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Supporting Undoability in Systems Operations

Authors: 

Ingo Weber and Hiroshi Wada, NICTA and University of New South Wales; Alan Fekete, NICTA and University of Sydney; Anna Liu and Len Bass, NICTA and University of New South Wales

Abstract: 

When managing cloud resources, many administrators operate without a safety net. For instance, inadvertently deleting a virtual disk results in the complete loss of the contained data. The facility to undo a collection of changes, reverting to a previous acceptable state, is widely recognized as valuable support for dependability. In this paper, we consider the particular needs of the system administrators managing API-controlled resources, such as cloud resources on the IaaS level. In particular, we propose an approach which is based on an abstract model of the effects of each available operation. Using this model, we check to which degree each operation is undoable. A positive outcome of this check means a formal guarantee that any sequence of calls to such operations can be undone. A negative outcome contains information on the properties preventing undoability, e.g., which operations are not undoable and why. At runtime we can then warn the user intending to use an irreversible operation; if undo is possible and desired, we apply an AI planning technique to automatically create a workflow that takes the system back to the desired earlier state. We demonstrate the feasibility and applicability of the approach with a prototypical implementation and a number of experiments.

Ingo Weber, NICTA & UNSW

Hiroshi Wada, NICTA & UNSW

Alan Fekete, NICTA & University of Sydney

Anna Liu, NICTA & UNSW

Len Bass, NICTA & UNSW

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