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docs: test section follows requirements [skip ci]
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@tyknkd
tyknkd committed May 22, 2024
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Expand Up @@ -77,6 +77,16 @@ This table summarizes the required software features and practices implemented i
| Event collaboration messaging | [components/mq-support](https://github.com/tyknkd/news-analyzer/tree/main/components/mq-support) |
| [Continuous delivery](https://github.com/tyknkd/news-analyzer/actions) | [github/workflows](https://github.com/tyknkd/news-analyzer/tree/main/.github/workflows) |

## Testing
Gradle is used to implement unit and integration tests, and these tests are incorporated into the continuous integration/continuous
deployment workflow. Using test doubles and mock external services, the unit tests check each element of the system (e.g., database
operations, message queue, data processing, etc.), and the integration tests check that these elements function together at the app
level as expected: that the data can be reliably (1) collected, (2) stored in the collector database, (3) transferred to the data analyzer,
(4) processed with unsupervised machine learning (LDA), (5) stored in the analyzer database, (6) passed to
the web server, (7) stored in the web-server database, and (8) displayed to the end user in reverse chronological order grouped by topic.
(It is worth noting that because unsupervised machine learning is being applied to unlabeled data in this project, the article topics
can only be identified by common keywords.)

## Live Production Environment
The project is deployed on [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine) and can be accessed at [www.jeitikei.online](https://www.jeitikei.online/)
![homepage](https://github.com/tyknkd/news-analyzer/blob/main/images/screenshot_home_page.png)
Expand All @@ -86,16 +96,6 @@ The REST API entry point is [www.jeitikei.online/api](https://www.jeitikei.onlin
discovery of the endpoints within the API.
![homepage](https://github.com/tyknkd/news-analyzer/blob/main/images/screenshot_api_hateoas.png)

## Testing
Gradle is used to implement unit and integration tests, and these tests are incorporated into the continuous integration/continuous
deployment workflow. Using test doubles and mock external services, the unit tests check each element of the system (e.g., database
operations, message queue, data processing, etc.), and the integration tests check that these elements function together at the app
level as expected: that the data can be (1) reliably collected, (2) stored in the collector database, (3) transferred to the data analyzer,
(4) processed with unsupervised machine learning (LDA), (5) stored in the analyzer database, (6) passed to
the web server, (7) stored in the web-server database, and (8) displayed to the end user in reverse chronological order and by topic group.
(NB: It is worth noting that because unsupervised machine learning is being applied, the article topics are only identified by
common keywords.)

## Monitoring
Production monitoring is accomplished by scraping metrics with [Prometheus](https://cloud.google.com/stackdriver/docs/managed-prometheus)
and visualizing with [Google Cloud Monitoring](https://cloud.google.com/monitoring).
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