CN111082985A - API (application program interface) monitoring method based on open platform - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
Abstract
The invention relates to the technical field of interface monitoring, in particular to an API (application program interface) monitoring method based on an open platform. The monitoring module comprises simulation user access API interface detection, server resource monitoring and API monitoring port monitoring. According to the API interface monitoring method based on the open platform, performance analysis is carried out according to historical data, an access time consumption early warning value is analyzed, performance analysis is carried out according to the historical data, an access speed early warning value is analyzed, access quantity analysis is carried out according to the historical data, the access quantity early warning value is analyzed, operation conditions of all API interfaces are monitored conveniently, early warning is carried out, related responsible personnel are notified, threats possibly caused by opening are shielded outside a core network in a hospital, and external unified services are guaranteed to be opened in a safe mode.
Description
Technical Field
The invention relates to the technical field of interface monitoring, in particular to an API (application program interface) monitoring method based on an open platform.
Background
With the continuous development and promotion of hospital information work, hospital information construction has been extended outwards from the traditional hospital internal business system, cross-industry cooperation, and integration of social resources has become one of the working key points of the next stage. Various information of the hospital needs to be integrated with various social resources such as banks, communication operators, media, superior institutions, peer medical institutions and the like, and rich and convenient medical and health services are provided for patients.
Based on the above current situation, institutions want to open an external unified service in a secure manner and to shield threats that may result from the opening from the hospital's internal core network. However, most of the existing methods only monitor the survival condition of the API, and cannot monitor the operation condition of each API and give an early warning to relevant responsible personnel.
Disclosure of Invention
The invention aims to provide an API (application program interface) monitoring method based on an open platform so as to solve the problems in the background technology.
In order to achieve the above object, the present invention provides an API interface monitoring method based on an open platform, which includes a log module, a monitoring module, an event management module, an alarm module and an analysis module, wherein the monitoring module includes an API interface detection for simulating user access, a server resource monitoring and an API monitoring port monitoring, and the detection method includes the following steps:
s1, the log module stores the user access information into an elastic search non-relational database;
s2, when monitoring of the API monitoring port and monitoring of the server resources are abnormal, sending the abnormal information to the event management module;
s3, simulating user access API interface detection, sending to the event management module when access is abnormal, and judging whether the user access record is abnormal by the event management system;
s4, the event management module associates the monitoring module and the analysis module, and sends the association result to the alarm module or displays the monitoring result;
and S5, the alarm module informs the sending related personnel of the alarm information.
Preferably, the user access information includes API feature codes, request ip, request time, request parameters, access time consumption, access speed, request user, request result, return data size and return data.
Preferably, the analysis module comprises the following analysis steps:
s1.1, filtering the access records with request results of 4X and 5X (access abnormal records) in order to ensure the accuracy of analysis, and filtering the access records with access return data size of 0;
s1.2, performing performance analysis according to historical access data of each API interface, and writing an analysis result into a mysql database, wherein the main fields comprise: the method comprises the steps that an API feature code, an API access time consumption upper limit early warning value and an API access speed lower limit early warning value are sent to an event management module when the access time consumption is higher than the early warning value and the access speed is lower than the early warning value (because the time consumption only represents the access time and cannot accurately represent whether the performance is abnormal, whether the performance is abnormal or not can be judged by analyzing whether the access speed is lower than the early warning value at the same time), the event management module is associated with the server resource monitoring condition, if the resource monitoring has sent an abnormal alarm, no alarm is needed, and if not, an alarm is sent;
s1.3, carrying out access analysis and early warning according to historical access data of each API interface, writing an analysis result into a mysql database, wherein the main fields comprise: the method comprises the steps of obtaining an API characteristic code, an API access time period, a maximum API interface access amount early warning value and a minimum API interface access amount early warning value, sending an event management module when the API interface access amount is smaller than the minimum early warning value or higher than the maximum early warning value, and sending an alarm module to carry out early warning.
Preferably, the performance analysis is performed according to the historical access data of each API interface, and the method for analyzing the access time consumption early warning value includes: analyzing a certain time T access time-consuming early warning value of a certain API interface, wherein the access time-consuming abnormal value is defined as:
access time consuming outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
Preferably, the time-consuming upper-limit early warning value for defining the time-consuming abnormal value when the user accesses the API interface is:
min { access time-consuming outlier > -max { mean, Q3+1.5 — IQR } };
if the above value is not present, max { mean, Q3+1.5 iQR } is taken.
