during offline processing:

updating a recent history table with critical events and any associated non-critical events that may occur in the distributed network;

computing conditional probability values into a probability table, said probability values comprising joint probability values reflecting a probability that a sequence of two or more non-critical events happen before the critical event occurs;

periodically updating the probability table;

periodically examining the probability table to determine when online analysis of the non-critical event is possible; and

generating event masks for use in a masking mechanism to filter a subset of the non-critical events associated with the critical events so that online analysis can be carried out in real-time;

during online processing:

loading the conditional probability table and the event masks computed from offline analysis;

dynamically filtering the non-critical events using the masking mechanism comprising timeout and probability thresholds;

determining that the probability of the occurrence of the critical event has surpassed a threshold level using the conditional probability table;

migrating a process away from the critical event if it is determined that a timeout period has not elapsed; and

if it is determined that the timeout period has elapsed:

reloading the conditional probability tables; and

generating new event masks to filter another subset of the non-critical events.