Micro-services is a technology, which enables creation of enterprise applications from small functional blocks distributed across heterogeneous server environments. Micro-services gain popularity due to increasing cloud adoption across organizations undergoing digital transformation.
Due to their principal positioning as interoperable blocks of business logic, micro-services win an increasing attention among BPM professionals as a valuable resource of business automation. However, micro-services are not unique in this respect. Interoperable aggregation of business objects dominates development of corporate IT during all its history. Nearly every notable digital business platform offered its own paradigm of distributed interoperability. Micro-services are just a manifestation of this long trend on the current level of technology.
As any growing ecosystem of business objects, micro-services principally require systematic structuring and maintenance achievable through BPM. Without delimited methodology, dedicated modeling and precious planning complex corporate systems of micro-services can easily fall apart burying costly and time consuming IT initiatives. BPM is principal facilitator and enabler for micro-services universe.
There always exists a discrepancy between a model of business process, however well designed and accurate, and real execution of this process in a business environment. The reason for this gap is an unforeseen depth and hidden details inherent to any real process. Real business model of organization is ultimately unlimited in its depth. Going from highest management levels, it descends to individual departments, client relations, production units, technical code of equipment and controllers etc. In vast majority of cases, it is impossible and senseless to build a complete model covering all and every fine detail of the business. Omitted lower layers of the model create (pseudo) random fluctuations during execution of the model. Real execution paths of a process never follow its model exactly. However, in case of the correct model, we can expect to see that an ensemble of execution paths statistically converges to the model as to its average path over a significant set of observation...
Comments
Post a Comment