Multicloud test automation framework

1 . One or more non-transitory computer-readable media storing computer-executable instructions which, when executed by a processor on a computer system, perform a method for secure multicloud validation, the method comprising:

receiving a natural language request for a cloud-based test scenario, the request comprising a cloud resource and a cloud platform;

using a machine learning model, mapping keywords extracted from the test scenario to a test case associated with the cloud resource and a configuration file associated with the cloud platform, the configuration file selected from a set of configuration files each associated with a cloud platform and comprising:

a cloud service access point comprising a secure gateway;

an encrypted security key; and

a security level for the test case and security levels for each test case in a set of test cases;

retrieving a pre-coded shell script associated with the test case from a shell script repository;

based on the configuration file:

tuning the secure gateway to the security level for the test case and the cloud platform, the tuning comprising adjusting a connection parameter for the secure gateway; and

accessing the cloud platform via the secure gateway;

executing the shell script using data from the cloud platform; and

generating a summary report comprising execution results for the shell script.

2 . The media of claim 1 , wherein the cloud resource is a first cloud resource, the cloud platform is a first cloud platform, the test case is a first test case, the shell script is a first shell script, and the secure gateway is a first secure gateway, the method further comprising:

using the machine learning model, mapping keywords extracted from the test scenario to a second test case associated with a second cloud resource and a second configuration file associated with a second cloud platform;

retrieving a second shell script associated with the second test case;

based on the second configuration file, accessing the second cloud platform via a second secure gateway;

executing the second shell script using data from the second cloud platform; and

generating a summary report comprising execution results for execution of the first shell script and the second shell script.

3 . The media of claim 1 , the summary report comprising a test case name, a test case description, an execution status, an error log, a test duration, an execution date, and a test environment.

4 . The media of claim 1 , the method further comprising compiling a technical log for execution of the shell script.

5 . The media of claim 1 , the method further comprising using tokenization to extract a keyword from the test scenario and iterating through a natural language processing library to map a token to the cloud resource.

6 . The media of claim 1 , wherein the cloud platform is a public cloud platform comprising a private connection.

7 . A system for a secure multicloud validation framework comprising a processor configured to:

receive a natural language cloud-based test scenario, the test scenario comprising a cloud resource and a cloud platform;

using a machine learning model, map keywords extracted from the test scenario to a test case associated with the cloud resource and a configuration file associated with the cloud platform, the configuration file comprising:

a cloud service access point comprising a secure gateway;

an encrypted security key; and

a security level for the test case and security levels for each test case in a set of test cases;

retrieve a pre-coded shell script associated with the test case from a shell script repository;

based on the configuration file:

tune the secure gateway to the security level for the test case and the cloud platform, the tuning comprising adjusting a connection parameter for the secure gateway; and

access the cloud platform via the secure gateway;

execute the shell script using data from the cloud platform; and

generate a summary report for execution of the shell script.

8 . The system of claim 7 , wherein the cloud resource is a first cloud resource, the cloud platform is a first cloud platform, the test case is a first test case, the shell script is a first shell script, and the secure gateway is a first secure gateway, the processor further configured to:

using the machine learning model, map keywords extracted from the test scenario to a second test case associated with a second cloud resource and a second configuration file associated with a second cloud platform;

retrieve a second shell script associated with the second test case;

based on the second configuration file, access the second cloud platform via a second secure gateway;

execute the second shell script using data from the second cloud platform; and

generate a summary report for execution of the second shell script.

9 . The system of claim 7 , further comprising a router proprietary to the cloud platform, the processor configured to route the shell script to the router based on the configuration file.

10 . The system of claim 7 , further comprising a user interface configured to receive input of a natural language test scenario.

11 . The system of claim 7 , the summary report comprising a test case name, a test case description, an execution status, an error log, a test duration, an execution date, and a test environment.

12 . The system of claim 7 , the processor further configured to compile a technical log for execution of the shell script.

13 . The system of claim 7 , the processor further configured to use tokenization to extract a keyword from the natural language test scenario and iterate through a natural language processing library to map a token to the cloud resource.

14 . A method for a secure multicloud validation framework comprising non-transitory computer-executable instructions that when executed by a processor:

receive a natural language request for a cloud-based test scenario, the request comprising a cloud resource and a cloud platform;

using a machine learning model:

map a first keyword extracted from the request to a test case associated with the cloud resource; and

map a second keyword extracted from the request to a configuration file associated with the cloud platform, the configuration file comprising:

a cloud service access point comprising a secure gateway;

an encrypted security key; and

a security level for the test case, the security level variable based on a test case;

retrieve a pre-coded shell script associated with the test case from a shell script repository;

based on the configuration file:

tune the security gateway to the security level for the test case and the cloud platform, the tuning comprising adjusting a connection parameter for the secure gateway; and

access the cloud platform via the secure gateway;

execute the shell script using data from the cloud platform; and

generate a summary report for execution of the shell script.

15 . The method of claim 14 , wherein the cloud resource is a first cloud resource, the cloud platform is a first cloud platform, the test case is a first test case, the shell script is a first shell script, and the secure gateway is a first secure gateway, the processor further configured to:

using the machine learning model, map keywords extracted from the request to a second test case associated with a second cloud resource and a second configuration file associated with a second cloud platform;

retrieve a second shell script associated with the second test case;

based on the second configuration file, access the second cloud platform via a second secure gateway;

execute the second shell script using data from the second cloud platform; and

generate a summary report for execution of the first shell script and the second shell script.

16 . The method of claim 14 , further comprising adapting the framework for an additional cloud platform by providing access to an additional configuration file.

17 . The method of claim 14 , the configuration file comprising a cloud service access point and an encrypted authentication key.

18 . The method of claim 14 , the summary report comprising a test case name, a test case description, an execution status, an error log, a test duration, an execution date, and a test environment.

19 . The method of claim 14 , further comprising, using tokenization to extract a keyword from the natural language request and iterating through a natural language processing library to map a token to the cloud resource.