Serverless Functions in Cloud–Edge Environments: A Comprehensive Critical Review and Taxonomy
TL;DR
An extensive critical review of serverless functions in cloud–edge environments reveals that cloud–edge serverless systems need accountable placement, state-aware workflows, reproducible benchmarking, trustworthy orchestration, and carbon-aware lifecycle control, which can be achieved only by going beyond latency and elasticity.
Abstract
Cloud–edge continuums are driving the shift of cloud-native applications from centralized data centers to latency-, mobility-, privacy-, and energy-saving applications. The serverless architecture provides an attractive “Function-as-a-Service” (FaaS) model in this transition, as it is driven by events, elastic and fine-grained, and controlled by the platform. But introducing a mix of heterogeneous edge nodes, fog/MEC resources, regional clouds, and hyperscale data centers creates a seemingly simple FaaS deployment problem to solve with a set of multi-objective orchestration challenges: runtime selection, autoscaling, cold start mitigation, placement, migration, workflow coordination, state management, trust, cost, energy, and carbon. In this article, we provide an extensive critical review of serverless functions in cloud–edge environments. While some surveys are narrowly focused on aspects of autoscaling, offloading, IoT, or security, the review brings together architectural evolution, runtime mechanisms, platform ecosystems, governance issues, sustainability issues, and emerging applications using AI. It builds a multidimensional taxonomy ranging from runtime systems, autoscaling, cold start mitigation, function placement, and offloading/migration, to workflow orchestration, state and data management, intelligent scheduling, security, sustainability, and industrial serverless platforms. It also presents a built-in conceptual model that connects application needs, runtime environment, orchestration intelligence, governance policies, and system-level results. The synthesis reveals that cloud–edge serverless systems need accountable placement, state-aware workflows, reproducible benchmarking, trustworthy orchestration, and carbon-aware lifecycle control, which can be achieved only by going beyond latency and elasticity. The paper ends with research directions on adaptive, interoperable, explainable, and sustainable serverless systems on the cloud–edge continuum.