As we've already seen today organizations are struggling with the increasing demands of data infrastructure. Another new report from MinIO highlights how organizations are leveraging object storage for AI, machine learning (ML), and data-intensive workloads.
The survey of over 650 IT leaders 70 percent of enterprise data is in object storage today and this is expected to grow to 75 percent over the next two years.
"This research confirms what MinIO, AWS, Azure and Google already know -- that object storage is the storage technology of the cloud -- public, private or edge," says Jonathan Symonds, chief marketing officer at MinIO. "What is more interesting, however, is the expected acceleration of adoption, driven by GenAI workloads. Modern object stores are uniquely qualified to meet the demands of these workloads -- namely throughput performance, immutability and exascale. We are keen to watch this research evolve as enterprises build new storage architectures to support their AI ambitions."
Both public and private clouds are expected to grow their share of AI data over the next 12-24 months. While the majority of respondents indicate that their overall infrastructure is primarily in the public cloud, 68 percent are concerned about the cost of running AI workloads. Looking specifically at current approaches to running AI/ML workloads, the majority of IT leaders cite a hybrid cloud approach as the most popular choice.
AI deployments still come with challenges though, IT leaders cite security and privacy (44 percent), data governance (27 percent), and cloud-native storage (25 percent) as the three biggest challenges to AI success at their organization. This data points to one of the reasons enterprises repatriate data from public to private cloud -- more control over security and privacy. This, and the concerns around cloud-native storage, reflects a larger trend of ensuring data portability.
You can get the report on the MinIO site.
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