=Paper=
{{Paper
|id=Vol-2339/paper7
|storemode=property
|title=Model-driven Software Migration Towards Finegrained Cloud Architectures (short paper)
|pdfUrl=https://ceur-ws.org/Vol-2339/paper7.pdf
|volume=Vol-2339
|authors=Robin Lichtenthäler
|dblpUrl=https://dblp.org/rec/conf/zeus/Lichtenthaler19
}}
==Model-driven Software Migration Towards Finegrained Cloud Architectures (short paper)==
https://ceur-ws.org/Vol-2339/paper7.pdf
Model-driven software migration towards
fine-grained cloud architectures
Robin Lichtenthäler
Distributed Systems Group, University of Bamberg, Germany
robin.lichtenthaeler@uni-bamberg.de
Abstract. Observing the trend towards building cloud-native applica-
tions, there is also demand for migrating existing system to the fine-
grained architectures of cloud-native applications. To support such mi-
gration efforts, this position paper proposes a model-driven approach to
enable a structured and reproducible migration.
Keywords: model-driven, migration, cloud-native, position paper
1 Introduction: Towards fine-grained cloud architectures
Today’s software is more and more composed of fine-grained components which
are combined to build more complex applications. This trend started with the rise
of Service-Oriented Architectures (SOA) [9] superseding monolithic architectures.
SOA aims towards independently developable and deployable components with
a bounded business functionality. The trend towards fine-grained components
with a bounded business functionality has in recent years manifested itself in
the microservices architectural style [3] which can be seen as an evolution of
SOA. The microservices architectural style in turn combined with the increasing
popularity of cloud computing plus the softwareization of infrastructure lead to the
emergence of so-called Cloud-Native Applications (CNA). In this paper the CNA
definition by Kratzke and Quint [6] is adopted: "A CNA is a distributed, elastic
and horizontal scalable system composed of (micro)services [..]. The application
and each self-contained deployment unit of that application is designed according
to cloud-focused design patterns and operated on a self-service elastic platform."
Fine-grained architectures are an inherent characteristic of CNAs, because they
enable the exploitation of the benefits offered by cloud computing. In this context,
the latest effort towards even finer-grained components is the Function as a
Service (FaaS) paradigm [1] where the deployment unit is a single function
deployed to an elastic FaaS platform which inherently enables scalability and
abstracts from operational concerns.
Building CNAs is the aim of many new software projects, but also of migration
projects where an existing system should be transformed to a CNA. A key
aspect of such a migration is the architectural transformation to the fine-grained
architecture of a CNA which typically means decomposing the existing system.
S. Kolb, C. Sturm (Eds.): 11th ZEUS Workshop, ZEUS 2019, Bayreuth, Germany, 14-15
February 2019, published at http://ceur-ws.org/Vol-2339
36 Robin Lichtenthäler
However, such a decomposition is difficult and rarely supported by structured
approaches or tools. Therefore, it would be beneficial to explore possible structured
approaches for the transformation of existing software systems to the fine-grained
cloud architecture of CNAs to support software engineers engaged in such projects.
This support will remain valuable in the future, because even today it argued
that it is a reasonable procedure to start off with a monolithic architecture [8].
A monolithic architecture can then be gradually transformed to a fine-grained
cloud architecture, when complexity grows and demand increases.
A promising field of research in this regard is Model-Driven Engineering (MDE)
[5]. In MDE, models are considered as a key resource for software development
and evolution. For architecture transformations, models can help to focus on
the key aspects of the software architecture and enable a structured and tool-
supported transformation. Although reducing the migration to a fine-grained
cloud architecture to a model-based transformation seems promising, a key
challenge in MDE is the alignment between the actual code and the model. The
transition from code to a model and vice versa should be automated to a large
extent, since manual steps in a MDE-based approach would cause an overhead
and hinder reproducibility.
To explore the applicability of MDE for the migration of existing software
towards fine-grained cloud architectures, the following research questions are
investigated:
– Which model or collection of models can be used to represent an existing
software architecture and a fine-grained cloud architecture?
