A framework for microservices synchronization

Iasio, Antonio De; Zimeo, Eugenio

doi:10.1002/spe.2877

Cited by 6 publications

(5 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In these cases, the Domain Metrics approach can be leveraged by engineers to take decisions about possible architectural choices that best fit the expected operational setting. These choices are easy to instantiate and test with recent middleware technologies and deployment infrastructures [26]. In fact, we successfully applied the proposed approach to guide and evaluate the decomposition of a monolithic smart mobility web application towards microservices.…”

Section: Discussionmentioning

confidence: 99%

Domain Metric Driven Decomposition of Data-Intensive Applications

Camilli

Colarusso

Russo

et al. 2020

2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)

Self Cite

View full text Add to dashboard Cite

The microservices architectural style is picking up more and more momentum in IT industry for the development of systems as loosely coupled, collaborating services. Companies that undergo the migration of their own applications have aspirations such as increasing maintainability and the scale of operation. Such a process is worthwhile but not easy, since it should ensure atomic improvements to the overall architecture for each migration step. Furthermore, the systematic evaluation of migration steps becomes cumbersome without sensible optimization metrics that take into account performance and scalability under expected operational conditions. Recent lines of research recognize this task as challenging, especially in data-intensive applications where known approaches based, for instance, on Domain Driven Design may not be adequate. In this paper, we introduce an approach to evaluate a migration in an iterative way and recognize whether it represents an improvement in terms of performance and scalability. The approach leverages a Domain Metric-based analysis to quantitatively evaluate alternative architectures. We exemplified the envisioned approach on a data-intensive application case study in the domain of smart mobility. Preliminary results from our controlled experiments show the effectiveness of our approach to support systematic and automated evaluation of migration processes.

show abstract

Section: Discussionmentioning

confidence: 99%

Domain Metric Driven Decomposition of Data-Intensive Applications

Camilli

Colarusso

Russo

et al. 2020

2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The microservices architectural style 1 promotes the development of applications through the composition of independently deployable units. 2 They are multi-service applications where constituent services are owned and managed by the same authority (tenant). The style and the related agile development approaches improve scalability 3 and maintenance, but a bad placement of the microservices onto the underlying (physical or virtualized) hardware could lead to increased response times and performance degradation due to excessive inter-machine communication.…”

Section: Introductionmentioning

confidence: 99%

“…The microservices architectural style 1 promotes the development of applications through the composition of independently deployable units 2 . They are multi‐service applications where constituent services are owned and managed by the same authority (tenant).…”

Section: Introductionmentioning

confidence: 99%

A distributed tracing pipeline for improving locality awareness of microservices applications

Colarusso,

De Caro,

Falco

et al. 2024

Softw Pract Exp

Self Cite

View full text Add to dashboard Cite

The microservices architectural style aims at improving software maintenance and scalability by decomposing applications into independently deployable components. A common criticism about this style is the risk of increasing response times due to communication, especially with very granular entities. Locality‐aware placement of microservices onto the underlying hardware can contribute to keeping response times low. However, the complex graphs of invocations originating from users' calls largely depend on the specific workload (e.g., the length of an invocation chain could depend on the input parameters). Therefore, many existing approaches are not suitable for modern infrastructures where application components can be dynamically redeployed to take into account user expectations. This paper contributes to overcoming the limitations of static or off‐line techniques by presenting a big data pipeline to dynamically collect tracing data from running applications that are used to identify a given number of microservices groups whose deployment allows keeping low the response times of the most critical operations under a defined workload. The results, obtained in different working conditions and with different infrastructure configurations, are presented and discussed to draw the main considerations about the general problem of defining boundary, granularity, and optimal placement of microservices on the underlying execution environment. In particular, they show that knowing how a specific workload impacts the constituent microservices of an application, helps achieve better performance, by effectively lowering response time (e.g., up to a reduction), through the exploitation of locality‐driven clustering strategies for deploying groups of services.

show abstract

“…The proposed patterns are related to migration of monolithic applications to microservices. De Iasio and Zimeo 24 proposed a framework to support synchronization among microservices to avoid unavailability of dependent microservices to achieve the goal of the application. Freire et al 25 proposed an approach for migration of monolithic applications to microservices using aspect oriented programming.…”

Section: Introductionmentioning

confidence: 99%

A service graph based extraction of microservices from monolith services of service‐oriented architecture

Raj

Sadam

2022

Softw Pract Exp

View full text Add to dashboard Cite

Service-oriented architecture (SOA) has been widely used to design enterprise applications in the past two decades. The services in SOA are becoming complex with the increase in changing user requirements and SOA is still seen as monolithic from a deployment perspective. Monolithic services make the application complex, and it becomes difficult to maintain. With the evolution of microservices architecture, software architects started migrating legacy applications to microservices. However, existing migration approaches in the literature mostly focus on migrating monolithic applications to microservices. To the best of our knowledge, very few works have been done in migrating SOA applications to microservices. One of the major challenges in the migration process is the extraction of microservices from the existing legacy applications. To address this, we propose an approach to extract the candidate microservices using graph based algorithms. In particular, four algorithms are defined: (i) construction of service graph (SG), (ii) construction of task graph (TG) for each service of the a SOA application, (iii) extraction of candidate microservices using the SG of SOA application, and (iv) construction of a SG for a microservices application to retain the dependencies between the generated microservices. We chose a SOA-based web application to demonstrate the proposed microservices extraction approach and extracted the microservices. Additionally, we have evaluated the extracted microservices and compared them with SOA based services.

show abstract

A framework for microservices synchronization

Cited by 6 publications

References 18 publications

Domain Metric Driven Decomposition of Data-Intensive Applications

Domain Metric Driven Decomposition of Data-Intensive Applications

A distributed tracing pipeline for improving locality awareness of microservices applications

A service graph based extraction of microservices from monolith services of service‐oriented architecture

Contact Info

Product

Resources

About