EP3785128A2 - Système et procédé de création de recommandations de microservice de division et de fusion - Google Patents

Système et procédé de création de recommandations de microservice de division et de fusion

Info

Publication number
EP3785128A2
EP3785128A2 EP19792327.9A EP19792327A EP3785128A2 EP 3785128 A2 EP3785128 A2 EP 3785128A2 EP 19792327 A EP19792327 A EP 19792327A EP 3785128 A2 EP3785128 A2 EP 3785128A2
Authority
EP
European Patent Office
Prior art keywords
microservice
unit
data
splitting
merging
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP19792327.9A
Other languages
German (de)
English (en)
Inventor
Haci Mehmet Yildirim KOCDAG
Ahmet Faruk BISKINLER
Mucahit AKYOL
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Borsa Istanbul AS
Original Assignee
Borsa Istanbul AS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Borsa Istanbul AS filed Critical Borsa Istanbul AS
Publication of EP3785128A2 publication Critical patent/EP3785128A2/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment

Definitions

  • the present invention relates to a system for observing microservices in systems running by microservice architecture by taking into consideration various parameters, and for creating recommendations intended for splitting or merging microservices accordingly.
  • Microservice architecture -use of which becomes widespread increasingly today- consists of microservices which are atomic services with development processes, dependencies, sizes as small as possible. Big works are divided into small parts, load distribution is made and it is ensured that the system keeps up while transitions are being performed in systems having critical importance by means of microservices. Transactions of merging a microservice with other microservices or splitting it into several microservices is carried out by taking into consideration factors such as network security, risk management, user/role appraisal, performance, dependencies, resource consumption, the network being used, technologies being used, frequency of deployment, business model, function and rules, frequency of use, software standards, intra-team dynamics writing the application, usage calendar. However, it is required to review the microservice design after any update, modification or maintenance.
  • test data can be stored in a server and/or sent to a data analysis server.
  • the data analysis server analyses the test data and creates recommendations for splitting or merging microservices.
  • the data analysis server can be located on the server as a module, on another server or it can be an independent server. Microservices are analysed by looking at their independent functionalities and functional responsibilities, in order to determine whether they should be split or merged.
  • the data analysis server determines that microservice performs functions A and B and creates a recommendation for splitting the microservice into two for function A and function B. Similarly, the data analysis server determines that microservices A and B perform the same X function and creates a recommendation for merging microservice B with microservice A.
  • An objective of the present invention is to realize a system for creating recommendations intended for splitting or merging microservices by carrying out analysis on various data about current microsystems in systems running by microservice architecture.
  • Another objective of the present invention is to realize a system for creating simulation scenarios and ensuring that these scenarios are used for creating recommendation intended for splitting or merging microservices.
  • Figure 1 is a schematic view of the inventive system.
  • FIG. 2 is a flowchart of the inventive method.
  • the system (1) for creating recommendation of splitting and merging microservice comprises:
  • microservice monitoring unit (2) which is configured such that it will make observation on current microservices by connecting to the microservice servers (MSS);
  • At least one data storage unit (3) which is in communication with the microservice monitoring unit (2) and stores the data about the microservices; at least one data processing unit (4) which enables to carry out various analyses on the stored data;
  • At least one simulation unit (5) which is configured such that it will determine simulation will be used for recommendation of splitting and merging microservice, and will create the related recommendation when it is decided to use simulation;
  • At least one recommendation unit (6) which is in communication with the data processing unit (4) and the simulation unit (5) and creates recommendations intended for splitting the monitored microservice into several microservice or merging them with other microservices;
  • the microservice monitoring unit (2) included in the inventive system (1) is a unit which enables to monitor each microservice.
  • the data storage unit (3) included in the inventive system (1) is in communication with the microservice monitoring unit (2) and it instantly stores the data about the microservices monitored by the microservice monitoring unit (2) by connecting to the microservice servers (MSS).
  • the data stored in the data storage unit (3) may be data such as whether the service is reliable or not, the resource consumed (use of RAM-random access memory and CPU-central processing unit), size of data carried on network, frequency of call, number of call, from which subnetwork it is called and in which subnetwork it is located, error logs, database servers being connected to, microservices called in itself, ports opened, service performance, service technology, service dependencies, deployment frequency, which team do developments belong to, complexity of the service written, user and role authority, call calendar, response time of function on service, call number of function on service.
  • the data processing unit (4) included in the inventive system (1) is in communication with the data storage unit (3) and clears the data not to be used among the data stored in the data storage unit (3). Then, it enables to extract interrelation of data by using various data decomposition and classification methods on the data cleared.
  • the data decomposition and classification methods used can be methods such as a decision tree method which is a classification method wherein a tree structure is created to make a decision and probabilities are placed to the leaves of the tree; k-nearest neighbor method which is a classification method wherein proximity of a data -that is requested to be classified- to previous data -which have been placed to a coordinate system- is looked; logistic regression method which is a classification method wherein artificial neural networks, logistics models are created and which is used for probability calculations to estimate dependent variable values; ZeroR algorithm which places a new data to a class having the maximum data among the classes in the data set; OneR algorithm which is a more advanced than ZeroR algorithm and makes classification by creating frequency tables for classes; naive bayesian classification algorithm which is a method wherein test data are classified according to previously obtained probability values; C4.5 algorithm which is a decision tree method performing normalization; ID3 algorithm which divides the data in the decision tree into two parts in the largest way; C4.5 algorithm which is an advanced version of C4.5 algorithm and used by
  • the simulation unit (5) included in the inventive system (1) is a unit which determines whether real data or a simulation structure will be used before a recommendation of splitting and merging microservice is created.
  • the simulation unit (5) determines microservice features over a current system in the event of deciding that real data will be used.
  • the simulation unit (5) creates a system simulation in the event of deciding that a simulation will be used for creating recommendation of splitting and merging microservice.
  • results can be obtained such as microservices that should be merged or split in network density changes, change that will occur in use of processor when the microservices are merged, change that will occur in log amounts when the microservices are merged, difference that will occur in response time of microservice in the event that the microservice functions merge or split.
  • the recommendation unit (6) included in the inventive system (1) is in communication with the data processing unit (4) and the simulation unit (5). It creates recommendations of splitting and merging microservice on the basis of the information that it receives from the data processing unit (4) and the simulation unit (5).
  • the recommendation unit (6) takes into consideration factors such as network security, risk management, user/role appraisal, performance, dependencies, resource consumption, the network being used, technologies being used, frequency of deployment, business model, function and rules, frequency of use, software standards, intra-team dynamics writing the application, usage calendar while it creates recommendation.
  • the reporting unit (7) included in the inventive system (1) creates a report in the event that a microservice does not have authority for split or merging autonomously.
  • user information and the related microservice comprise two different functions; namely, login and password control.
  • the login function is used very often and the function used for reporting may slow down the microservice and causes to receiving late reply upon being used at certain intervals. It may be enabled to split the service by considering the frequency of call of functions of services and the times for responding a call.
  • the requested microservices are made high security microservices by interlaying security layers.
  • Splitting and merging transaction is carried out in the related server by considering the security layer upon looking at the subnetwork wherein they are located.
  • the inventive method (100) creating recommendation of splitting and merging microservice comprises steps of:
  • microservice monitoring unit (2) saving the data about the microservices that it receives instantly by connecting to the microservice servers (MSS), to the data storage unit (3) (102),
  • the data processing unit parsing the data recorded in the data storage unit (3) and classifying them by using classification methods (103),
  • the simulation unit (5) determining whether real data or a system simulation will be used or not and creating the simulation in the event that a system simulation is used (104),
  • the recommendation unit (6) creating recommendation of splitting and merging microservice by receiving information about the microservice from the data processing unit (4) and the simulation unit (5) (105),
  • the data processing unit (4) giving splitting or merging instruction to the microservice servers (MSS) (106), in the event that the microservice has no authority for splitting or merging autonomously, the reporting unit (7) creating a report (107).
  • MSS microservice servers

