  Complex Event Processing (CEP) is a powerful paradigm for scalable data
management that is employed in many real-world scenarios such as detecting
credit card fraud in banks. The so-called complex events are expressed using a
specification language that is typically implemented and executed on a specific
runtime system. While the tight coupling of these two components has been
regarded as the key for supporting CEP at high performance, such dependencies
pose several inherent challenges as follows. (1) Application development atop a
CEP system requires extensive knowledge of how the runtime system operates,
which is typically highly complex in nature. (2) The specification language
dependence requires the need of domain experts and further restricts and
steepens the learning curve for application developers. In this paper, we
propose CEPLESS, a scalable data management system that decouples the
specification from the runtime system by building on the principles of
serverless computing. CEPLESS provides operator as a service and offers
flexibility by enabling the development of CEP application in any specification
language while abstracting away the complexity of the CEP runtime system. As
part of CEPLESS, we designed and evaluated novel mechanisms for in-memory
processing and batching that enables the stateful processing of CEP operators
even under high rates of ingested events. Our evaluation demonstrates that
CEPLESS can be easily integrated into existing CEP systems like Apache Flink
while attaining similar throughput under a high scale of events (up to 100K
events per second) and dynamic operator update in up to 238 ms.
