  Cloud systems are complex and large systems where services provided by
different operators must coexist and eventually cooperate. In such a complex
environment, controlling the health of both the whole environment and the
individual services is extremely important to timely and effectively react to
misbehaviours, unexpected events, and failures. Although there are solutions to
monitor cloud systems at different granularity levels, how to relate the many
KPIs that can be collected about the health of the system and how health
information can be properly reported to operators are open questions. This
paper reports the early results we achieved in the challenge of monitoring the
health of cloud systems. In particular we present CloudHealth, a model-based
health monitoring approach that can be used by operators to watch specific
quality attributes. The CloudHealth Monitoring Model describes how to
operationalize high level monitoring goals by dividing them into subgoals,
deriving metrics for the subgoals, and using probes to collect the metrics. We
use the CloudHealth Monitoring Model to control the probes that must be
deployed on the target system, the KPIs that are dynamically collected, and the
visualization of the data in dashboards.
