The notion of #Devops serves to accelerate time to market through greater cohesion in the release management life cycle.
So called 'service virtualisation', such as offerings from IBM and CA LISA, enables modular testing practise by learning typical behaviour patterns of defined systems. The effect is a more tightly focused testing process that reduces the dependency on external (inert) services.
Release Automation, such as in the newly acquired Nolio solution, allows the testing process to be further streamlined by providing cohesion through the multistage process. The benefits are most highly felt where complex dependencies and configurations add magnitude to setup and teardown for QA.
Agile methods need agile release management processes, and this is the whole point of #Devops. However the risks in this agile thinking come in end- to-end performance.
The missing link here is provided by prerelease Capacity Planning (such as provided by CA Performance Optimizer) , a virtual integration lab that brings together the performance and capacity footprints of each component in the production service. And while some of those components may be changing and therefore measured through the release management process, others are not - and are measured in production. Creating and assimilating component performance models allows the impact of each sprint to show on IT operations.
Capacity Planning is a true #Devops process. Only by adapting the capacity plan to take into account the step changes due to software release, can the risks of poor scalability and damaging impact be accurately guarded against.