A method for implementation by one or more data processors forming part of at least one computing system, the method comprising: placing a sample of data comprising files for access or execution by a computing system within a directed acyclic graph published to central resource manager represented as a queue of work items for a particular worker class, wherein the directed acyclic graph comprises a plurality of hierarchical nodes in which nodes are represented as the individual worker classes that are used to process the sample of data; scheduling, by the central resource manager using a scheduler, work items according to at least a sample prioritization or a worker rate within the queue for each of a plurality of workers, which are registered with the central resource manager and receive work items via a pull mechanism, by traversing the nodes of the directed acyclic graph; serving, by a router, the work items to the workers according to the queue; receiving results from the workers for the work items that comprise extracted features from the sample of data; and classifying the sample of data based on the received results to indicate whether or not at least one file in the sample of data likely comprises malicious code; wherein: the nodes of the directed graph are traversed based on the received results; each work item comprises one or more tasks to effect extraction of features from the sample of data; each worker class represents a resource that is managed by the central resource manager and each worker class is registered by providing the router a set of features it can provide to the router, as well as a set of routes and associated prerequisites and conditionals for each route; the directed acyclic graph represents a workflow, in which nodes are represented as the individual classes of workers and is defined by worker class prerequisites in a backward chain dependency mapping process that attempts to generate the shortest path through the directed acyclic graph resulting in a forward chaining of worker classes that represent the optimal pathing through the workflow. placing a sample of data comprising files for access or execution by a computing system within a directed acyclic graph published to central resource manager represented as a queue of work items for a particular worker class, wherein the directed acyclic graph comprises a plurality of hierarchical nodes in which nodes are represented as the individual worker classes that are used to process the sample of data; scheduling, by the central resource manager using a scheduler, work items according to at least a sample prioritization or a worker rate within the queue for each of a plurality of workers, which are registered with the central resource manager and receive work items via a pull mechanism, by traversing the nodes of the directed acyclic graph; serving, by a router, the work items to the workers according to the queue; receiving results from the workers for the work items that comprise extracted features from the sample of data; and classifying the sample of data based on the received results to indicate whether or not at least one file in the sample of data likely comprises malicious code; wherein: the nodes of the directed graph are traversed based on the received results; each work item comprises one or more tasks to effect extraction of features from the sample of data; each worker class represents a resource that is managed by the central resource manager and each worker class is registered by providing the router a set of features it can provide to the router, as well as a set of routes and associated prerequisites and conditionals for each route; the directed acyclic graph represents a workflow, in which nodes are represented as the individual classes of workers and is defined by worker class prerequisites in a backward chain dependency mapping process that attempts to generate the shortest path through the directed acyclic graph resulting in a forward chaining of worker classes that represent the optimal pathing through the workflow. the nodes of the directed graph are traversed based on the received results; each work item comprises one or more tasks to effect extraction of features from the sample of data; each worker class represents a resource that is managed by the central resource manager and each worker class is registered by providing the router a set of features it can provide to the router, as well as a set of routes and associated prerequisites and conditionals for each route; the directed acyclic graph represents a workflow, in which nodes are represented as the individual classes of workers and is defined by worker class prerequisites in a backward chain dependency mapping process that attempts to generate the shortest path through the directed acyclic graph resulting in a forward chaining of worker classes that represent the optimal pathing through the workflow.