Application Hub ML-Lab

The Application Hub is a comprehensive and modular platform delivering Software-as-a-Service (SaaS) products, designed to cater to the diverse and multifaceted needs of the EO community. It is crafted to support a wide array of stakeholders, from developers and service providers integrating cutting-edge algorithms to researchers harnessing computational power, and analysts requiring clear and concise visualisations. At the heart of the Application Hub is the ability to manage the delivery of work environments and tools for a wide range of user tasks, such as develop, host, execute, and perform exploratory analysis of EO applications, all managed within a single, unified Cloud infrastructure.

The Application Hub, leveraging Kubernetes and JupyterHub, creates a robust, scalable, and user-centric platform for EO applications and analytics. Kubernetes ensures scalable operation of containerized applications by managing deployment, operation, and traffic distribution, while JupyterHub orchestrates the launching, scaling, and management of application instances, acting as the primary gateway for user requests. The Hub uses dedicated namespaces for each application pod, ensuring organisation, security, and isolation. It also dynamically configures application pods based on the task, and personalises the experience based on user profiles through Kube Spawner. This design ensures the Application Hub remains modular, scalable, and capable of catering to the dynamic requirements of EO tasks.

Typically, the Application Hub provides access to platforms and web apps in a SaaS mode. Users can engage with containerized Interactive Graphical Applications (IGAs), specialised geospatial data exploration web apps, and customizable dashboards. This allows users not only to explore and analyse results but also to execute new applications or analyses and customise their computing experiences, all accessed from the same integrated Hub interface. Ultimately, this enhances user experience, optimises software usage costs, and promotes ease of use, making it more accessible to the broader EO community.

The Application Hub ML-Lab service leverages JupyterHub as an Application Hub to manage and deploy various web applications, including MLflow, JupyterLab, Code Server, QGIS Remote Desktop, and STAC Browser. JupyterHub acts as a central platform, facilitating the launching and management of these applications, providing a seamless and integrated experience for our users.

By harnessing the Application Hub’s capabilities, our service creates a unified and efficient environment where users can seamlessly switch between these web applications based on their specific needs. This integrated approach enhances productivity, collaboration, and the overall user experience, enabling our users to effectively utilise these applications to accomplish their goals.