  The advent of serverless computing has revolutionized the landscape of cloud
computing, offering a new paradigm that enables developers to focus solely on
their applications rather than managing and provisioning the underlying
infrastructure. These applications involve integrating individual functions
into a cohesive workflow for complex tasks. The pay-per-use model and
nontransparent reporting by cloud providers make it difficult to estimate
serverless costs, imped-ing informed business decisions. Existing research
studies on serverless compu-ting focus on performance optimization and state
management, both from empir-ical and technical perspectives. However, the
state-of-the-art shows a lack of em-pirical investigations on the understanding
of the cost dynamics of serverless computing over traditional cloud computing.
Therefore, this study delves into how organizations anticipate the costs of
adopting serverless. It also aims to com-prehend workload suitability and
identify best practices for cost optimization of serverless applications. To
this end, we conducted a qualitative (interviews) study with 15 experts from 8
companies involved in the migration and development of serverless systems. The
findings revealed that, while serverless computing is highly suitable for
unpredictable workloads, it may not be cost-effective for cer-tain high-scale
applications. The study also introduces a taxonomy for comparing the cost of
adopting serverless versus traditional cloud.
