A 2021 grounded-theory interview study of 16 microservices migration cases (Ayas, Leitner, and Hebig) produced an initial theory of migration decision-making: three decision-making processes comprising 22 decision-points, each with alternative options, spanning stakeholder engagement and feasibility assessment, technical implementation, and organizational restructuring. The study explicitly presents this as an initial theory and charts which decisions organizations make and which options they choose, without evaluating how the choices made at these decision-points affect migration outcomes. The open problem is to establish, with empirical and ideally quantitative, longitudinal evidence, how selecting among the options at the identified decision-points causally or associatively affects migration outcomes — operationalized by the answering study as measurable constructs of its justified choice (candidate constructs appearing in the source include migration cost and business effectiveness/efficiency) — and to quantify the trade-offs practitioners face. Later literature has extended the qualitative theory, surveyed perceived impact, built practitioner-evaluated decision models, and applied one retrospective cohort design to native microservice versus monolithic projects on velocity, but no study yet measures the relationship between migration decision-point choices and migration outcomes, so the problem remains open.

Background

A monolithic application packages all functionality of a system into a single deployable unit, whereas a microservices architecture decomposes it into small, independently deployable services that communicate over lightweight protocols. Migrating a production monolith to microservices is a long-running, expensive project involving many decisions — not only technical ones (e.g., how to decompose the system or which communication patterns to adopt), but also organizational and business ones (e.g., how to restructure teams or how to justify the investment). Prior research on such migrations concentrated largely on the technical side, for example catalogs of migration patterns distilled from industrial experience (Balalaie et al., 2018) and (semi-)automatic decomposition approaches, while organizational and business decision-making remained comparatively under-studied. To close this gap, Ayas, Leitner, and Hebig (2021) conducted a grounded-theory interview study — grounded theory being a qualitative methodology that builds theory inductively from systematically coded interview data rather than from pre-set hypotheses — covering 16 migration cases with 19 practitioners. Their resulting theory consists of three decision-making processes containing 22 decision-points (specific junctures during a migration at which practitioners must choose among alternative options), covering (a) creating stakeholder engagement and assessing feasibility, (b) technical implementation, and (c) organizational restructuring. The authors present this as an initial theory: they acknowledge that the enumerated decision-points may be incomplete and unrepresentative of all industries, company sizes, and regions, that sampling relied on the researchers' personal networks with a voluntary, opt-in procedure, and that researcher pre-exposure to migration literature may have biased the analysis. The study does not evaluate how the observed choices influenced migration outcomes. In the vocabulary of the field, migration success is discussed in terms of metrics such as migration cost, time-to-value (the elapsed time until the migrated architecture begins delivering the expected benefit), operational stability (e.g., incident frequency, availability, and mean time to recovery after failures), and business effectiveness (whether the architecture increases the delivery of value to customers); in the source itself, business effectiveness and efficiency and cost appear as aspects of pre-migration decision-making rather than as defined post-migration outcome metrics. What is missing is evidence connecting the two: no quantitative, and in particular no longitudinal, study establishes how the choice made at any of the catalogued decision-points relates to migration outcomes. The source names this evaluation among its future-research directions — 'Future research can also target the evaluation of such detailed decision-making processes' — while giving priority to identifying the reasoning behind decisions.

Problem Statement

Determine, with empirical and ideally quantitative, longitudinal evidence, how the choices made at the decision-points of microservices migration projects affect migration outcomes. Concretely: taking the decision-making taxonomy of Ayas, Leitner, and Hebig (2021) — three decision-making processes with 22 decision-points spanning stakeholder engagement and feasibility assessment, technical implementation, and organizational restructuring, each with alternative options — or an explicitly documented extension of that catalogued taxonomy (an extension of the enumerated decision-points, not a replacement or re-derivation of them), establish how the options chosen at the decision-points relate to the outcomes of the migration projects studied. The answer operationalizes migration outcomes as measurable constructs of its own justified choice (candidate constructs that appear in the source include migration cost and business effectiveness/efficiency), relates those outcomes to the options chosen at the decision-points, grounds the analysis in options-chosen and outcome data from real migration projects (retrospectively or prospectively) and documents its sampling and study design. The analysis addresses confounding by organizational context (size, domain, maturity, team capability) and states clearly which claims are causal and which are associational; the answer reports the trade-offs involved, the generalization scope (industries, company sizes, regions), and the limits of the evidence. The relationship is to be established for the catalogued decision-points, or for a documented subset or extension of them that covers all the decision-points of at least one decision-making process, with that coverage stated.

References

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