Many large-scale software systems (e.g., e-commerce websites, telecommunication infrastructures and enterprise systems, etc.) must service hundreds, thousands or even millions of concurrent requests. Many field problems of these systems are due to their inability to scale to field workloads, rather than feature bugs. In addition to conventional functional testing, these systems must be tested with large volumes of concurrent requests (called the load) to ensure the quality of these systems. Large-scale testing includes all different objectives and strategies of testing large-scale software systems using load. Examples of large-scale testing are live upgrade testing, load testing, high availability testing, operational profile testing, performance testing, reliability testing, stability testing and stress testing. Large-scale testing is a difficult task requiring a great understanding of the system under test. Practitioners face many challenges such as tooling (choosing and implementing the testing tools), environments (software and hardware setup) and time (limited time to design, test, and analyze). Yet, little research is done in the software engineering domain concerning this topic. Moreover, prior large-scale testing research have been largely focused on telecommunication applications and web-based e-commerce systems. Industry has been focused primarily on creating tools to automatically drive specified load into the system under test (e.g., LoadRunner or Apache JMeter). Large-scale testing is gaining more importance, as an increasing number of systems (on-premise and/or cloud-based systems) are designed to serve thousands or millions of users.