Backblaze continues commitment to the open cloud movement at the cloud-native conference in Atlanta.
Backblaze, Inc. , the cloud storage innovator providing a modern alternative to traditional cloud providers, will engage with engineers and technical leaders as a Silver sponsor of the upcoming KubeCon + CloudNativeCon North America conference in Atlanta on November 10–13.
“KubeCon brings together the cloud-native companies building for developers and AI. We’re here because Backblaze gives those companies and developers a real, independent choice in cloud storage,” said Gleb Budman, CEO of Backblaze.
Kubernetes is the orchestration tool used by 70% of enterprise companies operating in the cloud, according to the Cloud Native Computing Foundation. The highly anticipated conference dedicated to the latest Kubernetes and cloud-native developments takes place around the world, with upwards of 9,000 attendees expected in Atlanta. An increased focus on AI applications allows Backblaze to showcase their signature high-throughput cloud object storage, allowing developers to leverage portable, scalable, and flexible storage that can work alongside any Kubernetes deployment.
“KubeCon brings together the cloud-native companies building for developers and AI,” said Gleb Budman, CEO of Backblaze. “We’re here because Backblaze gives those companies and developers a real, independent choice in cloud storage—fast, affordable, and not locked into a single hyperscaler environment.”
In addition to exhibiting at the conference, Backblaze will also be featured in SiliconAngle’s theCUBE programming, including a live streamed interview with Budman on the importance of having access to scalable storage for cloud-native applications.
Backblaze will showcase B2 Overdrive as high-performance infrastructure for AI. The conference has an increased AI and machine learning focus, including a dedicated learning track exploring “cutting-edge AI and ML advancements in cloud native settings, providing insights into managing data models, deploying machine learning (ML) algorithms, and optimizing workflows with topics like MLOps and GPU utilization in Kubernetes.”
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