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Critical networked services enable significant revenue for network operators and, in turn, are regulated by Service Level Agreements (SLAs). In order to ensure SLAs are being met, service levels need to be monitored. One technique for this involves active measurements, such as IPSLA. However, active measurements are expensive in terms of CPU consumption on network devices. As a result, active measurements usually can cover only a fraction of what could be measured, which can lead to SLA violations being missed. The definition of which subsets of service paths to measure and to configure corresponding measurement probes is a practice that does not scale well and results in fairly static measurement setups that do not adapt well to shifting networking patterns. We propose a solution to increase the detection rate of SLA violations in which devices in a network autonomously and dynamically determine how to place probes in order to detect service level violations. It does not require human intervention, is adaptive to changes in network conditions, resilient to networking faults, and independent of the underlying active measurement technology. Our solution is based on peer-to-peer principles and is characterized by a high degree of decentralized decision making across a network using a self-organizing overlay. In these experiments it is possible to observe that an increase in the information used in probe placement decisions decreases the number of SLA violations missed.