A computer implemented method comprising: determining, at a remote device, a first occurrence of an event associated with a resource; storing, at a memory of the remote device, a first resource instance of the resource comprising a first resource instance identifier and first event data associated with the first occurrence of the event; determining, at a remote device, a second occurrence of an event associated with the resource; storing, at the memory of the remote device, a second different resource instance of the resource comprising a second resource instance identifier and second event data associated with the second occurrence of the event; and transmitting, from the remote device to an external entity, at least one of the first resource instance and the second different resource instance.

A building management system for generating a building model for a building and operating building equipment of the building based on the building model. The system includes a processing circuit configured to receive a context, wherein the context includes metadata defining the building model for the building and generate a building model editor interface for viewing and editing the received context, wherein the building model interface includes building elements for the building model, wherein the building elements are based on the received context and represent the building equipment. The processing circuit is configured to receive user edits of the context via the building model interface, wherein the user edits include edits to the building elements, generate an updated context based on the user edits of the context, and deploy the updated context to control environmental conditions of the building with the building equipment based on the updated context.

An apparatus for extracting data from a database for object initialization, and apparatus for writing object data to a database, and corresponding methods are provided. A data extraction kernel on the native-side reads database data from a plurality of locations in the database using a database interface and writes the database data to a buffer using a native-side buffer API (application programming interface). An object initialization kernel on the virtual machine (VM-)side reads the database data from the buffer using a native-side buffer API and initializes a plurality of objects. Information indicating one of the plural memory regions in the buffer where the data extraction kernel writes the database data is known to the native-side buffer API and to the VM-side buffer API. According to the application, fast and memory efficient data exchange between a native side and VM side is achieved.

Extending object-schema-based application programming interfaces (APIs) is described. According to one embodiment, a method generally includes receiving, from a user, a schema defining an extension to the API and a reference to a parent node in a graph projection of the API. An API system updates the graph projection of the API to include a node representing the extension and navigable path to the node representing the extension. The API system processes a request from the user by traversing through the updated graph projection of the API, the request representing the navigable path to the node representing the extension.

This specification describes techniques for blockchain-based consensus. One example method includes storing, by a database of a blockchain node, consensus data needed for performing a consensus procedure, wherein the consensus data is retrievable by a first server and a second server during the consensus procedure, wherein the blockchain node is included in a blockchain and comprises the first server, the second server, and the database; in response to a determination that the first server is faulty, retrieving, by the second server in place of the first server, the consensus data from the database and executing the consensus procedure based on the consensus data to generate a consensus result; and storing, by the second server, the consensus result in the database.

Described embodiments provide systems and methods for identifying a context of an endpoint accessing a plurality of microservices is provided. A device intermediary to a plurality of endpoints and a plurality of microservices can receive a plurality of calls to one or more of the plurality of microservices originating from the plurality of endpoints. The device can identify a context for each of the endpoints. The context can include one of a type of device or a type of application. The device can identify, for each unique context, one or more microservices of the accessed by the plurality of endpoints having that unique context. A service graph can be generated to identify the one or more microservices of the plurality of microservices accessed by the plurality of endpoints having that at least one unique context.

A processing method based on distributed stream computing is performed by a computing device. After receiving flow data sent by an upstream computing node, the computing device stores the flow data into a flow data pool. The computing device collects a data ratio of the flow data in the flow data pool to a total capacity of the flow data pool. When the collected data ratio is greater than or equal to a first threshold, the computing device performs an operation of adding a mark for enabling the upstream computing node to decrease a flow data sending rate; when the collected data ratio is less than or equal to a second threshold, the second threshold being less than the first threshold, the computing device performs an operation of deleting the mark for enabling the upstream computing node to increase the flow data sending rate.

A service processing method and a network device, where the network device includes a network processor (NP) and a central processing unit (CPU). The NP is configured to receive a first packet, obtain a packet feature of the first packet, obtain a processing rule corresponding to the packet feature, process the first packet based on the processing rule, to obtain a second packet, and send the second packet to the CPU. The CPU is configured to receive the second packet, and process the second packet. Before the CPU processes the first packet, the NP processes the first packet, and sends the second packet obtained after processing to the CPU.

In another aspect, a system for machine learning using a distributed framework, includes a computing device communicatively connected to a plurality of remote devices, the computing device designed and configured to select at least a remote device of a plurality of remote devices, determine a confidence level of the at least a remote device, and assign at least a machine-learning task to the at least a remote device, wherein assigning further comprises assigning at least a secure data storage task to the at least a remote device and assigning at least a model-generation task to the at least a remote device.

The current document is directed to methods and systems that that generate proxy-object interfaces to external executable code for use in workflows executed by a workflow-execution system. The workflow-execution-engine component of a cloud-management system provides one example of a workflow-execution system in which proxy-object interfaces to external executable code are used. In one implementation, an existing automated-code-generation subsystem generates plug-in class declarations that represent one or more external executables. An additional class-wrapping subsystem then generates a proxy class for each code-generated plug-in class.