The increase in data volumes from Earth Observation (EO) data in the past decade has led to an emergence of cloud-based services in recent years, but within their own data silos, often behind their respective data access methods. Although there are some efforts on the "Data Federation" to unify the data access, this has not been achieved so far and still will not solve the traditional way of disseminating the EO data, which forces end users to download data from data providers for analysis and processing.

With growing data volumes, the data size often exceeds the capacity of being downloaded and processed locally. Therefore, there are several efforts to bridge the gap between the distributed nature of the EO data processing, allowing end-users to provision compute resources close to the data, eliminating the need to download the data, and focusing on processing data on their respective cloud infrastructure in combination with the emerging cloud-optimized formats such as Cloud Optimized GeoTIFF (COG) and Zarr and frameworks such as Dask.

In this session, we will dive in on how Terraform helps bridge the multi-cloud gap for the EO community. We'll examine practical applications such as the Data Proximity Compute Platform (DPC) and the European Weather Cloud (EWC), addressing various challenges in accessing and disseminating EO data today, and how it can be adapted for other use cases around the globe. We will showcase how Terraform can help to deploy, manage, and operate on multiple Openstack clouds and several Kubernetes clusters as well as how other Hashicorp products can be integrated to offer additional services to end users. In the meantime, we will also highlight the challenges that we have faced in multi-cloud applications, such as service discovery, network connectivity, and security.

Join us to learn more about our journey! We'll give you a detailed look at our setup, highlighting how Terraform can make Multi-cloud and Multi-cluster setups easier.