripe sign an expanded global agreement, deepening the two companies’ long-standing partnership.
Under the new agreement, Stripe will become a strategic payments partner for Amazon in the US, Europe, and Canada, processing a significant portion of Amazon’s total payments volume across its businesses, including Prime, Audible, Kindle, Amazon Pay, Buy With Prime, and more.
Stripe will expand its use of Amazon Web Services, Stripe’s long-standing cloud infrastructure provider, to run and grow its business while reliably serving millions of internet companies.
Stripe has long relied on AWS to provide the core compute infrastructure on which Stripe is built. The partnership has allowed Stripe to increase developer productivity and accelerate product development even as Stripe has scaled to support millions of internet businesses around the world. Under today’s agreement, Stripe will continue to expand its AWS footprint and to transform global commerce by taking advantage of AWS’s rapidly-expanding suite of services, including Graviton for efficiency and performance in data processing, and Nitro enclaves to enhance data security.

If you don't know how Stripe is using Graviton today, I encourage you to watch this amazing talk called AWS Graviton deep dive: The best price performance for AWS workloads in the last re:Invent 2022 about the topic with Oran Barak (Head Of Core Compute Engineering at Stripe)

Amazon SageMaker is now available in AWS GovCloud (US-East) Region

Amazon SageMaker is now available in AWS GovCloud (US-East) Region. Starting today, you can build, train, and deploy machine learning (ML) models in the region.

AWS Compute Optimizer is now available in AWS GovCloud (US) Region

AWS GovCloud (US) Region customers can now use AWS Compute Optimizer to reduce costs and improve performance.
By using machine learning to analyze historical utilization metrics, AWS Compute Optimizer helps customers choose optimal configurations for three types of AWS resources: Amazon Elastic Compute Cloud (EC2) instance types, Amazon Elastic Block Store (EBS) volumes, and AWS Lambda functions.

Announcing the general availability of AWS Local Zones in Lagos, Lima, and Querétaro

AWS Local Zones are now available in three new metro areas—Lagos, Lima, and Querétaro. You can now use these AWS Local Zones to deliver applications that require single-digit millisecond latency or local data processing.
In early 2022, AWS announced plans to launch AWS Local Zones in over 30 metro areas across 27 countries outside of the US. AWS Local Zones are also generally available in 12 metro areas outside of the US (Bangkok, Buenos Aires, Copenhagen, Delhi, Helsinki, Hamburg, Kolkata, Muscat, Perth, Santiago, Taipei, and Warsaw) and 16 metro areas in the US (Atlanta, Boston, Chicago, Dallas, Denver, Houston, Kansas City, Las Vegas, Los Angeles, Miami, Minneapolis, New York City, Philadelphia, Phoenix, Portland, and Seattle).

AWS Pricing Calculator now supports optimized pricing estimation for EC2 Dedicated Hosts

Windows Server and SQL Server on Amazon EC2 calculator now supports Dedicated Hosts price estimation. With this feature, you can now generate optimized price estimate for bring-your-own-license (BYOL) scenarios on Dedicated Hosts.


Articles and Tutorials

How switching to AWS Graviton slashed our infrastructure bill by 35%, by Lewis Monteith, co-founder of Squeaky.AI

We’re strong believers in continuously improving tools and process, and that’s really paid off this time. By having all our apps running the latest versions of languages, frameworks and dependencies, we’ve been able to switch over to brand new infrastructure with almost zero code changes.
Switching our entire operation over to Graviton only took one day and we’ve saved approximately 35% on our infrastructure costs. When comparing our CPU and memory usage, along with latency metrics, we’ve seen no performance degradation. In fact, our overall memory footprint has dropped slightly, and we expect to see further improvements as the month rolls on.
It’s fair to say we're all-in on ARM, and any future pieces of infrastructure will now be powered by Graviton.

Save big with AWS Aurora: How to upgrade any instance to Graviton2, by the CloudFix team

We can empathize with any DBAs being hesitant to switch to Graviton2.
Switching processor architecture can often come with a long list of problems and risks. However, with RDS and Aurora, AWS has done the heavy lifting, and the upgrade to Graviton2 is safe and seamless.
You can even mix Graviton and non-Graviton instances in your cluster, and if you – as per our recommendations below – add new read replicas and promote them rather than upgrading the existing instances directly, you can upgrade to Graviton2 with practically no downtime.

CleverTap Saves 20% with AWS Graviton and Data Lake on Amazon S3 for Petabyte-Scale User Retention Platform

CleverTap found that Graviton2 instances were up to 20 percent less expensive than their x86 counterparts and offered equal or better performance.
The instances also excelled in terms of performance while executing vectorized ML algorithms.
By adopting a data lake approach to storage with Amazon S3 and converting to Graviton2 instances for queries, CleverTap has reduced its overall compute requirements by 50–75 percent.
It has also laid a strong foundation for HPC for increasing compute-intensive ML workloads.

OpenShift Container Platform 4.12 now supports Graviton3 instances

OpenShift Container Platform 4.12 is now supported on ARM architecture-based Azure installer-provisioned infrastructure. AWS Graviton 3 processors are now available for cluster deployments and are also supported on OpenShift Container Platform 4.11. For more information about instance availability and installation documentation, see Supported installation methods for different platforms

5 Best Practices for Reducing Kubernetes Costs

Another option of saving in the cloud is low-cost processors like Amazon Graviton processors are custom-designed processors that are built using ARM Neoverse cores and are optimized for running cloud-native workloads. They can provide a cost-effective alternative to x86-based processors for running Kubernetes clusters on AWS.


Slides, Videos and Audio

[VIDEO] ARM vs x86 performance benchmark (amd64 vs arm64 - AWS Graviton - AWS EKS - Kubernetes - Golang), by Anton Putra (Lead DevOps Engineer at Juniper Networks):Arm64

A very interesting (AWS Graviton2) vs Amd64 (AMD Epyc) performance benchmark.

You can find the code of the tutorial on GitHub


Jobs

If you are actively looking for a new role, you should join our Talent Collective here. It's completely free to the candidates.

And if you are a company looking for new members for your time, you can get access to our Talent Collective here.

There are 21 active candidates ready for interviews:


Events

No events this week


Quote of the week

We reduced our AWS cloud costs (dev environment) by 50% in less than 3 months.

Crazy optimizations?

Not really.

Mostly, it was the results of a few small tweaks that might be useful in your environment too.

1. Reduce wastefulness. For example, we were running two environments with sometimes duplicate computations. We unified them and saved on cost as well as simplified internal processes.

2. Consider data retention and storage options. We had tons of old data that was no longer needed. We got rid of it by adjusting our S3 lifecycle policies. Also, we started to differentiate between data we want to keep in the Standard Storage and the older records we are happy to put into Glacier Deep Archive.

3. Switch to Graviton instances. We changed our EMR cluster to use Graviton instances which have a better price-performance ratio.

We were already using Spot Instances for most of our workloads, so no change there, but if you don't this could be a big money saver as well.

Francesco Cavrini, Engineering Manager at ThousandEyes

Source: LinkedIn

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Marcos Ortiz

I'm a Data Engineer by day at Riot Games (via X-Team ) and by night, I curate the last news/product announcements/resources about AWS Silicon (Graviton, AWS Nitro, Inferentia, and Trainium).

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