Abstract: Methods, systems, and computer storage media for providing a multi-tenant system that executes graph language requests using graph operations of a graph language. A graph language request—that configures tenant data for tenants in a multi-tenant system—is executed using a graph operations engine. The graph operations engine receives and parses a graph language request that includes a list of tenants and a definition of data operations. The set of data operations of the definition are executed on a tree of data operation nodes comprising a plurality of leaf nodes and a root node. Executing the data operations is based on graph language actions (e.g., composition, transformation, and aggregation) that support asynchronously returning results data associated with configuring the Tenant data. Executing the data operations of the definition causes generation of results data (e.g., root node results or leaf node results) configuration of the tenant data in the multi-tenant system.

Abstract: The disclosed techniques assist in diagnosing performance problems of a software application. A profiling module dynamically instruments the application at runtime by intercepting a request to compile one of the application's functions and augmenting the function with performance measuring code. This way, instrumentation is installed without recompiling the application. The execution time of a synchronous function is tracked by adding a local variable that stores function entry time, and by inserting code at each function exit point that computes the elapsed time. The execution time of an async function that executes across multiple threads is measured by repurposing a state machine value to also store the initial function entry time. Instrumented functions that are executed at a rate exceeding a threshold are un-instrumented to avoid self-inflicted performance problems. Function invocations associated with a particular activity, such as responding to a particular web request, may be correlated.

Abstract: A method may include receiving, at a server device, a request to extract configuration settings of a source tenant organization from a data store; in response to the request at the server device, recursively accessing the configuration settings of the source tenant organization; generating, at the server device, a configuration tree data structure based on the accessed configuration settings, the configuration tree data structure organized as a plurality of key-value pairs; selecting, at the server device, a target tenant organization; based on the configuration tree data structure, generating, at the server device, a deployment order including chained API calls directed towards the target tenant organization; executing, at the server device, the chained API calls.

Abstract: Methods, systems, and computer storage media for providing a multi-tenant system that executes graph language requests using graph operations of a graph language. A graph language request—that configures tenant data for tenants in a multi-tenant system—is executed using a graph operations engine. The graph operations engine receives and parses a graph language request that includes a list of tenants and a definition of data operations. The set of data operations of the definition are executed on a tree of data operation nodes comprising a plurality of leaf nodes and a root node. Executing the data operations is based on graph language actions (e.g., composition, transformation, and aggregation) that support asynchronously returning results data associated with configuring the Tenant data. Executing the data operations of the definition causes generation of results data (e.g., root node results or leaf node results) configuration of the tenant data in the multi-tenant system.

Abstract: The disclosed techniques assist in diagnosing performance problems of a software application. A profiling module dynamically instruments the application at runtime by intercepting a request to compile one of the application's functions and augmenting the function with performance measuring code. This way, instrumentation is installed without recompiling the application. The execution time of a synchronous function is tracked by adding a local variable that stores function entry time, and by inserting code at each function exit point that computes the elapsed time. The execution time of an async function that executes across multiple threads is measured by repurposing a state machine value to also store the initial function entry time. Instrumented functions that are executed at a rate exceeding a threshold are un-instrumented to avoid self-inflicted performance problems. Function invocations associated with a particular activity, such as responding to a particular web request, may be correlated.

Abstract: Methods, systems, and computer storage media for providing a multi-tenant system that executes graph language requests using graph operations of a graph language. A graph language request—that configures tenant data for tenants in a multi-tenant system—is executed using a graph operations engine. The graph operations engine receives and parses a graph language request that includes a list of tenants and a definition of data operations. The set of data operations of the definition are executed on a tree of data operation nodes comprising a plurality of leaf nodes and a root node. Executing the data operations is based on graph language actions (e.g., composition, transformation, and aggregation) that support asynchronously returning results data associated with configuring the Tenant data. Executing the data operations of the definition causes generation of results data (e.g., root node results or leaf node results) configuration of the tenant data in the multi-tenant system.