– What are rules and patterns for the transformation to a fine-grained cloud
architecture and how can they be applied to the identified model or collection
of models?
– How can the generation of models from code, the model-to-model transfor-
mation, and the generation of code from models be effectively supported by
tools?
2 Related Work
Various research directions can be identified covering different aspects of the
proposed research questions. Regarding modeling languages for the cloud, the
available languages [2] focus on the required cloud resources and their configura-
tions, but not on the complete software architecture, i.e. the relations between
the components and how they interact. These languages can be incorporated
when a migrated application should be deployed to different cloud providers,
but for the proposed MDE approach there is no suitable modeling language
yet. Considering MDE-based approaches for software migration, a noteworthy
and comprehensive research project was the ARTIST-project [7] which had the
goal of providing a complete methodology and corresponding tools for migrating
legacy applications to the cloud. While MDE was already used in this project,
their focus was more on the general migration from on-premises deployments to
Model-driven software migration towards fine-grained cloud architectures 37
cloud deployments without a substantial software architecture transformation.
Furthermore, FaaS offerings enabling fine-grained architectures were not yet
available at the time of the project and were not considered. Regarding research
on the software architecture transformation, i.e., how to split an existing system
into smaller components, only some approaches have been proposed, for example
by Gysel et al. [4]. However, the existing approaches do not explicitly employ
MDE. Furthermore, the existing approaches are based on exemplary use cases
and need to be evaluated regarding their validity and general applicability.
3 The model-driven approach
In order to answer the given research questions, this position paper proposes
a model-driven migration of existing software systems to fine-grained cloud
architectures. The basic idea is that a model can be generated representing the
existing system. This model can then be (semi-)automatically transformed to a
model of a fine-grained cloud architecture. Finally, artifacts can be generated from
the transformed model to facilitate the implementation of the new architecture.
Because implementing this approach as a whole is ambitious, it should be
separated into different concerns, as represented by the corresponding research
questions. First, a modeling language or collection of languages needs to be defined.
It should enable the modeling of an existing application, the identification of
possibilities for deriving fine-grained components, as well as representing the
resulting fine-grained cloud architecture. Therefore, a key challenge for the
modeling language is to find the right level of abstraction. Next, rules and
patterns for splitting an application into more fine-grained components should be
defined and represented in model transformation rules. Finally, because tools are
seen as a key part of MDE, tools should be provided for creating a model from
code, transforming the model and generating artifacts for the new architecture.
The approach focuses on the actual execution of a migration. However, it
should be noted that before the actual execution, a careful analysis of the
necessity and usefulness of a migration should be conducted. Not every existing
application should be transformed to a CNA and evaluating the applicability of
a transformation is another important research question. Sometimes also hybrid
applications are sensible where only parts of the existing system are migrated to
be cloud-native. The approach could provide additional insights for this question
as well, but to keep the approach focused, it is assumed that a prior evaluation
has been done.
That said, there are several further challenges which need to be taken into
account. There exists a large technological heterogeneity for existing applications
and especially cloud-native applications. The aim for this approach would be to
make the models for the existing system and the fine-grained cloud architecture
as generic as possible. Technological differences are then addressed inside the
steps for generating a model from code and generating artifacts, e.g., through
profiles. Furthermore, when thinking about possibilities to split an application
into smaller components, a purely technical view might suggest several different
38 Robin Lichtenthäler
possibilities with potentially conflicting outcomes. In such cases the business
view rather than the technical view is crucial to make reasonable decisions. The
approach could therefore be semi-automatic and suggest different options during
the model transformation phase which could then be decided upon using business
knowledge.
As a starting point, an exemplary application is manually transformed. During
the manual transformation, requirements for the modeling language and first
transformation rules can be identified. For this exemplary application a specific
technological stack needs to be chosen. The differences with regard to other
technological possibilities, are considered afterwards. Further applications or
successful migration projects are then considered to iteratively evaluate and
improve the approach.
In conclusion, transforming applications into fine-grained CNAs is an ongoing
challenge for developers. Providing support for this task through structured
approaches and tooling would therefore be beneficial to developers and to research
on CNAs as a whole.
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