Ampere and Oracle Cloud Infrastructure (OCI) are releasing second-generation Ampere-based compute instances, OCI Ampere A2 Compute, based on the AmpereOne family of processors.
The new offering builds upon the success of OCI Ampere A1 Compute instances, which have been adopted by OCI customers and deployed across over 100 OCI services, including Oracle Database services like HeatWave, MySQL, as well as Oracle Cloud Applications.
OCI Ampere A2 Compute instances provide higher core count virtual machines and high-density containers within a single server, delivering more performance, scalability, and cost-efficiency for cloud native workloads. In addition, the OCI Ampere A2 Compute series further extends OCI's lead in both Arm-based cloud computing and price-for-performance.
"OCI and Ampere began our collaboration with the ground-breaking A1 shapes. We've demonstrated the versatility of these shapes on a wide range of workloads from general purpose applications and OCI services to the most recently announced and highly demanding use case: Llama3 generative AI services," said Jeff Wittich, chief product officer at Ampere. "Building on this momentum, the new OCI Ampere A2 Compute shapes using our AmpereOne processors are set to create a new baseline in price-performance for the cloud industry across an ever-expanding variety of cloud native workloads and instance types."
Like OCI Ampere A1 instances, OCI Ampere A2 Compute instances show strong performance for multiple AI functions, including generative AI.
Beyond AI, OCI Ampere A1 and A2 Compute instances are also well-suited for other cloud native workloads, such as analytics and databases, media services, video streaming, and web services, according to the vendors.
They offer the linear scalability, low latency, density, and predictable performance these workloads need, bringing more performance and higher cost savings.
OCI Ampere A1 and A2 Compute shapes represent a significant advancement in cloud computing by lowering general purpose cloud computing costs, addressing AI computing efficiency, providing a more predictable and linearly scalable compute resource, and helping companies achieve ESG goals faster.
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