Preferably, the method for analyzing the early warning value of the access speed according to the historical access data of each API interface includes: analyzing an access speed early warning value of a certain service in a certain time period T, and adopting a boxplot abnormal value test method, namely a boxplot test method, wherein the access speed abnormal value is defined as:
access speed outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
Preferably, the access speed abnormal value defines a lower limit early warning value of the access speed of the user access API interface as follows:
max { access speed outlier < ═ min { mode, Q1-1.5 × IQR } };
if the above value is not present, then min { mode, Q1-1.5 × IQR } is taken.
Preferably, the method for analyzing the early warning value of the access amount according to the historical access data of each API interface includes: analyzing an early warning value of the access amount in a certain service period T, and adopting a boxplot abnormal value test method, namely a boxplot test method, wherein the access amount abnormal value is defined as:
access volume outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
Preferably, the access quantity abnormal value defines an upper limit early warning value of the user access quantity as follows:
min { access volume outlier > -max { mean, Q3+1.5 × IQR } };
if the value is not present, max { mean, Q3+1.5 × IQR };
defining a user access amount lower limit early warning value of the access amount abnormal value as follows:
max { access volume outlier < ═ min { mode, Q1-1.5 × IQR } };
if the above value is not present, then min { mode, Q1-1.5 × IQR } is taken.
Preferably, the calculation method of the boxplot algorithm includes the following steps:
s2.1, sorting the data from small to large, and counting the data into an array a (1ton), wherein n represents the length of the array;
s2.2, determining the position of the quartile: b is 1+ (n-1) x k/4, the integer part of b is the fractional part of cb is d, calculate Q1: Q1 ═ a (c) + [ a (c +1) -a (c) ] ═ d ═ a (2) + [ a (3) -a (2) ] -1/4;
and S2.3, calculating Q2 and Q3, and calculating the quartile IRQ (Q3-Q1).
Compared with the prior art, the invention has the beneficial effects that: according to the API interface monitoring method based on the open platform, performance analysis is carried out according to historical data, an access time consumption early warning value is analyzed, performance analysis is carried out according to the historical data, an access speed early warning value is analyzed, access quantity analysis is carried out according to the historical data, the access quantity early warning value is analyzed, operation conditions of all API interfaces are monitored conveniently, early warning is carried out, related responsible personnel are notified, threats possibly caused by opening are shielded outside a core network in a hospital, and external unified services are guaranteed to be opened in a safe mode.
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FIG. 1 is an overall process flow diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution:
the invention provides an API interface monitoring method based on an open platform, which comprises a log module, a monitoring module, an event management module, an alarm module and an analysis module, wherein the monitoring module comprises an API interface detection module for simulating user access, a server resource monitoring module and an API monitoring port monitoring module, and the detection method comprises the following steps:
s1, the log module stores the user access information into an elastic search non-relational database;
s2, when monitoring of the API monitoring port and monitoring of the server resources are abnormal, sending the abnormal information to the event management module;
s3, simulating user access API interface detection, sending to the event management module when access is abnormal, and judging whether the user access record is abnormal by the event management system;
s4, the event management module associates the monitoring module and the analysis module, and sends the association result to the alarm module or displays the monitoring result;
and S5, the alarm module informs the sending related personnel of the alarm information.
In this embodiment, the user access information includes an API feature code, a request ip, a request time, a request parameter, an access time, an access speed, a request user, a request result, a return data size, and a return data.
Further, the analysis module comprises the following analysis steps:
s1.1, filtering the access records with request results of 4X and 5X (access abnormal records) in order to ensure the accuracy of analysis, and filtering the access records with access return data size of 0;
s1.2, performing performance analysis according to historical access data of each API interface, and writing an analysis result into a mysql database, wherein the main fields comprise: the method comprises the steps that an API feature code, an API access time consumption upper limit early warning value and an API access speed lower limit early warning value are sent to an event management module when the access time consumption is higher than the early warning value and the access speed is lower than the early warning value (because the time consumption only represents the access time and cannot accurately represent whether the performance is abnormal, whether the performance is abnormal or not can be judged by analyzing whether the access speed is lower than the early warning value at the same time), the event management module is associated with the server resource monitoring condition, if the resource monitoring has sent an abnormal alarm, no alarm is needed, and if not, an alarm is sent;
s1.3, carrying out access analysis and early warning according to historical access data of each API interface, writing an analysis result into a mysql database, wherein the main fields comprise: the method comprises the steps of obtaining an API characteristic code, an API access time period, a maximum API interface access amount early warning value and a minimum API interface access amount early warning value, sending an event management module when the API interface access amount is smaller than the minimum early warning value or higher than the maximum early warning value, and sending an alarm module to carry out early warning.