Abstract

La présente invention concerne un système d'observation de microservices dans des systèmes fonctionnant par architecture de microservice en tenant compte de divers paramètres, et de création de recommandations destinées à la division ou à la fusion de microservices en conséquence.
EP19792327.9A 2018-04-26 2019-04-25 Système et procédé de création de recommandations de microservice de division et de fusion Withdrawn EP3785128A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
TR201805929 2018-04-26
PCT/TR2019/050277 WO2019209231A2 (fr) 2018-04-26 2019-04-25 Système et procédé de création de recommandations de microservice de division et de fusion

Publications (1)

Publication Number Publication Date
EP3785128A2 true EP3785128A2 (fr) 2021-03-03

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
EP19792327.9A Withdrawn EP3785128A2 (fr) 2018-04-26 2019-04-25 Système et procédé de création de recommandations de microservice de division et de fusion

Country Status (2)

Country Link
EP (1) EP3785128A2 (fr)
WO (1) WO2019209231A2 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114928633A (zh) * 2022-05-16 2022-08-19 江苏赞奇科技股份有限公司 一种基于复杂云应用环境的高效控制方法及系统

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11640289B2 (en) 2020-08-24 2023-05-02 Rockwell Collins, Inc. Microservices cloud-native architecture for ubiquitous simulation as a service
CN113342472A (zh) * 2021-06-28 2021-09-03 平安消费金融有限公司 微服务集群创建方法、装置、电子设备及可读存储介质
US11847443B2 (en) 2021-09-07 2023-12-19 International Business Machines Corporation Constraints-based refactoring of monolith applications through attributed graph embeddings
US11726778B2 (en) 2021-09-29 2023-08-15 International Business Machines Corporation Translating clusters of a monolith application to microservices
US11768679B2 (en) 2021-11-30 2023-09-26 International Business Machines Corporation Identifying microservices for a monolith application through static code analysis

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9749428B2 (en) * 2014-10-21 2017-08-29 Twilio, Inc. System and method for providing a network discovery service platform
CN104462026A (zh) * 2014-12-10 2015-03-25 中国科学院软件研究所 提供云字库服务的方法和系统
US20170364434A1 (en) * 2016-06-15 2017-12-21 International Business Machines Corporation Splitting and merging microservices

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114928633A (zh) * 2022-05-16 2022-08-19 江苏赞奇科技股份有限公司 一种基于复杂云应用环境的高效控制方法及系统
CN114928633B (zh) * 2022-05-16 2024-04-16 江苏赞奇科技股份有限公司 一种基于复杂云应用环境的高效控制方法及系统

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Publication number Publication date
WO2019209231A2 (fr) 2019-10-31
WO2019209231A3 (fr) 2020-01-23

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