DOCKER-BASED MONOLITHIC AND MICROSERVICES ARCHITECTURE PERFORMANCE COMPARISON

In this paper the information technologies stack is presented. Thesetechnologies are used during network architecture deployment. The analysis of technological advantages and drawbacks under investigation for monolithic and network architectures will be useful during of cyber security analysis in telecom networks. The analysis of the main numeric characteristics was carried out with the aid of Kubectl. The results of a series of numerical experiments on the evaluation of the response speed to requests and the fault tolerance are presented. The characteristics of the of monolithic and microservice-based architectures scalability are under investigation. For the time series sets, which characterize the network server load, the value of the Hurst exponent was calculated.
 The research main goal is the monolithic and microservice architecture main characteristics analysis, time series data from the network server accruing, and their statistical analysis.
 The methodology of Kubernetes clusters deploying using Minikube, Kubectl, Docker has been used. Application deploy on AWS ECS virtual machine with monolithic architecture and on the Kubernetes cluster (AWS EKS) were conducted.
 The investigation results gives us the confirmation, that the microservices architecture would be more fault tolerance and flexible in comparison with the monolithic architecture. Time series fractal analysis on the server equipment load showed the presence of long-term dependency, so that we can treat the traffic implementation as a self-similar process.
 The scientific novelty of the article lies in the application of fractal analysis to real time series: use of the kernel in user space, kernel latency, RAM usage, caching of RAM collected over 6 months with a step of 10 seconds, establishing a long-term dependence of time series data.
 The practical significance of the research is methodology creation of the monolithic and microservice architectures deployment and exploitation, as well as the use of time series fractal analysis for the network equipment load exploration.

As the entrance of the computer systems, the API gateway is an indispensable part of the microservice architecture. To realize the load balancing of API gateway, this paper studies the load balancing algorithm of the API gateway based on the microservice architecture. In doing this, we analyze the microservice architecture level from the data layer, the basic layer, and other levels, take the container cloud as the carrier of the microservice architecture, combine it with the client and API gateway, and design the API gateway based on the microservice architecture. We then judge whether the microservice identifier in the request source of the API gateway client is included in the API gateway routing table and determine the service cluster to which the microservice belongs according to the microservice identifier. After retrieving the qualified backend microservice container list according to the service cluster information, it adopts a load balancing algorithm based on dynamic weight, takes central processing unit (CPU) utilization and memory utilization as parameters to evaluate the resource load of microservers, uses an extreme gradient lifting model to predict CPU utilization and memory utilization, calculates the weight of microservers based on the prediction results, selects the microserver with the highest weight value to make API gateway service requests, and initiates API gateway service calls to specific backend microservice containers, thereby completing the load balancing of the API gateway. The experimental results show that the average load balancing degree of the algorithm is about 95 %, the average network resource utilization rate is as high as 89 %, and the algorithm execution time is short.

The previous chapter introduces the concept of Enterprise Internet of things with the help of sample applications. This chapter introduces the architectural concerns of Enterprise Internet of Things. The chapter starts with a reference architecture of Enterprise Internet of Things where all the components of an end to end IoT solution is explained. The critical component in the architecture is the middleware solution. The middleware component enables communication across the disparate hardware and software components in the solution. Enterprise IoT solutions are more complicated to develop and maintain due to the participation of several vendors. The interoperability challenges are handled with the help of middleware solutions and this chapter addresses two important architectures namely Monolithic architecture and Microservices architecture. These architectures are not specific to IoT solutions but generic for Enterprise software development. This chapter illustrates how the Microservices architecture is the most suitable choice for designing Enterprise IoT applications. In the last part, there is a detailed discussion on the trade-off between Monolithic and Micro services architectures.

Microservice architecture reduces the coupling between application modules, which is conducive to the development, deployment and operation and maintenance of complex application systems. However, compared with the monolithic architecture, the access control of its resources becomes more complex. Based on the application scenario of enterprise system micro service architecture, aiming at the high security requirements of business system, through the analysis and research of micro service architecture, this paper designs a set of access control solution, which can meet the requirements of unified authentication, improving the efficiency of authority verification and accelerating the system development speed under the microservice architecture, which has reference for enterprise application system design significance.

