A framework is described that improves resource utilization during operations executing within workflows of the distributed data processing system (e.g., having a plurality of interconnected nodes) in a disaster recovery (DR) environment configured to support synchronous and asynchronous (i.e., heterogeneous) DR workflows (e.g., generating snapshots and replicating data) that include synchronous replication, asynchronous replication, nearsync (i.e., short duration snapshots of metadata) replication and migration of data objects associated with the workflows for failover (e.g., replication and/or migration) to a secondary site in the event of failure of the primary site. The framework meters (regulates) execution of the operations directed to the workloads so as to efficiently use the resources in a manner that allows timely progress (completion) of certain (e.g., high-frequency) operations and reduction in blocking (stalling) of other (e.g., low-frequency) operations by avoiding unnecessary resource hoarding/consumption and contention. Notably, the framework also provides metering and tuning of properties during execution of the workflows and maintains their state to provide for recovery.