- Google is moving thousands of internal workloads from x86 to Arm CPUs
- The company built an AI tool called CogniPort to automate migration fixes
- Google engineers spent months fixing testing bugs tied to x86 infrastructure
Google has embarked on a hugely ambitious project to migrate all of its internal workloads from x86 to Arm-based CPUs, a process that involves one of the largest hardware transitions ever attempted by a global technology company.
The effort aims to let its systems run efficiently on both x86 processors and its custom-built Axion silicon.
With around 30,000 applications already converted, Google continues to rely heavily on automation to handle the huge code base involved in the process.
Porting workloads at warehouse scale
In a blog post describing the project, Google engineering fellow Parthasarathy Ranganathan and developer relations engineer Wolff Dobson noted that the migration began with some of the company’s most critical systems, including F1, Spanner, and Bigtable.
Initially, teams relied on conventional software development practices with dedicated engineers and weekly coordination meetings.
Although they anticipated major architectural hurdles, modern compilers and debugging tools helped reduce many of the anticipated problems.
However, a large amount of time was still spent tuning thousands of tests that were tightly coupled to Google’s existing x86-based infrastructure.
Engineers also faced challenges updating legacy build and release systems, managing production deployments, and ensuring stability across mission-critical environments.
To speed up the transition, Google developed a new AI tool known as “CogniPort.”
The system works by analyzing build and test errors and then trying to fix them automatically, especially in cases where an Arm-specific library or binary fails to compile.
CogniPort has shown a success rate of around 30%, and performs best when handling test corrections, data handling inconsistencies, and conditional platform code.
While not flawless, the tool represents a key step in enabling warehouse-scale automation and reducing the human workload required for such conversions.
The long-term motivation behind Google’s move lies in performance and efficiency – its Axion-powered Arm servers reportedly deliver up to 65% better price-performance and can be as much as 60% more energy efficient than comparable x86 instances.
This shift could result in fewer x86 processors across Google’s vast data infrastructure, potentially changing the makeup of its internal computing clusters.
So far, large applications like YouTube, Gmail and BigQuery already work on both x86 and Arm-based systems.
As Google migrates the remaining 70,000 packages, doubts remain about whether AI tools can handle such scale without adding new maintenance challenges across its systems.
Via The register
Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews and opinions in your feeds. Be sure to click the Follow button!
And of course you can too follow TechRadar on TikTok for news, reviews, video unboxings, and get regular updates from us on WhatsApp also.
