Deterministic execution is useful and sometimes vital in contexts such as in debugging, fault tolerance, and distributed consensus schemes, but deterministic parallel execution presents many technical challenges.  The Determinator project at Yale has built the first operating system implementing a pervasively and enforceably deterministic parallel environment compatible with existing languages.  Determinator's model simplifies parallel programming by offering more predictable semantics and eliminating Heisenbugs in both shared-memory and multi-process parallel code.  Existing parallel software often requires little or no porting, and some applications perform on Determinator comparably to conventional nondeterministic environments.  While Determinator can emulate nondeterministic pthreads-style semantics when necessary, we find that over 90% of the synchronization code throughout several parallel benchmark suites either directly or idiomatically expresses naturally deterministic abstractions.  These results suggest that pervasively deterministic models, such as our Deterministic OpenMP (DOMP) framework, can make Heisenbug-free programming intuitive, accessible, and practical.  Beyond programming convenience, Determinator's ability to enforce determinism even on buggy or malicious code can improve security by preventing malware from detecting or escaping intrusion detection systems, and leads to the first practical method of controlling timing side-channels  in cloud computing environments.