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Amazon Web Services (AWS) is making available in preview a C7gn instance on the Amazon Elastic Compute Cloud (Amazon EC2) based on AWS Graviton processors. The C7gn instances provide up to 200 Gbps network bandwidth and as much as 50% higher packet-processing performance compared to previous-generation C6gn instances.
Announced at the AWS re:Invent 2022 conference, these instances are based on Arm processor architecture that AWS provides as an alternative to x86 processors.
Rahul Kulkarni, director of product management for Amazon EC2, said interest in more efficient AWS Graviton processors has spiked sharply as the overall economic outlook softened. More IT teams than ever are being tasked with finding ways to reduce costs as the overall number of applications being deployed in the cloud continues to grow, he added.
While it’s not clear how many applications are being developed to run natively on Arm processors, Kulkarni noted that the process of refactoring existing applications to run on Arm processors is not as intensive for most applications as it was when previously moving applications from one class of processors to another.
Overall, AWS now offers more than 600 types virtual machine instances on its cloud platform, including a set of Inf2 instances, available in preview, based on custom AWS processors that are optimized for processing workloads that include machine learning algorithms that drive artificial intelligence (AI) models.
Every AWS instance takes advantage of a set of AWS Nitro Cards that offload the overhead virtualization creates so IT organizations can take full advantage of compute resources without having to allocate any resources to run virtualization software, noted Kulkarni. That virtualization tax is instead absorbed by AWS to reduce total cloud costs for the customer, he added.
In addition, more customers are taking advantage of tools such as AWS Cost Optimizer and AWS Karpenter for Kubernetes clusters that employ machine learning algorithms to identify opportunities to reduce the cost of cloud infrastructure by, for example, shifting workloads to different classes of services.
There are, of course, multiple strategies for containing cloud costs that range from committing to consuming a specified amount of compute resources annually at discounted rates to relying more on spot instances that are available for limited amounts of time. Less effective is moving workloads from one cloud provider to another simply because the total cost migrating workloads can be substantial depending on the number of proprietary application programming interfaces (APIs) that have been invoked.
Regardless of approach, the days when developers were allowed to invoke cloud resources at will appear to have come to an end. Enterprise IT organizations are a lot more conscious of the total cost of IT in the cloud era. As a result, many of them are adopting financial operations (FinOps) best practices to maximize utilization of cloud infrastructure resources.
It’s not clear how readily IT organizations will embrace AWS Graviton alongside other classes of Arm processors to achieve that goal, but as the economic outlook continues to remain uncertain, there is no doubt all options are now on the table.