Specifically, the method for analyzing the access time consumption early warning value according to the performance analysis of the historical access data of each API interface comprises the following steps: analyzing a certain time period T access time consumption early warning value of a certain API interface, randomly extracting 30 sample data of six days including T-7 days, T-14 days, T-21 days, T-28 days, T-35 days and T-42 days of the service, wherein the total time consumed for accessing the API interface by 180 users is defined as the following:
access time consuming outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
Defining a time consumption upper limit early warning value for accessing the API interface by a user according to the access time consumption abnormal value, wherein the time consumption upper limit early warning value is as follows:
min { access time-consuming outlier > -max { mean, Q3+1.5 — IQR } };
if the above value is not present, max { mean, Q3+1.5 iQR } is taken.
It should be noted that, according to the historical access data of each API interface, the method for analyzing the early warning value of the access speed includes: analyzing an early warning value of the access speed of a certain service in a certain time period T, randomly extracting 30 sample data of six days including T-7 days, T-14 days, T-21 days, T-28 days, T-35 days and T-42 days of the service, wherein the access speed of 180 users to the API interface is determined, and the access speed abnormal value is defined as:
access speed outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
The definition user access API interface access speed lower limit early warning value of the access speed abnormal value is as follows:
max { access speed outlier < ═ min { mode, Q1-1.5 × IQR } };
if the above value is not present, then min { mode, Q1-1.5 × IQR } is taken.
Still further, the method for analyzing the early warning value of the access amount according to the historical access data of each API interface comprises the following steps: analyzing the early warning value of the visit amount in a certain service period T, counting the visit amount in the service period T-7 days, T-14 days, T-21 days, T-28 days, T-35 days, T-42 days, T-49 days and T-56 days, and adopting a boxplot test method, wherein the visit amount abnormal value is defined as:
access volume outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
The definition user access amount upper limit early warning value of the access amount abnormal value is as follows:
min { access volume outlier > -max { mean, Q3+1.5 × IQR } };
if the value is not present, max { mean, Q3+1.5 × IQR };
the definition user access amount lower limit early warning value of the access amount abnormal value is as follows:
max { access volume outlier < ═ min { mode, Q1-1.5 × IQR } };
if the above value is not present, then min { mode, Q1-1.5 × IQR } is taken.
It is worth to be noted that, the calculation method of the boxplot algorithm includes the following steps:
s2.1, sorting the data from small to large, and counting the data into an array a (1ton), wherein n represents the length of the array;
s2.2, determining the position of the quartile: b is 1+ (n-1) x k/4, the integer part of b is the fractional part of cb is d, calculate Q1: Q1 ═ a (c) + [ a (c +1) -a (c) ] ═ d ═ a (2) + [ a (3) -a (2) ] -1/4;
and S2.3, calculating Q2 and Q3, and calculating the quartile IRQ (Q3-Q1).
Where n is the number of sample data.
In addition, the calculation Q2 is the same as the calculation Q3 and the calculation Q1, and the mode is the numerical value with the largest occurrence frequency in the sample data; the average is the average of the sample data.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The API interface monitoring method based on the open platform comprises a log module, a monitoring module, an event management module, an alarm module and an analysis module, and is characterized in that: the monitoring module comprises simulation user access API interface detection, server resource monitoring and API monitoring port monitoring, and the detection method comprises the following steps:
s1, the log module stores the user access information into an elastic search non-relational database;
s2, when monitoring of the API monitoring port and monitoring of the server resources are abnormal, sending the abnormal information to the event management module;
s3, simulating user access API interface detection, sending to the event management module when access is abnormal, and judging whether the user access record is abnormal by the event management system;
s4, the event management module associates the monitoring module and the analysis module, and sends the association result to the alarm module or displays the monitoring result;
and S5, the alarm module informs the sending related personnel of the alarm information.
