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11/02/2024 12:36:58 pm

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Spotify Announces Infrastructure Migration to Google Cloud

Spotify

(Photo : Reuters) Spotify is moving to Google Cloud from Amazon Web Services.

Popular music streaming service Spotify has announced that it is migrating its entire infrastructure from Amazon Web Services to Google Cloud. Spotify claims that Google's data platform and tools are far superior to Amazon's, hence the decision to move.

In a statement posted on the official Spotify blog, Spotify engineering and infrastructure vice president Nicholas Harteau wrote, "Good infrastructure isn't just about keeping things up and running. It's about making all of our teams more efficient and more effective, and Google's data stack does that for us in spades."

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Despite the decision to move to Google Cloud, Spotify's content-delivery service including the company's music file storage will remain on Amazon Web Services.

As part of the migration, Google said that Spotify will start implementing Google Cloud Datashore and Google Cloud Bigtable. Spotify is also expected to deploy Google's cloud networking services like Cloud VPN, Direct Peering and Cloud Router.

As for majority of Spotify's data, the company will adopt a new stack technology which includes moving from Hadoop, Hive, MapReduce along with a series of "home-grown" dashboarding tools.

The new partnership with Google also means that Spotify will adopt a handful of data processing tools such as Google Cloud Dataproc, Google Cloud Dataflow, Google BigQuery and Google Cloud Pub/Sub.

Experts believe that the massive migration to Google Cloud will take a lot of time to be completed. Due to this, Spotify is planning to create a dedicated engineering blog that will report on important details and changes as they happen.

Market analysts predict that the huge amount of data generated by Spotify's seven million users may lead to Google dropping the price of some of its cloud services. The search giant has been regularly dropping the price of its cloud services as it embraces the "more users, lower cost" price modelling.

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