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Measurement method based on DevOps research and development and operation integration

A measurement method and measurement element technology, applied in office automation, instruments, electrical and digital data processing, etc., can solve the problems of data abandonment, shelving, and few people mention the business goals of the software R&D team, so as to improve work efficiency and accuracy. sexual effect

Pending Publication Date: 2020-08-25
北京华佑科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the past, these data were abandoned or shelved after they were generated, and were rarely used, or only used at the end of the year in some enterprises. The scenarios used were nothing more than work reports, annual R&D big data display, etc.
In the face of current complex business scenarios, organizational structure, individual differences, work habits, system platforms and other factors, how to objectively and truly measure software R&D teams, individual roles, software systems and even business goals has been rarely mentioned

Method used

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  • Measurement method based on DevOps research and development and operation integration
  • Measurement method based on DevOps research and development and operation integration
  • Measurement method based on DevOps research and development and operation integration

Examples

Experimental program
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Embodiment 1

[0025] see figure 1 , figure 1 Shown is a schematic flowchart of the measurement method based on the integration of DevOps R&D and operation provided by the embodiment of the present application. Among them, the measurement method based on the integration of DevOps R&D and operation includes the following steps: store different measurement methods in the measurement model, so as to select the measurement method; collect measurement data from the data source, clean and store the measurement data; analyze the measurement data The feature data is extracted as the measurement metadata; the measurement metadata is stored according to the data source, and all the stored measurement metadata are analyzed according to the selected measurement method to obtain the development trend and abnormal analysis of the measurement data.

[0026] Optionally, when selecting an appropriate measurement method through the measurement model, it is first necessary to clarify the purpose of measuremen...

Embodiment 2

[0040] The difference between the embodiment of this application and embodiment 1 is that when the measurement method is used for team portraits, please refer to image 3 , taking the measurement method based on the integration of DevOps R&D and operations to draw a team portrait as an example. When the team includes multiple engineers in Embodiment 1, the measurement data analysis and prediction of each engineer are carried out through the steps in Embodiment 1, so as to summarize into a team portrait. The team image is mainly based on the data of each person in the team, combined with the relevant data of the project undertaken by the team, to generate a portrait of the team.

[0041] Optionally, the measurement data may include one or more of several categories such as delivery performance, delivery quality, delivery speed, business value, health, and maturity. Delivery performance data can be represented by indicators such as R&D productivity, production stability, iterat...

Embodiment 3

[0043] The difference between the embodiment of this application and embodiment 1 is that when the measurement method is used for system portrait, please refer to Figure 4 , taking the measurement method based on the integration of DevOps R&D and operation to draw a system portrait of software development as an example. Combining the requirements phases in the software development life cycle, such as development, access control, testing, release, production and other stages involved in the relevant process and tool chain, extract version control data, change management data, continuous integration and construction data, test related data, Quality access control data, deployment pipeline, environmental management data, database change related data, and system operation related data and business data together constitute the relevant data of a software system to collect measurement data. Wherein, the image of item A and the image of item B are overlapped and displayed, and for t...

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Abstract

The invention provides a measurement method based on DevOps research and development and operation integration, and relates to the field of measurement methods. The measurement method based on DevOpsresearch and development and operation integration comprises the following steps of storing different measurement methods into a measurement model so as to select the measurement method; acquiring measurement data from a data source, and cleaning and storing the measurement data; analyzing the measurement data to extract feature data as measurement metadata; and storing the measurement metadata according to the data source, and analyzing all the stored measurement metadata according to the selected measurement method to obtain a development trend and anomaly analysis of the measurement data. According to the invention, rapid and complete collection and analysis can be realized; therefore, the comprehensive measurement requirements in the current DevOps practice are met; software research and development teams, individual roles, software systems and even business targets can be measured, and related current situation reports and trends can be quickly and completely collected, analyzed and objectively displayed, so that the method serves as an important basis for organizing decision references of roles such as managers, product managers and individuals and discriminating bottleneck problems in time.

Description

technical field [0001] The present invention relates to the field of measurement methods, in particular to a measurement method based on the integration of DevOps R&D and operation. Background technique [0002] In recent years, with the gradual implementation and vigorous development of concepts such as DevOps, cloud computing, micro-services, and containers, there are more and more machines, more and more applications, more and more detailed service content, and more and more diverse application operating environment. Such as containers, virtual machines and physical machines. First of all, in the face of such a complex scenario, traditional measurement methods mostly focus on the measurement of individual projects such as software project management, development costs, software quality, and development productivity (thousand lines of code per person / month). Secondly, in the entire software R&D life cycle, a large amount of R&D process data will be generated from all link...

Claims

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Application Information

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IPC IPC(8): G06F11/36G06Q10/10
CPCG06F11/3612G06Q10/103
Inventor 雷涛
Owner 北京华佑科技有限公司
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