November 2024
Intermediate to advanced
332 pages
11h 17m
French
Content preview from Gérer les données natives du cloud sur Kubernetes
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Chapitre 10. Apprentissage automatique et autres cas d'utilisation émergents
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Dans les chapitres précédents, nous avons abordé l'infrastructure de données traditionnelle, notamment les bases de données, les plateformes de streaming et les moteurs analytiques, en mettant l'accent sur Kubernetes. Il est maintenant temps de commencer à regarder au-delà, en explorant les projets et les communautés qui commencent à faire du cloud native leur destination, notamment en ce qui concerne l'IA et la ML.
Chaque fois que plusieurs flèches commencent à pointer dans la même direction, cela vaut la peine d'y prêter attention. Les flèches directionnelles de l'infrastructure de données pointent toutes vers une macro-tendance globale de convergence sur Kubernetes, soutenue par plusieurs tendances interdépendantes :
Des piles communes émergent pour gérer les charges de travail AI/ML à forte intensité de calcul, y compris celles qui exploitent du matériel spécifique tel que les GPU.
Les formats de données communs contribuent à promouvoir le déplacement efficace des données entre les ressources de calcul, de réseau et de stockage.
Le stockage d'objets est en train de devenir une couche de persistance courante pour l'infrastructure de données.
Dans ce chapitre, nous allons examiner plusieurs technologies émergentes qui incarnent ces tendances, les cas d'utilisation qu'elles ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.