Normalized claim
4K random read IOPS: 150% increase
4K random read IOPS improved to ~500K— a 150% increase.
AlibabaEvidence: Low35/100
Alibaba Cloud Tair KVCache: 3FS-based enterprise KVCache storage pipeline for agent-style inference
Use case typeTraining infrastructure modernizationUpdated Jul 2, 2026
Alibaba Cloud's Tair KVCache team and storage hardware-software integration team upgraded the open-source 3FS file system to support enterprise KVCache storage for AI inference. The work optimized RDMA load balancing and small I/O, added a user-space persistence engine, introduced GPU Direct RDMA and multi-tenant isolation, and built a Kubernetes Operator for one-click deployment, self-healing, elastic scaling, and monitoring. The solution was integrated with SGLang, vLLM, and Tair KVCache Manager to improve long-context and agent-style inference performance.
- Organization
- Alibaba Cloud
- Industry
- Tech & Comms
- Location
- China
- Published
- July 2026
Reported outcomes
4K random read IOPS: Approximately 150% higher
Other quantified impact
CPU utilization: Approximately 27% lowerTTFT: −84%Inference throughput: +830%Near-theoretical peak bandwidth: Approximately 20 GB/s
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
CPU utilization: 27% decrease
CPU utilization dropped by approximately 27%.
Normalized claim
TTFT: 84% decrease
TTFT reduced by 84% vs cold-start recomputation
Normalized claim
Inference throughput: 830% increase
throughput increased by 830%
Normalized claim
Near-theoretical peak bandwidth: 20 GB/s increase
achieved near-theoretical peak bandwidth of ~20GB/s
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Alibaba Cloud
- Provider
- Alibaba
- Maturity
- Unknown
- Linked source
- Alibaba Cloud Blog
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1Training infrastructure modernization
- 2AI model training
- Enhanced 3FS with RDMA traffic load balancing and small I/O tuning.
- Integrated a full user-space persistence engine and enabled GDR support.
- Built cloud-native management via Kubernetes Operator and monitoring dashboard.
- Integrated with inference engines and Tair KVCache Manager for global KVCache reuse.
- 4K random read IOPS increased by 150%.
- CPU utilization dropped by approximately 27%.
- SGLang L3 cold-start TTFT reduced by 84% and throughput increased by 830%.
- SGLang achieved near-theoretical peak bandwidth of about 20 GB/s.
Architecture
3FS-based KVCache storage pipeline with RDMA networking, user-space persistence engine, GDR zero-copy support, Kubernetes Operator management, and integration with SGLang/vLLM and Tair KVCache Manager.
Sources & evidence1
Evidence: Low35/100Evidence strength
- Customer explicitly identified
- Quantified outcome available
- Technical implementation details available
Type: Blog PostPublished: Jul 2, 2026Publisher: Alibaba CloudEvidence: VendorConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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