Software architecture is a set of important decisions about the organization of the software system. The success and speed of the project development, the complexity of its support and understanding of the program structure depends on the correct choice of software architecture. For this reason, developers often use new architectural solutions to build software, trying to find the best solutions to a problem. The common practice of program development was the development on the principle of monolithic architecture, which envisages the project as a single program, which is responsible for all necessary functionality. Of course, this approach had its advantages, such as ease of development, testing and deploying. But with project`s growth, the monolithic architecture begins to make some flaws in the development process: the addition of a certain new functionality is accompanied by an increase in the code base, observance of limits of responsibility of internal modules is blurred, compiling and deploying takes much more time. Given the drawbacks of monolithic architecture above, developers have begun to take other approaches. One is microservice architecture. Microservice Architecture – A variant of service architecture (modular software development approach) software, focused on the interaction of as small as possible, loosely coupled and easily replaceable modules – microservices [1]. With such an architecture, the project is a set of small services, the communication between which is done through lightweight mechanisms (for example, HTTP, which can be used in REST architectural style to get an increased productivity and simplified architecture) [2]. Each of these services must fulfil its clearly defined business task. This architecture has the following advantages: better scaling, independent module development and deploying, better reusability etc.

The traditional online teaching adopts the single architecture to develop and implement the system, which facilitates the data sharing and testing of the system. However, due to the increasing complexity of the system's business functions, the system based on monolithic architecture has become increasingly complex, its scalability has deteriorated, and its concurrency performance has decreased. Based on these problems, this paper puts forward combining microservice architecture and online teaching platform, using microservice architecture independent deployment, concurrent performance characteristics such as high technology selection and flexible, the complex business function is divided into several small service module, solve the challenges faced by the traditional system, at the same time improve the efficiency of the use of online teaching platform and students' learning autonomy, The system function design, architecture design, safety design and so on are expounded to build an efficient and perfect online teaching platform.

A multitenant SaaS is a single codebase and run-time customizable application supporting multiple tenants and users. There is a huge demand for multitenant applications as it reduces total cost of ownership for both, service provider as well as consumers. However, Multitenant SaaS applications face fluctuating load problem due to variable tenants and users. Thus, managing resources becomes difficult. Traditionally, to overcome this issue, resources are managed and scaled using monolithic architecture which may lead to underutilization and over utilization of resources in cases of low load and high load respectively. Microservices architecture is a new exemplar for developing cloud SaaS applications as it has several advantages over monolithic. The paper aims to analyze the performance and scalability analysis of multitenant SaaS application using both microservices and monolithic architecture. Utility Booking application is developed for a case study. Scalability analysis is performed, and the performance of application using both approaches is compared using average response time and throughput. Results show that multitenant applications using microservices with large number of concurrent users outperforms monolithic approach and are resource efficient as microservice application scales dynamically based on varying load.

The article examines the critical role of cloud-native API gateways in ensuring resilience within microservices architectures. Drawing from comprehensive studies across 145 organizations and analysis of 892 software practitioners, the article demonstrates how microservices adoption has transformed modern application development, with adoption rates reaching 89% in financial services, 76% in retail, and 71% in healthcare sectors. It presents empirical evidence of significant improvements, including a 71% decrease in deployment time and 68% reduction in system downtime compared to monolithic architectures. Through analysis of production environments spanning 178 organizations, the article reveals that API gateways achieve 99.95% service availability and can handle up to 250,000 requests per second during peak loads. The article explores advanced features including circuit breaking patterns, which reduce cascading failures by 83.5%, and intelligent load balancing strategies that improve resource utilization by 88%. Additionally, it examines the business impact through metrics demonstrating substantial improvements in system uptime, incident response times, and infrastructure costs.

Motivation. Microservices architecture has become more prevalent in cloud-based applications where small, looselycoupled service components work together to handle user requests [1]. This architecture differs greatly from traditional monolithic deployments and provides advantages such as agile resource management, better fault tolerance, and platform compatibility [2, 3]. The figure 1 shows the difference between monolithic and microservice architecture. However, microservices come with their own set of challenges, particularly in the area of resource management. Resource management for microservices-based applications is more challenging than for monolithic applications due to the larger configuration space and complex communication topology [4, 5]. Additionally, existing resource management techniques for monolithic applications must manage microservices effectively. The resource management challenges for microservices must be addressed as more production cloud services adopt this architecture [6, 7].

With the development of cloud computing and container virtualization, the microservice architecture has received more and more attention. While microservices bring many benefits, they also bring some challenges. A user’s request may require multiple microservices to collaborate, and chained invocations between microservices result in higher latency than a monolithic architecture. In this paper, we propose a dynamic priority based weighted scheduling algorithm for the problem that the latency of chained-service requests is too long in the case of high concurrency. Experiments show that the algorithm can reduce the latency of chained-service requests effectively in the case of little impact on the latency of leaf-service requests.

