SLFS: a Flexible, Low-Cost Distributed File System Using Serverless Designs

Jul 16, 2026

Large-scale distributed file systems must allocate capacity for peak demand, even though file access patterns shift unpredictably and leave resources idle during off-peak periods. Existing scaling granularity is at the whole-server or storage-node level, requiring costly data migration and reconfiguration that take minutes to hours. SLFS is a serverless-based distributed file system implementing both data and metadata operations with millisecond elasticity and pay-per-use execution. It uses key-value-store-backed services, a multi-threaded short-lived server design to mitigate cold starts, and a coordinator to enforce lifetimes and map files to function instances, enabling flexible backend selection and lower cost while maintaining performance.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages15

Reading Time38 min

Introduction

Resource over-provisioning and coarse-grained scaling

Serverless computing as an alternative

Prior work on serverless metadata/file services

Proposed approach: SLFS

SLFS: a Flexible, Low-Cost Distributed File System Using Serverless Designs Cheng Hao (Ryan) Yang∗ Northeastern University Boston, MA, USA Paola Alsharabaty∗ Northeastern University Boston, MA, USA Soufiane Jounaid Northeastern University Boston, MA, USA Cristina Nita-Rotaru Northeastern University Boston, MA, USA Ji-Yong Shin Northeastern University Boston, MA, USA arXiv :2607 .0 1486v 1 [ cs .DC] 1 Jul 2026 Abstract Large-scale distributed file systems must provision resources for peak demand, yet file access patterns fluctuate significantly, leaving substantial capacity idle during off-peak periods. Existing scaling mechanisms operate at the granularity of entire servers and take minutes to hours, making them unable to track the rapid, finegrained load variations that file systems commonly experience. Serverless computing, with its millisecond-granularity elasticity and pay-per-use pricing, offers a compelling alternative. We present SLFS, the first distributed file system built with serverless functions for both data and metadata operations. SLFS implements file services on top of key-value stores, keeping function operations simple and short, and introduces a novel multi-threaded, short-lived server design that overcomes the cold-start problem while maintaining low cost. A policy-enforcing coordinator efficiently maps files to function instances, scales the system elastically, and controls function lifetimes to balance performance and cost. SLFS can flexibly run on diverse storage backends—from cloud-native services like S3 to user-managed key-value stores—enabling configurable costperformance trade-offs. Our evaluation shows that SLFS mitigatescold starts by 580× compared to the base serverless design and outperforms 􀁟FS, EFS, and Ceph at up to 63%, 68%, and 63% lower cost, respectively. 1 Introduction Large-scale distributed file systems are composed of hundreds of server nodes where some nodes handle file operations while others focus on storing data [32, 49, 57, 65, 78, 83] . In practice, file system load fluctuates significantly: not all files are actively accessed at any given time, and access patterns shift unpredictably across time of day, workload phase, and tenant activity. Yet, to meet peak demand and maintain acceptable latency, operators must provision resources for worst-case load, leaving substantial capacity idle during off-peak periods. This over-provisioning translates directly into wasted cost. Existing distributed file systems offer scaling mechanisms, but these operate at the granularity of entire servers or storage nodes—adding or removing a node involves data migration, rebalancing, and reconfiguration that can take minutes to hours [7, 83]. Such coarse-grained scaling cannot track the rapid, fine-grained load variations that file systems commonly experience. ∗ Both authors contributed equally to this research. Serverless computing offers a compelling alternative. In the serverless model, users register function images and the framework dynamically launches, auto-scales, and terminates function instances on demand, charging only for the resources consumed during execution [42, 54, 70] . This model provides two key benefits for fluctuating workloads. First, elasticity: function instances can scale from zero to thousands and back in seconds, matching demand at a granularity far finer than server-level scaling. Second, cost efficiency: because the pricing model charges per millisecond of execution, applications with idle intervals between bursts of activity pay only for the time they are active, unlike VMs that incur cost whether busy or idle. These properties have already enabled serverless designs for data analytics [67, 89], machine learning [39, 52], and video encoding [46], hinting at the potential of serverless computing to host a broader class of backend services. Distributed file systems are natural candidates to benefit from these properties. Most file operation

FAQs

How does SLFS address the serverless cold-start problem while controlling cost?

SLFS introduces a novel multi-threaded, short-lived server design to mitigate cold starts, and uses a policy-enforcing coordinator that maps files to function instances and scales elastically while controlling function lifetimes to balance performance and cost.

Jul 16, 2026

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