Abstract: Technologies are shown for storing data from a data object in a distributed application architecture and reassembling the data object from the stored data. A first set of data from the data object is stored on a distributed file system, and a second set of data from the data object is stored on a blockchain. In response to a request for the data object, a script from the blockchain is executed to generate a reassembled data object by: obtaining, from the blockchain, metadata to reassemble the data object, obtaining the second set of data from the blockchain and the first set of data from the distributed file system, and generating the reassembled data object using the first set of data and the second set of data based on the metadata.

Abstract: Technologies are shown for storing data from a data object in a distributed application architecture and reassembling the data object from the stored data. A first set of data from the data object is stored on a distributed file system, and a second set of data from the data object is stored on a blockchain. In response to a request for the data object, a script from the blockchain is executed to generate a reassembled data object by: obtaining, from the blockchain, metadata to reassemble the data object, obtaining the second set of data from the blockchain and the first set of data from the distributed file system, and generating the reassembled data object using the first set of data and the second set of data based on the metadata.

Abstract: Technologies are shown for storing a data object in a distributed application architecture. Critical data in the data object is stored in an object data block on a blockchain. Noncritical data elements in the data object are stored in data block files at an address on a distributed file system, where the addresses are stored in the data block. The object data block is retrieved from the blockchain. The noncritical elements are retrieved from the file system using the address in the data block. The critical and noncritical elements are combined into a reassembled data object. The critical and noncritical data elements can be differentiated in a data definition for the data object or algorithmically analyzing data in the data object. Metadata for the data object can be stored in the object data block and utilized to combine the critical and noncritical elements into the reassembled data object.

Abstract: Technologies are shown for storing a data object in a distributed application architecture. Critical data in the data object is stored in an object data block on a blockchain. Noncritical data elements in the data object are stored in data block files at an address on a distributed file system, where the addresses are stored in the data block. The object data block is retrieved from the blockchain. The noncritical elements are retrieved from the file system using the address in the data block. The critical and noncritical elements are combined into a reassembled data object. The critical and noncritical data elements can be differentiated in a data definition for the data object or algorithmically analyzing data in the data object. Metadata for the data object can be stored in the object data block and utilized to combine the critical and noncritical elements into the reassembled data object.

Abstract: Methods, systems and media for profiling CPU performance are provided. In one example, a method for profiling CPU performance includes generating a CPU profiling data file using a profiling tool, loading a flame graphing tool into a browser, loading the CPU profiling data file into a profiling page of the browser using the flame graphing tool, converting the loaded CPU profiling data file into an aggregated JSON format, and using the flame graphing tool to generate a flame graph using the aggregated JSON data.