Abstract: Techniques are described herein for managing transactions between data consumers and data providers using a blockchain. In some embodiments, a blockchain network receive smart contracts that govern access rights to data sets provided by blockchain members and smart contracts that execute blockchain transactions based on the usage of data sets. When a data set is provided to a blockchain member through the blockchain network, usage of the data set may be tracked. Responsive to detecting usage of the data set, one or more smart contracts may execute one or more blockchain transactions within the blockchain network.

Abstract: Techniques for analyzing, understanding, and remediating differences in configurations among many software resources are described herein. Machine learning processes are applied to determine a small feature set of parameters from among the complete set of parameters configured for each software resource. The feature set of parameters is selected to optimally cluster configuration instances for each of the software resources. Once clustered based on the values of the feature set of parameters, a graph is generated for each cluster of configuration instances that depicts the differences among the configuration instances within the cluster. An interactive visualization tool renders the graph in a user interface, and a management tool allows changes to the graph and changes to the configuration of one or more software resources.