Improving interoperability in distributed multi-tier software stacks

Distributed multi-tier software stacks organise and deploy software components as a hierarchy of interacting tiers. The components are typically heterogeneous, i.e. each component may be written in a different language and may interoperate using a variety of protocols. Tiered software is modular but leads to a range of interoperability challenges including the following. (1) Interoperating components in multiple languages and paradigms increases developer cognitive load since they must simultaneously reason in multiple languages and paradigms. (2) There must be correct interoperation of components, e.g. adherence to the API or communication protocols between components. (3) Interoperation between different components can lead to diverse modes of failure as each component can fail in unique ways. Many of these challenges are the result of contributing factors like tight coupling or polyglot programmming. This thesis investigates techniques to improve heterogeneous interoperability in distributed multi-tier software stacks. Some common approaches include microservices and tierless languages. Microservices are perceived to offer better reliability than components in multi-tier software stacks through the loose coupling of services. The reliability of microservices is investigated by combining the established properties of dependence and state with reliability. This defines a new three-dimensional space: the Microservices Dependency State Reliability (MDSR) classification with six classes. The feasibility of statically identifying MDSR classes is demonstrated with a prototype analyser that identifies all six classes in Flask microservices web applications. The reliability implications of the different MDSR classes are evaluated by running three case study applications (Hipster-Shop, JPyL & WordPress) against a fault injector. Key results are as follows. (1) All applications fail catastrophically if a critical microservice fails. (2) Applications survive the failure of individual minor microservice(s). (3) The failure of any chain of microservices in JPyL & Hipster is catastrophic. (4) Individual microservices do not necessarily have minor reliability implications. In a tierless language, the compiler generates the code for each component and ensures their correct interoperation. They are mainly used to implement web stacks. However, their use in implementing IoT stacks is less common. This investigation compares interoperation in tiered and tierless IoT stacks through the systematic evaluation of four implementations of the prototype UoG smart campus IoT system: two tierless and two Python-based tiered. Key results of the study are as follows. (1) Tierless languages have the potential to significantly reduce the development effort for IoT systems, requiring 70% less code than the tiered implementations. (2) Tierless languages have the potential to significantly improve the reliability of IoT systems. (3) The first comparison of a tierless codebase for resource-rich sensor nodes and one for resourceconstrained sensor nodes shows that they have very similar functional structure and code sizes - within 7%. Tier elimination is a technique that removes a tier/component by integrating two tiers. Specifically, this thesis investigates the implications of eliminating the Apache web server in a 4-tier web stack: Jupyter Notebook, Apache, Python, Linux (JAPyL) and replacing it with PHP libraries in the frontend webpage to get the 3-tier (JPL). The study reveals the following. (1) The JPL 3-tier web stack requires that the developer uses fewer programming languages and paradigms than JAPyL, i.e two compared with four languages and two compared with three paradigms. (2) JPL requires 42% less code than JAPyL. (3) In JPL, some of the functionalities can be automated due to the decreased abstraction levels at the upper layers of the stack. (4) However, the latency in JPL is two to three times greater than that of JAPyL. So while tier elimination reduces developer effort and semantic friction the tradeoffs are high performance overhead & resource consumption and increasing code complexity

Could tierless languages reduce IoT development grief?

Internet of Things (IoT) software is notoriously complex, conventionally comprising multiple tiers. Traditionally an IoT developer must use multiple programming languages and ensure that the components interoperate correctly. A novel alternative is to use a single tierless language with a compiler that generates the code for each component and ensures their correct interoperation. We report a systematic comparative evaluation of two tierless language technologies for IoT stacks: one for resource-rich sensor nodes (Clean with iTask), and one for resource-constrained sensor nodes (Clean with iTask and mTask). The evaluation is based on four implementations of a typical smart campus application: two tierless and two Python-based tiered. (1) We show that tierless languages have the potential to significantly reduce the development effort for IoT systems, requiring 70% less code than the tiered implementations. Careful analysis attributes this code reduction to reduced interoperation (e.g. two embedded domain-specific languages (DSLs) and one paradigm versus seven languages and two paradigms), automatically generated distributed communication, and powerful IoT programming abstractions. (2) We show that tierless languages have the potential to significantly improve the reliability of IoT systems, describing how Clean iTask/mTask maintains type safety, provides higher order failure management, and simplifies maintainability. (3) We report the first comparison of a tierless IoT codebase for resource-rich sensor nodes with one for resource-constrained sensor nodes. The comparison shows that they have similar code size (within 7%), and functional structure. (4) We present the first comparison of two tierless IoT languages, one for resource-rich sensor nodes, and the other for resource-constrained sensor nodes

Classifying the Reliability of the Microservice Architectures

Microservices are popular for web applications as they offer better scalability and reliability than monolithic architectures. Reliability is improved by loose coupling between individual microservices. However in production systems some microservices are tightly coupled, or chained together. We classify the reliability of microservices: if a minor microservice fails then the application continues to operate; if a critical microservice fails, the entire application fails. Combining reliability (minor/critical) with the established classifications of dependence (individual/chained) and state (stateful/stateless) defines a new three dimensional space: the Microservices Dependency State Reliability (MDSR) classification. Using three web application case studies (Hipster-Shop, Jupyter and WordPress) we identify microservice instances that exemplify the six points in MDSR. We present a prototype static analyser that can identify all six classes in Flask web applications, and apply it to s even applications. We explore case study examples that exhibit either a known reliability pattern or a bad smell. We show that our prototype static analyser can identify three of six patterns/bad smells in Flask web applications. Hence MDSR provides a structured classification of microservice software with the potential to improve reliability. Finally, we evaluate the reliability implications of the different MDSR classes by running the case study applications against a fault injector