  Cloud systems are complex, large, and dynamic systems whose behavior must be
continuously analyzed to timely detect misbehaviors and failures. Although
there are solutions to flexibly monitor cloud systems, cost-effectively
controlling the anomaly detection logic is still a challenge. In particular,
cloud operators may need to quickly change the types of detected anomalies and
the scope of anomaly detection, for instance based on observations. This kind
of intervention still consists of a largely manual and inefficient ad-hoc
effort.
  In this paper, we present Anomaly Detection as-a-Service (ADaaS), which uses
the same as-a-service paradigm often exploited in cloud systems to declarative
control the anomaly detection logic. Operators can use ADaaS to specify the set
of indicators that must be analyzed and the types of anomalies that must be
detected, without having to address any operational aspect. Early results with
lightweight detectors show that the presented approach is a promising solution
to deliver better control of the anomaly detection logic.
