An integrated cloud-ready geospatial data management system to store, process, manage, provide and display vector-/raster- and time-series data providing OGC interfaces and a customisable WebGIS to ensure FAIR data. Environmental research increasingly relies on spatial data from diverse sources, including remote sensing, modeling, and sensor networks. This data must be effectively stored, processed, published, and visualized in line with the FAIR principles. We present spatial.IO, a modular, cloud-ready application designed to support the complete data lifecycle of raster, vector, and time series geospatial data, using open standards and open-source components. spatial.IO functions as a Spatial Data Infrastructure (SDI) that integrates services for metadata management, data provisioning, user access, and visualization. It incorporates GeoServer for data publication via OGC standards such as WMS and WFS, GeoNetwork for metadata cataloging and DOI assignment, a FROST®-Server implementing the SensorThings API for time series data (with optional integration into the time.IO digital ecosystem), and S3-compatible object storage for optimized cloud access. A Django-based web application allows users to manage and configure spatial data and visualizations through a self-service interface. The system supports widely used geospatial formats including NetCDF, Cloud-Optimized GeoTIFF (COG), Shapefiles, and CSV point data. Metadata are structured using JSON-LD to enable semantic interoperability and ensure future-proof data reuse. Data can be ingested from various infrastructures or directly uploaded, with optional integration into HPC Clusters or AI platforms via the S3-compatible storage backend. The WebGIS module allows for the creation of custom instances for interactive spatial data visualization. Current applications include the UFZ Water Resources Information System Germany (WIS-D) and the UFZ Forest Condition Monitor. spatial.IO enforces community standards such as the Binding Regulations for Storing Data as netCDF Files - widely adopted in the environmental modeling community - and the DataCite Metadata Schema for persistent identification and citation. The platform aims to reduce manual intervention through semi-automated workflows and standardized interfaces. It offers a robust solution for FAIR-aligned, cloud-based spatial data management and is continuously evolving into a self-service platform that supports reproducible, scalable, and open spatial data workflows. Requirements Simply FAIR Science- and Management friendly: Provide interoperable and reliable spatial data enriched by metadata and with provenance information. User friendly: Easy to use user interface for people that manage spatial data or create WebGIS for netCDF data, without requiring knowledge about underlying technologies like databases. Admin friendly: A scalable and transferable container based solution that will smoothly integrate into typical scientific IT landscapes. Developer friendly: Common open source solutions structured by microservice architecture to keep it open and simple to extend for developers. Features S3 cloud-storage FROST®-Server to store and access sensor data (in combination with time.IO and SaQC) Creation of custom interactive WebGIS components for netCDF, STA and GeoTIFF data Extendable processes to get spatially aggregated values raster data Use of django framework to make configuration of data and WebGIS user-friendly Workflow for automated creation of OGC web services with GeoServer of new spatial data Workflow for automated creation of metadata entries in GeoNetwork Quickstart Install Docker Engine (Community Edition - CE is enough) and Docker Compose Install a git client and checkout the spatial.IO repository or unzip the attached archive Follow step-by-step instructions in README.md to startup Techstack, dependencies and third party open source products FROST®-Server GeoServer GeoNetwork django PostgreSQL Vue Bulma pygeoapi Acknowledgements We thank the Helmholtz Association and the Federal Ministry of Education and Research (BMBF) for supporting the DataHub Initiative of the Research Field Earth and Environment. The DataHub enables an overarching and comprehensive research data management, following FAIR principles, for all Topics in the Program Changing Earth – Sustaining our Future.