Testing framework with load forecasting
A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about at least one of respective protocols and respective interfaces associated with respective ones of the plurality of components. The data is analyzed to determine at least one of the respective protocols and the respective interfaces associated with the respective ones of the plurality of components. In the method, operations of one or more components of the plurality of components are tested based at least in part on the determination of the at least one of the respective protocols and the respective interfaces. The method further includes outputting respective statuses of the one or more components, wherein the respective statuses are derived at least in part from the testing.
1. A method, comprising:
collecting data corresponding to a plurality of computer-based components in a system, wherein the data comprises information about at least one of respective protocols and respective interfaces associated with respective ones of the plurality of computer-based components;
analyzing the data to determine at least one of the respective protocols and the respective interfaces associated with the respective ones of the plurality of computer-based components;
determining one or more testing methods compatible with the respective ones of the plurality of computer-based components based at least in part on the determination of the at least one of the respective protocols and the respective interfaces;
testing operations of one or more computer-based components of the plurality of computer-based components using the one or more testing methods; and
outputting respective statuses of the one or more computer-based components;
wherein the respective statuses are derived at least in part from the testing; and
wherein the steps of the method are executed by a processing device operatively coupled to a memory.
2. The method of claim 1 , wherein the plurality of computer-based components comprise at least one of one or more applications, one or more instances of middleware and one or more servers.
3. The method of claim 2 , wherein the one or more instances of middleware comprise one or more message-oriented-middleware platforms.
4. The method of claim 1 , further comprising:
generating one or more visualizations depicting one or more of the respective statuses, wherein the one or more the respective statuses comprise at least one of a successful transaction and a failed transaction corresponding to one or more applications.
5. The method of claim 1 , wherein the respective protocols comprise one or more message-oriented-middleware messaging integration patterns.
6. The method of claim 5 , wherein the one or more message-oriented-middleware messaging integration patterns comprise at least one of a point-to-point without routing message-oriented-middleware messaging integration pattern, a point-to-point without routing and with load balancing message-oriented-middleware messaging integration pattern, a many-to-one point-to-point without routing message-oriented-middleware messaging integration pattern, a point-to-point with routing message-oriented-middleware messaging integration pattern, a fan-out message-oriented-middleware messaging integration pattern and a publisher/subscriber message-oriented-middleware messaging integration pattern.
7. The method of claim 5 , wherein the testing of the one or more computer-based components comprises testing at least one of a source computer-based component and a target computer-based component associated with one or more of the message-oriented-middleware messaging integration patterns.
8. The method of claim 1 , wherein the respective protocols comprise at least one of a webservice protocol, a batch protocol, a request/reply protocol, an extensible markup language protocol, a JavaScript object notation protocol, a representational state transfer protocol and a simple object access protocol.
9. The method of claim 1 , further comprising identifying at least one computer-based component of the one or more computer-based components requiring an update based at least in part on one or more of the respective statuses.
10. The method of claim 9 , further comprising identifying at least one of a protocol and an interface corresponding to the at least one computer-based component requiring the update.
11. The method of claim 9 , wherein the identifying of the at least one computer-based component requiring the update comprises determining, based at least in part on the testing, that operation of the at least one computer-based component is impeded by a modification to an application programming interface.
12. The method of claim 1 , wherein the testing comprises load testing of the one or more computer-based components, and the method further comprises:
predicting a transaction load for the one or more computer-based components at one or more time periods; and
scheduling the load testing based at least in part on the predicted transaction load;
wherein the predicting is performed using one or more machine learning techniques.
13. The method of claim 1 , further comprising simulating one or more unavailable services required for performance of the testing.
14. The method of claim 1 , wherein the data further comprises information about respective channels associated with respective ones of the plurality of computer-based components, wherein the analyzing further comprises analyzing at least two or more of the respective protocols, the respective channels and the respective interfaces associated with the respective ones of the plurality of computer-based components, wherein at least one of the plurality of computer-based components has at least one of a different respective protocol, a different respective channel, and a different respective interface from other ones of the plurality of computer-based components.
15. An apparatus comprising:
a processing device operatively coupled to a memory and configured to:
collect data corresponding to a plurality of computer-based components in a system, wherein the data comprises information about at least one of respective protocols and respective interfaces associated with respective ones of the plurality of computer-based components;
analyze the data to determine at least one of the respective protocols and the respective interfaces associated with the respective ones of the plurality of computer-based components;
determine one or more testing methods compatible with the respective ones of the plurality of computer-based components based at least in part on the determination of the at least one of the respective protocols and the respective interfaces;
test operations of one or more computer-based components of the plurality of computer-based components using the one or more testing methods; and
output respective statuses of the one or more computer-based components, wherein the respective statuses are derived at least in part from the testing.
16. The apparatus of claim 15 , further comprising identifying at least one computer-based component of the one or more computer-based components requiring an update based at least in part on one or more of the respective statuses, wherein the processing device is further configured to identify at least one of a protocol and an interface corresponding to the at least one computer-based component requiring the update.
17. The apparatus of claim 15 , wherein the testing comprises load testing of the one or more computer-based components, and the processing device is further configured to:
predict a transaction load for the one or more computer-based components at one or more time periods; and
schedule the load testing based at least in part on the predicted transaction load;
wherein the predicting is performed using one or more machine learning techniques.
18. An article of manufacture comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes said at least one processing device to perform the steps of:
collecting data corresponding to a plurality of computer-based components in a system, wherein the data comprises information about at least one of respective protocols and respective interfaces associated with respective ones of the plurality of computer-based components;
analyzing the data to determine at least one of the respective protocols and the respective interfaces associated with the respective ones of the plurality of computer-based components;
determining one or more testing methods compatible with the respective ones of the plurality of computer-based components based at least in part on the determination of the at least one of the respective protocols and the respective interfaces;
testing operations of one or more computer-based components of the plurality of computer-based components using the one or more testing methods; and
outputting respective statuses of the one or more computer-based components, wherein the respective statuses are derived at least in part from the testing.
19. The article of manufacture of claim 18 , further comprising identifying at least one computer-based component of the one or more computer-based components requiring an update based at least in part on one or more of the respective statuses, wherein the program code causes said at least one processing device to further perform the step of identifying at least one of a protocol and an interface corresponding to the at least one computer-based component requiring the update.
20. The article of manufacture of claim 18 , wherein the testing comprises load testing of the one or more computer-based components, and the program code causes said at least one processing device to further perform the steps of:
predicting a transaction load for the one or more computer-based components at one or more time periods; and
scheduling the load testing based at least in part on the predicted transaction load;
wherein the predicting is performed using one or more machine learning techniques.