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JuiceFS 1.2: Gateway Upgrade, Enhanced Multi-User Permission Management

JuiceFS 1.2: Gateway Upgrade, Enhanced Multi-User Permission Management

2024-04-22
Jian Zhi
JuiceFS 1.2 Beta 1 is released, with enhanced gateway capabilities and support for POSIX ACL and seamless upgrades.
How to Monitor the JuiceFS File System with Grafana Cloud

How to Monitor the JuiceFS File System with Grafana Cloud

2024-04-18
Herald Yu
Learn how to monitor JuiceFS file system status using Grafana Cloud.
LLM Storage: Performance, Cost, and Multi-Cloud Architecture

LLM Storage: Performance, Cost, and Multi-Cloud Architecture

2024-04-09
Rui Su
Learn how JuiceFS tackles challenges in large language model storage, balancing performance and cost and solving issues in multi-cloud environments.
How Zhihu Ensures Stable Storage for LLM Training in Multi-Cloud Architecture

How Zhihu Ensures Stable Storage for LLM Training in Multi-Cloud Architecture

2024-04-03
Xin Wang
Learn how Zhihu, China’s Quora, ensures stable LLM training and seamless petabyte-scale data migration across clouds with JuiceFS.
How to Persist Data in Google Colab Using JuiceFS

How to Persist Data in Google Colab Using JuiceFS

2024-03-27
Jet
Learn how to persist data in Colab using JuiceFS, overcoming Google Drive’s limitations.
98% GPU Utilization Achieved in 1k GPU-Scale AI Training Using Distributed Cache

98% GPU Utilization Achieved in 1k GPU-Scale AI Training Using Distributed Cache

2024-03-07
Feihu Mo
Learn how JuiceFS achieved over 98% GPU utilization in 1,000 GPU-scale AI training using distributed cache.
BentoML Reduced LLM Loading Time from 20+ to a Few Minutes with JuiceFS

BentoML Reduced LLM Loading Time from 20+ to a Few Minutes with JuiceFS

2024-02-29
Xipeng Guan
Learn how BentoML, a platform for building LLM AI apps, accelerates model loading using JuiceFS in a serverless environment.
How a Distributed File System in Go Reduced Memory Usage by 90%

How a Distributed File System in Go Reduced Memory Usage by 90%

2024-02-22
Sandy
Learn JuiceFS Enterprise Edition’s metadata engine design and optimization methods that reduced its metadata memory usage by 90%.
From Object Storage to K8s+JuiceFS: 85% Storage Cost Cut, HDFS-Level Performance

From Object Storage to K8s+JuiceFS: 85% Storage Cost Cut, HDFS-Level Performance

2024-02-07
Experienced JuiceFS user
Explore the evolution of a financial technology company's big data platform on the cloud, transitioning from object storage + EMR to K8s+JuiceFS.
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