Reading and analyzing data from sensors are crucial in many areas of life. IoT concepts and related issues are becoming more and more popular, but before we can process data and draw conclusions, we need to think about how to design an application. The most popular solutions today are microservices and monolithic architecture. In addition to this choice, there is also the question of the technology in which you will work. There are more and more of them on the market and in each of them it is practically possible to achieve similar results, but the difference lies in how quickly it will be possible and whether the approach invented will turn out to be the most optimal. Making the right decisions at the beginning of application development can determine its path to success or failure. The main goal of this article was to compare technologies used in applications based on microservice architecture. The preparation of a book lending system, whose server part was implemented in three different versions, each using a different type of technology, helped to achieve this goal. The compared solutions were: Spring Boot, Micronaut and Quarkus. The reason for this research was to investigate projects using sensor networks, ranging from telemedicine applications to extensive sensor networks collecting scientific data, or working in an environment with limited resources, e.g., with BLE or WIFI transmitters, where it is critical to supply energy to these transmitters. Therefore, the issue of efficiency and hence energy savings may be a key issue depending on the selected programming technology.

The paper proposes the method of building the electric power marketing business application system based on the cloud computing and microservices architecture technologies to solve the issues of the current system with the concentrated infrastructure and the monolithic architecture which are difficult to support the business processing in very large scale and the evolution of the electric power marketing business. The paper first introduces the current electric power marketing business application system and highlights its main drawbacks. Then it proposes the method to build the innovative electric power marketing business application system with the main technical characteristics as follows: the IaaS part of the application system has the distributed infrastructures with the IT resource elastic management and powerful horizontal scalability brought by the cloud computing technology; its PaaS part is the service platform with the components of the data processing, information integration, application building, and cloud service center to provide the several cloud services, such as one-click deployment, flexible scaling, fault self-healing, gray distribution, full-link monitoring and other cloud service capabilities; and its SaaS part has the microservices architecture with the features of servitization, componentization, decentralization, independent deployment etc. Finally, the suggestions are given to design the microservices for the electric power marketing business application.

Web systems have existed for a long time and quite a lot of them have been created. Modern development uses new microservice architectural to improve performance, portability, and other important characteristics. This necessitates the transformation of legacy systems from a monolithic architecture to a microservices one. Such a process is complex and costly, so improving the methods for converting old systems to a new platform is relevant. This research aims to develop a method of applying microfrontends approach for monolithic single page applications (SPA). The article proposes a method of transforming the software system architecture from monolithic to microservice architecture (MSA). Since the client part of the system is considered, the term microfrontend is proposed, as an analog of microservers in the server part of the software systems. A brief review of existing architecture reengineering research is made and the advantages of a microservice approach are identified. The proposed three-stage method differs from the methods by the selection of an additional stage of conversion, which allows to gently change the connections between parts of the monolithic application, which were implemented in the initial monolithic architecture. The first stage is reverse engineering, it is proposed to shift the focus from the search for outdated code to the functional analysis of the program as such. The second stage, a transition to a modular architecture with the allocation of functionality into separate modules is proposed. At the end of the third stage, we have several separate programs (microinterfaces) that are connected to the main program. An experiment with a typical external SPA demonstrates the operation of the proposed algorithm. The system obtained as a result of the transformation is compared with the original one according to the following measurable parameters: production builds building time, size of the main bundle, and first page average load time. All comparisons showed the advantages of the system obtained as a result of the conversion. As a result, the architecture transformation algorithm allows you to obtain a guaranteed better result, taking into account the limitations of the interface SPA, which were not considered by the authors of previous articles.

As organizations increasingly seek to enhance their software systems' scalability, flexibility, and maintainability, the transition from monolithic architectures to microservice architectures has gained significant attention. This paper investigates the challenges and lessons learned from decoupling monolithic systems into microservices, focusing on practical case studies and established best practices. The research begins by examining the limitations of traditional monolithic architectures, including issues related to deployment speed, codebase complexity, and scalability constraints. Monolithic systems often lead to increased development time and difficulty in accommodating changes, which hinders an organization's agility. In response to these challenges, many organizations have begun to adopt microservices, which break down applications into smaller, independently deployable services.

The growing interest in the Internet of Things (IoT) has prompted a more innovative architectural design approach and evolutionary frameworks to integrate heterogeneous IoT devices better. Edge computing, which provides services close to end-user devices without requiring high-speed Internet connectivity, has become a popular paradigm for reducing network congestion and allowing real-time Internet of Things applications. However, the heterogeneous and resource-constrained edge nodes make it difficult to design edge computing frameworks. However, because the edge computing environment is dynamic, with irregular connections and limited bandwidth, it's critical to deal with the challenge of determining the relative performance of applications deployed in the edge computing paradigm when input traffic, networking protocols, or system software changes. So, this paper explores three software architectures, namely monolithic architecture, microservices architecture (MSA), and service-oriented architecture (SOA), providing a framework for edge computing's many requirements. A comparative analysis of these three software architectures is also covered based on the fundamental characteristics of an edge computing framework.