The Function-as-a-Service (FaaS) paradigm offers a serverless approach that abstracts the management of underlying infrastructure, enabling developers to focus on application logic. However, leveraging infrastructure-aware features can further optimize serverless performance. We present a software prototype that enhances Apache OpenWhisk serverless platform with a novel architecture incorporating tAPP (topology-aware Allocation Priority Policies), a declarative language designed for specifying topology-aware scheduling policies. Through a case study involving distributed data access across multiple cloud regions, we show that tAPP can significantly reduce latency and minimizes performance variability compared to the standard OpenWhisk implementation.

Functions-as-a-Service (FaaS) is a Serverless Cloud paradigm where a platform manages the scheduling (e.g., resource allocation, runtime environments) of stateless functions. Recent work proposed using domain-specific languages to express per-function policies, e.g., policies that enforce the allocation on nodes that enjoy lower latencies to databases and services used by the function. Here, we focus on affinity-aware scenarios, i.e., where, for performance and functional requirements, the allocation of a function depends on the presence/absence of other functions on nodes. We present aAPP, an extension of a declarative, platform-agnostic language that captures affinity-aware scheduling at the FaaS level. We implement an aAPP-based prototype on Apache OpenWhisk. Besides proving that a FaaS platform can capture affinity awareness using aAPP and improve performance in affinity-aware scenarios, we use our prototype to show that aAPP imposes no noticeable overhead in scenarios without affinity constraints.

Serverless computing has extended its reach to encompass private edge cloud systems, aiming to enhance latency, security, and privacy while optimising resource usage. However, this extension comes with challenges such as running platforms and functions on disparate and resource-constrained devices. To respond to the challenges, we present FunLess, a Function-as-a-Service (FaaS) platform tailored for private edge cloud systems. Unlike conventional solutions relying on container technologies for function invocation, FunLess leverages WebAssembly (Wasm) as its runtime environment. This choice offers several advantages, including inherent security and isolation mechanisms crucial for data integrity and confidentiality, portability and consistent development and deployment, and a reduced memory footprint that allows functions to run on constrained edge devices.

State-of-the-art serverless platforms use hard-coded scheduling policies that are unaware of the possible topological constraints of functions. Considering these constraints when scheduling functions leads to sensible performance improvements, e.g., minimising loading times or data-access latencies. This issue becomes more pressing when considered in the emerging multi-cloud and edge-cloud-continuum systems, where only specific nodes can access specialised, local resources. To address this problem, we present a declarative language for defining serverless scheduling policies to express constraints on topologies of schedulers and execution nodes. We implement our approach as an extension of the OpenWhisk platform.