Xiaomi’s data‑lake team explains how they tackled small‑file issues, unified metadata with Gravitino, migrated Hive to Iceberg and Fileset, leveraged JuiceFS for multi‑cloud storage, and combined Iceberg and Paimon to achieve cost‑effective, high‑performance batch and real‑time analytics.
This article explains how to gather JuiceFS access logs using the LogCollector agent, parse and structure them with TLS, design index fields, build analytical dashboards, run advanced SQL queries for write‑IO distribution, sequential‑read ratios, overwrite detection, file‑lifecycle analysis, and set up real‑time monitoring and alerting for performance anomalies.
This guide walks ops engineers through setting up comprehensive monitoring for JuiceFS CSI in Kubernetes, covering metrics extraction via the mount pod, creating a PodMonitor for Prometheus, and visualizing data with Grafana dashboards to enable proactive issue detection and rapid response.
This article explains how JuiceFS integrates with Kubernetes via the CSI interface, covering its three deployment modes, the detailed Mount‑Pod workflow, step‑by‑step Helm deployment, configuration, verification, and why this cloud‑native storage solution outperforms traditional block storage for modern applications.
This guide explains what JuiceFS is, its cloud‑native architecture separating data and metadata, and provides step‑by‑step instructions—including prerequisites, client installation, formatting, mounting, and verification—to help you deploy the high‑performance distributed file system on object storage and PostgreSQL.
This article thoroughly examines how JuiceFS, a FUSE‑based distributed file system, aligns with Linux's discretionary and mandatory access control models, implements Unix permissions, POSIX ACLs, special permission bits, capability handling, and SELinux integration, while detailing practical configurations such as SDK access, root‑squash, all‑squash, and optimized ACL storage.
This article explains the evolution of file system architecture from kernel‑level VFS to userspace via FUSE, reviews the historical role of NFS, details JuiceFS's implementation on top of FUSE, and presents benchmark results that demonstrate its high throughput and practical limitations.
This article presents JuiceFS, a cloud‑native distributed file system that bridges the gaps between HDFS and object storage, explaining Data Lake and Lakehouse concepts, comparing storage options, detailing JuiceFS's architecture and performance benefits, and showcasing real‑world user case studies.
The 2023 online summit held on August 5‑6 showcases a series of technical talks by industry experts on modern big‑data storage architectures such as Paimon, JuiceFS, Databend, and CloudFS, highlighting cloud‑native design, storage‑compute separation, and practical implementation experiences.
This article examines the evolution of big‑data storage from on‑premise HDFS to cloud‑native object storage, compares their architectures and performance, outlines future lakehouse storage requirements, and demonstrates a practical implementation using the JuiceFS distributed file system.
This article explains how Metabit Trading built a cloud‑native quantitative research platform using Fluid and JuiceFSRuntime to achieve elastic compute, high‑throughput data caching, and cost‑effective scaling for AI‑driven trading strategies.
This article details Volcano Engine's edge cloud storage challenges, evaluates multiple storage solutions, and explains how JuiceFS was adopted to simplify workflows, boost read/write performance, and provide a cloud‑native, POSIX‑compatible system for large‑scale edge rendering workloads.
This article reviews the evolution of file storage, outlines the challenges of the cloud era, and details JuiceFS's design philosophy, architecture, key capabilities, and real‑world use cases such as Kubernetes, AI, big‑data analytics, and NAS migration to the cloud.
This article reviews the evolution of file storage, outlines challenges of cloud‑native data management, and details JuiceFS’s cloud‑native design philosophy, architecture, and key use cases such as Kubernetes, AI, and big‑data workloads.
This article presents Ctrip's experience migrating over 2 PB of cold data to JuiceFS, detailing the system's architecture, metadata engine selection, extensive performance testing, fault‑tolerance analysis, and operational optimizations that reduced storage and maintenance costs while supporting future petabyte‑scale workloads.
This presentation provides a comprehensive overview of JuiceFS, an open‑source cloud‑native distributed file system, detailing its role in modern data lake and lakehouse architectures, comparing it with HDFS and object storage, and highlighting its performance, integration, and community ecosystem.
Shopee ClickHouse implements a cold‑hot storage architecture by mounting JuiceFS‑backed S3 as a remote volume, using table‑level storage policies and TTL‑driven background moves to shift data from SSD to cold storage, achieving cost‑effective scalability, improved disk utilization, and validated performance despite operational challenges such as Redis memory pressure and small‑file handling.
This case study details how integrating JuiceFS with Presto reduced HDFS cluster load by about 26%, achieved over 90% cache hit rate for ad‑hoc queries, and lowered average query latency by roughly 13%, while simplifying operations and improving system stability.
