home Anil Madhavapeddy, Professor of Planetary Computing  

Programming Unikernels in the Large via Functor Driven Development

Gabriel Radanne, Thomas Gazagnaire, Anil Madhavapeddy, Jeremy Yallop, Richard Mortier, Hannes Mehnert, Mindy Preston and Dave Scott.

Working paper at arXiv.

URL (arxiv.org)   DOI   BIB

Compiling applications as unikernels allows them to be tailored to diverse execution environments. Dependency on a monolithic operating system is replaced with linkage against libraries that provide specific services. Doing so in practice has revealed a major barrier: managing the configuration matrix across heterogenous execution targets. A realistic unikernel application depends on hundreds of libraries, each of which may place different demands on the different target execution platforms (e.g.,\textasciitildecryptographic acceleration). We propose a modular approach to structuring large scale codebases that cleanly separates configuration, application and operating system logic. Our implementation is built on the \textbackslashmirage unikernel framework, using the \textbackslashocaml language's powerful abstraction and metaprogramming facilities. Leveraging modules allows us to build many components independently, with only loose coupling through a set of standardised signatures. Components can be parameterized by other components and composed. Our approach accounts for state, dependency ordering, and error management, and our usage over the years has demonstrated significant efficiency benefits by leveraging compiler features such as global link-time optimisation during the configuration process. We describe our application architecture and experiences via some practical applications of our approach, and discuss how library development in \textbackslashmirage can facilitate adoption in other unikernel frameworks and programming languages.

# 1st May 2019   iconpapers mirageos ocaml preprint unikernels

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