Google Cloud Rolls Out Axion-Based C4A VMs for Improved Performance

Google services such as Bigtable, Spanner, and YouTube Ads are already using Axion-based servers in production

Summary
  • C4A instances are available in U.S., Europe, and Asia regions, with further expansion planned
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Alphabet's (GOOG, Financials) Google Cloud announced the general availability of C4A virtual machines, powered by its first custom Arm-based Axion CPUs, which deliver up to 10% better price-performance compared to the latest generation of Arm-based instances from leading cloud providers.

Originally intended for general-purpose tasks, the C4A VMs are currently accessible all over many areas worldwide.

Already beginning to use Axion-based servers, key Google services like Bigtable, Spanner, Big Query, and YouTube Ads point to notable performance improvements. Andi Gutmans, VP and GM of Databases at Google, notes that Spanner in first testing saw up to 60% improved query performance per virtual CPU over previous generation servers.

Offering up to 65% higher price-performance and up to 60% better energy efficiency than equivalent x86-based instances, C4A instances are intended for high-performance use cases such web servers, containerized microservices, and artificial intelligence inference applications. Supported Linux operating systems include RHEL, Ubuntu, and SESE Linux, the VMs come in standard, high-memory, and high-CPU variants.

Apart from improved performance, C4A VMs provide connection tools including up to 50 Gbps conventional bandwidth and 100 Gbps with Tier-1 networking. With up to 350,000 IOPS and 5 GB/s throughput, they also support Google's newest Hyperdisk storage.

Consumers using Google Cloud, including Applause and Dailymotion, have seen significant changes in testing and production settings. Rob Mason, chief technology officer at Applause, emphasized speedier testing cycles and more thorough feedback resulting from Axion CPUs' outstanding performance. Senior DevOps Engineer Corentin Mantion claims Dailymotion has lowered CPU use by 20% while improving general performance.

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