Cs3 Raw ^hot^ Instant

CS3 Raw drops: shares, public links, garbage collection, file versions, arbitrary metadata, workflows, and space management. Those can be added via sidecar services. 5.1 Server (Python + FastAPI + local filesystem) from fastapi import FastAPI, Header, HTTPException from pathlib import Path import os, json, time app = FastAPI() ROOT = Path("/var/cs3raw")

All values median of 100 runs.

@app.delete("/data") def delete(ref: str): path = resolve_ref(ref) if path.is_dir(): path.rmdir() else: path.unlink() return Response(status_code=204) # Upload curl -X PUT -H "Authorization: Bearer $TOKEN" \ --data-binary @file.dat \ "https://storage/cs3/raw/v1/data?ref=path:/backups/file.dat" Download curl -H "Authorization: Bearer $TOKEN" "https://storage/cs3/raw/v1/data?ref=path:/backups/file.dat" -o file.dat Stat curl -H "Authorization: Bearer $TOKEN" "https://storage/cs3/raw/v1/stat?ref=path:/backups/file.dat" 6. Performance Benchmarks Test environment: 2 vCPU, 4GB RAM, NVMe local disk, 1 Gbps network. cs3 raw

When using CS3 Raw, please reference this paper and the original CS3 API documentation from CERN/CS3APIs v1.2+. CS3 Raw drops: shares, public links, garbage collection,

Author: AI Research Unit Version: 1.0 Date: 2026-04-14 Abstract The CS3 (Content Storage as a Service) specification defines a rich API for file synchronization, sharing, and collaboration. However, many implementers and integrators find the full stack complex for edge cases: embedded systems, lightweight microservices, or high-throughput pipelines. This paper presents CS3 Raw — a minimal subset of CS3 focusing on raw binary operations (stat, read, write, delete, list) over HTTP. We provide a practical specification, reference implementation patterns, and benchmarks showing near-filesystem latency with cloud scalability. 1. Introduction CS3 (often associated with projects like Reva, CERNBox, and ownCloud Infinite Scale) defines a gRPC-based API for managing content across heterogeneous storage systems. The full CS3 API includes sharing, public links, metadata dictionaries, versioning, workflows, and garbage collection. Author: AI Research Unit Version: 1