Microservice management using machine learning
In some examples, a computing device may implement a method that includes receiving microservice profile information at a microservice profiler, performing lexical analysis of the microservice profile information (where the lexical analysis produces tokenized information), generating microservice modification information by performing machine learning analysis of one or more inputs (where the one or more inputs comprise the tokenized information), and outputting the microservice modification information from the microservice profiler. The microservice profile information describes one or more characteristics of a microservice. The lexical analysis is performed by a lexical analysis engine of the microservice profiler, and the machine learning analysis is performed by a machine learning system of the microservice profiler.
1. A method comprising:
receiving microservice profile information at a microservice profiler, wherein the microservice profile information describes one or more characteristics of a microservice;
performing lexical analysis of the microservice profile information, wherein the lexical analysis produces tokenized information, and the lexical analysis is performed by a lexical analysis engine of the microservice profiler;
generating microservice modification information by performing machine learning analysis of one or more inputs, wherein the one or more inputs comprise the tokenized information, the machine learning analysis is performed by a machine learning system of the microservice profiler, wherein the machine learning system outputs modification recommendations for the microservice to improve performance of the microservice, wherein the modification recommendations comprise removing functionality from a portion of a deployment of the microservice, wherein the portion of the deployment comprises the removed functionality, and directing traffic away from Hall the portion of the deployment of the microservice, wherein the portion of the deployment comprises the removed functionality;
outputting the microservice modification information from the microservice profiler, wherein the microservice modification information comprises the modification recommendation;
generating microservice dependency visualization data as part of the performing the machine learning analysis of the one or more inputs; and
outputting the microservice dependency visualization data from the microservice profiler to a visualization processor.
2. The method of claim 1 , wherein
the outputting outputs the microservice modification information to an input of the microservice profiler.
3. The method of claim 1 , wherein
the one or more inputs further comprise feedback microservice modification information, and
the feedback microservice modification information was generated by the machine learning system prior to the generating the microservice modification information.
4. The method of claim 1 , wherein
the lexical analysis engine employs a lexical analysis technique, and
the lexical analysis technique comprises at least one of
a term frequency-inverse document frequency lexical analysis technique, or
a multi-encoder lexical analysis technique.
5. The method of claim 1 , wherein
the machine learning system employs a machine learning technique, and
the machine learning technique is a recurrent neural network technique.
6. The method of claim 5 , wherein
the recurrent neural network technique is a long short-term memory technique.
7. The method of claim 1 , wherein
the outputting outputs the microservice modification information to a continuous integration continuous deployment pipeline.
8. The method of claim 7 , further comprising:
generating microservice program code;
generating microservice configuration information, wherein
the microservice program code and the microservice configuration information are generated by the continuous integration continuous deployment pipeline; and
analyzing the microservice program code and the microservice configuration information, wherein
the analyzing is performed by a microservice analyzer.
9. The method of claim 8 , further comprising:
generating the microservice profile information, wherein
the microservice profile information is generated by the microservice analyzer, based, at least in part, on the analyzing performed by the microservice analyzer.
10. The method of claim 1 , wherein
the microservice profile information is received from a microservice analyzer, and
the microservice profile information is generated by the microservice analyzer from at least one of one or more microservice characteristics, and
the one or more microservice characteristics comprise at least one of
a programming language,
program code,
a microservice type,
one or more microservice functionalities,
a request data type,
a response data type, or
microservice interaction information.
11. The method of claim 1 , wherein
the microservice profile information comprises at least one of
request/response information for the microservice,
a business context for the microservice, or
one or more dependencies between the microservice and one or more other microservices.
12. A non-transitory computer-readable storage medium comprising program instructions, which, when executed by one or more processors of a computing system, perform a method comprising:
receiving microservice profile information at a microservice profiler, wherein the microservice profile information describes one or more characteristics of a microservice;
performing lexical analysis of the microservice profile information, wherein the lexical analysis produces tokenized information, and the lexical analysis is performed by a lexical analysis engine of the microservice profiler;
generating microservice modification information by performing machine learning analysis of one or more inputs, wherein the one or more inputs comprise the tokenized information, the machine learning analysis is performed by a machine learning system of the microservice profiler, wherein the machine learning system outputs modification recommendations for the microservice to improve performance of the microservice, wherein the modification recommendations comprise removing functionality from a portion of a deployment of the microservice, wherein the portion of the deployment comprises the removed functionality, and directing traffic away from Hall the portion of the deployment of the microservice, wherein the portion of the deployment comprises the removed functionality;
outputting the microservice modification information from the microservice profiler, wherein the microservice modification information comprises the modification recommendation;
generating microservice dependency visualization data as part of the performing the machine learning analysis of the one or more inputs; and
outputting the microservice dependency visualization data from the microservice profiler to a visualization processor.
13. The non-transitory computer-readable storage medium of claim 12 , wherein
the one or more inputs further comprise feedback microservice modification information, and
the feedback microservice modification information was generated by the machine learning system prior to the generating the microservice modification information.
14. The non-transitory computer-readable storage medium of claim 12 , wherein
the lexical analysis engine employs a lexical analysis technique, and
the lexical analysis technique comprises at least one of
a term frequency-inverse document frequency lexical analysis technique, or
a multi-encoder lexical analysis technique.
15. The non-transitory computer-readable storage medium of claim 12 , wherein
the machine learning system employs a machine learning technique,
the machine learning technique is a recurrent neural network technique, and
the recurrent neural network technique is a long short-term memory technique.
16. The non-transitory computer-readable storage medium of claim 12 , the method further comprising:
the microservice profile information is received from a microservice analyzer, and
the microservice profile information is generated by the microservice analyzer from at least one of one or more microservice characteristics, and
the one or more microservice characteristics comprise at least one of
a programming language,
program code,
a microservice type,
one or more microservice functionalities,
a request data type,
a response data type, or
microservice interaction information.
17. The non-transitory computer-readable storage medium of claim 12 , the method further comprising:
the microservice profile information comprises at least one of
request/response information for the microservice,
a business context for the microservice, or
one or more dependencies between the microservice and one or more other microservices.
18. A system comprising:
one or more processors; and
a computer-readable storage medium coupled to the one or more processors, comprising program instructions, which, when executed by the one or more processors, perform a method comprising:
receiving microservice profile information at a microservice profiler, wherein the microservice profile information describes one or more characteristics of a microservice, performing lexical analysis of the microservice profile information, wherein the lexical analysis produces tokenized information, and the lexical analysis is performed by a lexical analysis engine of the microservice profiler, generating microservice modification information by performing machine learning analysis of one or more inputs, wherein the one or more inputs comprise the tokenized information, the machine learning analysis is performed by a machine learning system of the microservice profiler, wherein the machine learning system outputs modification recommendations for the microservice to improve performance of the microservice, wherein the modification recommendations comprise removing functionality from a portion of a deployment of the microservice, wherein the portion of the deployment comprises the removed functionality, and directing traffic away from Hall the portion of the deployment of the microservice, wherein the portion of the deployment comprises the removed functionality,
outputting the microservice modification information from the microservice profiler, wherein the microservice modification information comprises the modification recommendation;
generating microservice dependency visualization data as part of the performing the machine learning analysis of the one or more inputs; and
outputting the microservice dependency visualization data from the microservice profiler to a visualization processor.
19. The system of claim 18 , wherein
the one or more inputs further comprise feedback microservice modification information, and
the feedback microservice modification information was generated by the machine learning system prior to the generating the microservice modification information.