Unlock Efficiency: How Companies Are Managing AI/ML Workflows
Did you know? According to recent surveys, a staggering 65% of companies are leveraging vendor-specific solutions or turning to cloud solution providers to effectively manage and schedule their AI/ML jobs.
But that’s not all! 25% are opting for the flexibility of Slurm or another Open Source tool, while 9% are relying solely on Kubernetes—a choice that comes with its own set of considerations as it does not inherently support scheduling.
🔍 Why the mix? Each option offers distinct advantages and considerations. Vendor-specific solutions and cloud providers offer convenience and comprehensive support, but for those seeking customization and flexibility, Open Source tools like Slurm emerge as a strong contender. However, with Kubernetes’ rising popularity, it’s crucial to note its limitations when it comes to scheduling AI/ML jobs.
The key takeaway
Companies are navigating a diverse landscape of options to optimize their AI/ML workflows. Understanding the nuances of each solution is essential to make informed decisions that align with your organization’s goals and needs.
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