When managing systems, it is often difficult to find a suitable point in time to update without disrupting the availability. As Cyber-Physical Systems influence the physical environment, the importance of safely managing such systems, in order to avoid dangers, increases. Context-aware systems have previously been configured to only execute management processes when a set of situations is valid. Here, a situation can be understood as any event capable of changing, often connected with some form of sensor. This enables improved timing, but could still lead to an undesirable situation change during an update, resulting in a decrease of availability or forcing a rollback. To avoid situation changes, this thesis proposes executing processes in a time-frame during which all situations stay in their correct state. Scheduling the execution of a management operation during a time-frame is only possible when the duration of the process is known. Using TOSCA and the OpenTOSCA Runtime a prototypical implementation allowing the measurement of management processes in order to generate a worst-case execution time is introduced. Generating timing information enables context-aware systems to estimate if an operation can be performed during a time-frame, therefore decreasing the likelihood of executing management processes at undesired times. The timing information from plans can then be used to create profiles for often occurring actions, enabling the possibility of providing users with timing information while modeling the topology of a system.