Hados stores files in a cluster of servers. Its goal is to handle high availability by storing copies of the same file on several nodes. It provides RESTFUL APIs to easily store, check, or retrieve files. Using the cluster APIs, you can retrieve files from whichever node hosts them. To avoid any single point of failure, it is possible to apply a request to any node of the cluster; there is no master node.
LavaFlow creates useful reports on the usage of high-performance computing clusters. It takes data from the batch scheduling system, monitoring, and other tooling, and creates reports which help administrators, managers, and end users better understand their cluster environment. The reports are modular, and new modules are easy to create using templates and Django's query set API. LavaFlow uses human-readable RESTful URLs, making it easy to automate and share links to reports.
Strategico is an engine for running statistical analysis over groups of time series. It can manage one or more groups (projects) of time series: by default, you can get data from a database or CSV files, normalize them, and then save them inside the engine. The first statistical analysis implemented inside Strategico is the "Long Term Prediction": it automatically finds the best model that fits each time series. Some of the models implemented are mean, trend, linear, exponential smoothing, and Arima. Strategico is scalable: the statistical analysis over each time series (of a project) can be run separately and independently. It is suggested that you set up an HPC Cluster (High Performance Computing) and/or use a resource scheduler like slurm. It is developed with R, one of the most famous statistical languages.
Symbolic is an enterprise platform designed to build, configure, and manage your huge and globally distributed data centers. It features cloud computing, Web manager virtual environments (Xen, KVM, and libvirt), clustering support, custom operations and scripts support, and user and role definitions.