Speaker
Description
The ALICE experiment at CERN continuously reads out and records data at interaction rates of up to 50 kHz of Pb-Pb collisions. Online processing and reconstruction play a vital role for handling the enormous amounts of data, compressing about 3.5 TB/s of detector raw data down to 160 GB/s of compressed input data for offline reconstruction. The online processing is performed on dedicated Event Processing Nodes (EPNs). As the processing software is in continuous development, regular updates of the software on the EPNs are desirable but, at the same time, they need to be independent of ongoing online operations. In addition, the software needs to be validated on a decoupled production-like setup before being deployed on the production farm and the online workflow should be easily reproducible on a standalone server or laptop. Therefore, the topology of the global workflow graph and each individual process can be configured with a variety of common and unique options. We present how the topology is configured, taking into account the run parameters of the current data taking, input requirements of downstream components in the graph and configuration parameters for all individual tasks. In particular, we allow simple application of parameter overrides at run startup for tests as well as for mitigation of immediate issues during the data taking. The benefits of such an adaptable system will also be demonstrated by real-world examples.