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A tartalmat a Spotify R&D and Spotify R biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Spotify R&D and Spotify R vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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26: A Trillion Events

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Manage episode 399944494 series 3419329
A tartalmat a Spotify R&D and Spotify R biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Spotify R&D and Spotify R vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

How did we learn to do event delivery at scale at Spotify? It’s been a journey. When you do something like tap the play button in the Spotify app, that’s an event. And getting that event data is fundamental to the Spotify experience. Without it, we wouldn’t be able to make music recommendations, pay artists fairly, or track down pesky, hard-to-find bugs. At the most basic level, this seems like a straightforward process: record an event, send that event data to a server somewhere, do something useful with it. Easy, right? But now, multiply that process by 50 million events per second. So, how do we make sure all that important data is delivered reliably, from our client apps to the cloud?

Host and principal engineer Dave Zolotusky talks with 9-year Spotify veteran Riccardo Petrocco about our journey building a event delivery system that can reliably handle a trillion events around the world, moving from Kafka to the cloud, building systems that are simple enough so that nobody tries to find a way around them and encourages “doing the right thing”, the definition of “quality data”, the value of moving up the stack and focusing less on the data pipes and more on what’s in them, and how Backstage makes it easier for our developers to discover, consume, produce, and manage data.

Learn more about Spotify’s data journey:

Read what else we’re nerding out about on the Spotify Engineering Blog: engineering.atspotify.com

You should follow us on Twitter @SpotifyEng, LinkedIn, and YouTube!

  continue reading

30 epizódok

Artwork
iconMegosztás
 
Manage episode 399944494 series 3419329
A tartalmat a Spotify R&D and Spotify R biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Spotify R&D and Spotify R vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

How did we learn to do event delivery at scale at Spotify? It’s been a journey. When you do something like tap the play button in the Spotify app, that’s an event. And getting that event data is fundamental to the Spotify experience. Without it, we wouldn’t be able to make music recommendations, pay artists fairly, or track down pesky, hard-to-find bugs. At the most basic level, this seems like a straightforward process: record an event, send that event data to a server somewhere, do something useful with it. Easy, right? But now, multiply that process by 50 million events per second. So, how do we make sure all that important data is delivered reliably, from our client apps to the cloud?

Host and principal engineer Dave Zolotusky talks with 9-year Spotify veteran Riccardo Petrocco about our journey building a event delivery system that can reliably handle a trillion events around the world, moving from Kafka to the cloud, building systems that are simple enough so that nobody tries to find a way around them and encourages “doing the right thing”, the definition of “quality data”, the value of moving up the stack and focusing less on the data pipes and more on what’s in them, and how Backstage makes it easier for our developers to discover, consume, produce, and manage data.

Learn more about Spotify’s data journey:

Read what else we’re nerding out about on the Spotify Engineering Blog: engineering.atspotify.com

You should follow us on Twitter @SpotifyEng, LinkedIn, and YouTube!

  continue reading

30 epizódok

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