Why do we say that the data service API is the standard configuration of the data midrange?

Link to the original text ： Take the last kilometer of the data center station , Data services API It is the standard configuration of the data console

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One 、 Data services API Construction background

In the era of digital transformation , A substantial increase in new demand 、 The constant iteration of new technologies ,“ The Internet, 、 Digitization ” The continuous deepening of the process , More and more businesses are migrated to the Internet , Generate a large number of business interactions and external service requirements , Yes API The demand for interfaces is increasing day by day , How to quickly improve the enterprise's ability to open and share data , It is the key proposition for enterprises to face digital transformation .

Traditional methods, such as back-end developers through Java or Python And other languages to generate API Interface , The development cycle is too long , The cost of operation and maintenance is too high , Can no longer meet the needs of enterprises . Enterprises often face many difficulties in the process of digital transformation ：

In order to solve these problems more , We are open in the enterprise 、 The following objectives need to be identified in the process of sharing data ：

• Fast build API

• System stability 、 Data security

• Easy to integrate

• Authorized delivery

• Low cost operation and maintenance

Two 、 Data service platform construction methodology

Before sharing the methodology of data service platform construction , Let's first learn about the common data application architecture ：

The data service layer is in the middle of the overall application architecture of the data center , Pass the results of the data computing layer through the data API Is shared to the data application layer . The data service layer mainly includes 3 A role ：

1、 When the data has been integrated and calculated , It needs to be provided to products and applications for data consumption ;

2、 For better performance and experience , Build the data service layer , Provide external data services through interface servitization ;

3、 Meet various complex data service requirements of applications （ Simple data query service 、 Complex data query services 、 Real time data push ）

In the process of providing external services at the data service layer , Experienced from **“DWSOA” To “OneService”** The evolution of .

from “OneService” For the data service itself , It mainly solves the problem of heterogeneous data sources 、 building redundant project 、 Audit operation and maintenance is difficult 、 Understanding difficulties is 4 A question , adopt “OneService” service , Realize topic data service 、 Unified and diverse data services 、 Service objectives of cross source data services .

therefore , If you want to build a complete data service platform , You need to have the following 6 Elements ：

• Convenient development , Low code development capability

• Easier to manage ,API Manage operations visual queries API

• Easy to use , Have standardized document description information

• Safe and stable , Service call tracking monitoring 、 Service usage audit 、 Authentication etc.

• Easy operation and maintenance , test 、 Rectification 、 Problem rule configuration

• performance , Load balancing 、 High concurrency

3、 ... and 、 be based on OneService Building data systems

To understand the “OneService” theory , Next, let's share how to base on OneService Building data systems , Mainly follow the following steps ：

● First step ：API Definition

API The definition of includes ： Quick configuration parameters 、 Select the sort field 、API Diversity of types 、 Data preview 、 Copy fields, etc .

API Types of include generation API、 register API、 Service grouping and service arrangement 4 In terms of .

● The second step ：API Release

API The release of includes testing 、 Submit to API gateway 、 Release to API market 、 Version management .

● The third step ：API call

API Call includes data preview 、API apply 、 The examination and approval 、 Download the interface documentation 、 Formal call .

● Step four ： Call monitoring

Business ： Yes API Call statistics for in-depth analysis , And then get the key information ;

technical ： adopt API Call the statistical chart for analysis to find , Which? API The most popular ; And what almost nobody cares about , Should be eliminated ;

On the security ： Call on IP、 The number of calls is monitored , Trace the source of the caller .

● Step five ： Data security

Data security includes ： Unified Authentication 、 Transmission encryption 、 Security group 、 Role assignment 、 Line level authority 、 Call approval, etc .

The above data services API The construction process of , In fact, it is the several stacks of data services developed by kangaroo cloud EasyAPI The process of product implementation .

Data services （EasyAPI）, Efficient enterprise data service products , Configuration generation and registration through dual mode visualization API, Fast build OneService Data sharing services , Form an enterprise level API Market and API Service management platform , Improve the efficiency of data opening and sharing .

At the same time, the product has the following characteristics :

• Fast build

Configuration is development , Support 0 Code 、 Low code fast build API

• High safety

User authentication 、 monitor 、 Transmission encryption 、API Level security policy 、 Line level authority 、 Role assignment 、 Call application approval 、 Limit on the number of call cycles 、 Black and white list

• High flexibility

“ Service Orchestration “ For different API Are combined , Support integration python Data processing 、 Support “ conditional ” node , Select the branch that meets the criteria

• Flexible configuration

Horizontal expansion API gateway 、 cache

• Low cost operation and maintenance

use Serverless framework , Just focus on API Its own business logic , Little consideration is given to infrastructure such as the operating environment

Four 、API Implement landing cases

Next, let's share three actual cases of using customers , To introduce EasyAPI How to effectively help customers solve problems .

● Finance ： Application data service of a securities company

● School ： A university application data service

● retail ： Application data service of a network company

Kangaroo cloud open source framework nail technology exchange group （30537511）, Students interested in big data open source projects are welcome to join us to exchange the latest technical information , Open source project library address ：https://github.com/DTStack