2. The open platform based API monitoring method of claim 1, wherein: the user access information comprises API feature codes, request ip, request time, request parameters, access time consumption, access speed, request users, request results, return data size and return data.
3. The open platform based API monitoring method of claim 1, wherein: the analysis steps of the analysis module are as follows:
s1.1, filtering the access records of the access abnormal records, and filtering the access records with the access return data size of 0;
s1.2, performing performance analysis according to historical access data of each API (application program interface), writing an analysis result into a mysql database, sending the analysis result to an event management module when the access time consumption is higher than an early warning value and the access speed is lower than the early warning value, associating the event management module with the resource monitoring condition of a server, and if the resource monitoring has sent an abnormal alarm, no alarm is needed, otherwise, sending an alarm;
s1.3, performing access analysis and early warning according to historical access data of each API interface, writing an analysis result into a mysql database, sending an event management module when the access of the API interface is smaller than a minimum early warning value or higher than a maximum early warning value, and sending an alarm module for early warning.
4. The API interface monitoring method based on the open platform according to claim 3, characterized in that: the method for analyzing the access time consumption early warning value according to the performance analysis of the historical access data of each API interface comprises the following steps: analyzing an access time consumption early warning value of a certain time period T of a certain API interface, and adopting a boxplot abnormal value inspection method, namely a boxplot inspection method, wherein the access time consumption abnormal value is defined as:
access time consuming outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
5. The API interface monitoring method based on the open platform according to claim 4, characterized in that: the definition of the access time consumption abnormal value is that the time consumption upper limit early warning value of the user for accessing the API interface is as follows:
min { access time-consuming outlier > -max { mean, Q3+1.5 — IQR } };
if the above value is not present, max { mean, Q3+1.5 iQR } is taken.
6. The API interface monitoring method based on the open platform according to claim 3, characterized in that: the method for analyzing the early warning value of the access speed according to the historical access data of each API interface comprises the following steps: analyzing an access speed early warning value of a certain service in a certain time period T, and adopting a boxplot abnormal value test method, namely a boxplot test method, wherein the access speed abnormal value is defined as:
access speed outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
7. The API interface monitoring method based on the open platform according to claim 6, characterized in that: the definition user access API interface access speed lower limit early warning value of the access speed abnormal value is as follows:
max { access speed outlier < ═ min { mode, Q1-1.5 × IQR } };
if the above value is not present, then min { mode, Q1-1.5 × IQR } is taken.
8. The API interface monitoring method based on the open platform according to claim 3, characterized in that: the method for analyzing the early warning value of the access amount according to the historical access data of each API interface comprises the following steps: analyzing an early warning value of the access amount in a certain service period T, and adopting a boxplot abnormal value test method, namely a boxplot test method, wherein the access amount abnormal value is defined as:
access volume outliers { x > Q3+1.5 IQR | x < Q1-1.5 IQR }.
9. The API interface monitoring method based on open platform according to claim 8, wherein: the definition user access amount upper limit early warning value of the access amount abnormal value is as follows:
min { access volume outlier > -max { mean, Q3+1.5 × IQR } };
if the value is not present, max { mean, Q3+1.5 × IQR };
defining a user access amount lower limit early warning value of the access amount abnormal value as follows:
max { access volume outlier < ═ min { mode, Q1-1.5 × IQR } };
if the above value is not present, then min { mode, Q1-1.5 × IQR } is taken.
10. The open platform based API interface monitoring method according to any one of claims 4 to 9, wherein: the calculation method of the boxplot algorithm comprises the following steps:
s2.1, sorting the data from small to large, and counting the data into an array a (1ton), wherein n represents the length of the array;
s2.2, determining the position of the quartile: b is 1+ (n-1) x k/4, the integer part of b is the fractional part of cb is d, calculate Q1: Q1 ═ a (c) + [ a (c +1) -a (c) ] ═ d ═ a (2) + [ a (3) -a (2) ] -1/4;
and S2.3, calculating Q2 and Q3, and calculating the quartile IRQ (Q3-Q1).
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Application publication date: 20200428 |