FECFILE CRUD & Load Testing: Schedules A, B, C, D

Hey guys! Today, we're diving deep into the updates and enhancements made to FECFILE, specifically focusing on the implementation of CRUD (Create, Read, Update, Delete) functionality for schedules and the rigorous load testing conducted to ensure everything runs smoothly. This is a big one, so let's get started!

Introduction to CRUD Operations for Schedules

In this update, the main goal was to enhance the data management capabilities within FECFILE by adding full CRUD functionality for Schedules A, B, C, and D. Optionally, Schedules E and F were also considered. This means that users can now create new schedule entries, read existing ones, update information, and delete records as needed. This enhancement streamlines data entry and management, making the system more efficient and user-friendly.

Implementing CRUD operations is crucial for modern applications, especially those dealing with large amounts of data. By allowing users to interact with data in a more flexible way, we reduce the risk of errors and improve overall data accuracy. For FECFILE, this translates to a more robust system capable of handling the complex reporting requirements of the Federal Election Commission. The ability to perform these operations directly through the application interface, rather than relying on backend processes or database manipulations, empowers users and simplifies their workflows. Furthermore, the addition of CRUD functionality sets the stage for future enhancements and integrations, making the system more adaptable to evolving needs and requirements. We also re-evaluated existing tests, particularly concerning summary recalculations, to ensure that the new CRUD operations did not introduce any regressions or unexpected behavior. This thorough testing approach underscores our commitment to maintaining a stable and reliable system for all users. Ensuring data integrity and application stability is paramount, especially when dealing with sensitive financial information.

Locust Load Testing for CRUD Functionality

To ensure the stability and performance of the new CRUD functionalities, we implemented Locust load tests. Locust is a powerful, open-source load testing tool that allows us to simulate a large number of users accessing the application simultaneously. This helps us identify potential bottlenecks and performance issues before they impact real users. The tests specifically targeted the CRUD operations for Schedules A, B, C, and D, ensuring that each function could handle significant load without performance degradation.

Load testing is an essential part of software development, especially for applications like FECFILE that handle critical data and need to be available under varying levels of user traffic. By simulating real-world usage scenarios, we can proactively identify and address potential issues, ensuring a smooth and responsive user experience. The Locust tests were designed to mimic typical user interactions, including creating, reading, updating, and deleting schedule entries. This comprehensive approach allows us to assess the system's resilience under stress and identify areas for optimization. Moreover, the insights gained from these tests inform future development efforts, guiding us in making architectural and performance improvements. We also considered the optional testing of Schedules E and F, ensuring that the load testing framework could be extended to cover additional functionalities as needed. This scalability is crucial for accommodating future growth and enhancements to the FECFILE system. The goal is to create a robust and reliable platform that can meet the evolving demands of our users.

Data Creation Script Enhancements

Several enhancements were made to the data creation script to support the new CRUD functionalities and load testing efforts. These include:

User Creation for Specified User

The script now includes the ability to create a user if one doesn't already exist. This is crucial for ensuring that our tests have a consistent and predictable environment to run in. By automating user creation, we reduce the manual setup required for testing and ensure that the tests can be run repeatedly without conflicts.

Modification to Create Data for [email protected]

To streamline testing and prevent data conflicts, the script was modified to create data specifically for the [email protected] user. This ensures that our tests are isolated and don't interfere with other users' data. Limiting data creation to a specific user also simplifies debugging and troubleshooting, as we can easily identify and isolate any issues related to the test data. Furthermore, this approach aligns with best practices for test data management, ensuring that our test environment remains clean and consistent. By focusing on a single test user, we can also more easily track and manage the data created during testing, making it easier to clean up and reset the environment as needed.

New Bulk Delete Command

A new bulk delete load testing committee data command was introduced. This command is designed to remove all committees where the committee administrator and only user is [email protected]. This helps in cleaning up test data and ensuring a fresh environment for each test run. This is particularly important for local development and testing, where we need to ensure a clean slate for each iteration. The bulk delete command not only simplifies the cleanup process but also reduces the risk of data inconsistencies and conflicts. By automating the deletion of test data, we can ensure that our test environment remains consistent and reliable. This also allows us to run tests more frequently and efficiently, as we don't have to spend time manually cleaning up data. Note that locally, this means you’ll need to spin up fresh to run e2e tests and local manual testing with the data, as well as delete the user too.

Error Handling and Committee ID Ranges

Error handling was implemented to address scenarios where the creation script is run multiple times. This includes handling cases where the committee already exists and providing a flag to specify where to start the data creation process. This makes the script more robust and prevents errors due to duplicate data. By implementing error handling, we ensure that the script can be run repeatedly without issues, making it more reliable and efficient. The ability to specify committee ID ranges allows us to control the data creation process more precisely, ensuring that we don't create duplicate committees or exceed any limits. This is particularly useful when running tests in different environments or when needing to create a specific set of data. The error handling also helps in identifying and resolving any issues during the data creation process, ensuring that the test data is created correctly.

Schedule B Data Creation

The bulk data creation script was modified to create Schedule B data. Schedules C and D do not require bulk creation and can be handled with CRUD tests. This ensures that all necessary schedules are covered in our testing efforts. By focusing on Schedule B for bulk creation, we can efficiently generate a large volume of data for load testing, while Schedules C and D can be tested individually using the CRUD functionalities. This approach optimizes our testing efforts and ensures that all critical aspects of the system are thoroughly tested. The inclusion of Schedule B data creation also provides a more comprehensive test environment, allowing us to identify any potential performance issues related to this specific schedule. This targeted approach to data creation ensures that our testing is both efficient and effective.

Backup Administrator and Data Deletion

The creation of a backup administrator and adding it to committees was considered. This would involve deleting the backup administrator at the end of the testing process. Alternatively, the option of adding oneself as an administrator was discussed to facilitate data checking when login.gov is turned back on. This ensures that there are mechanisms in place for data verification and cleanup post-testing. The consideration of a backup administrator highlights the importance of data management and security in our testing process. Whether a temporary administrator is created and deleted, or an existing user is added as an administrator, the goal is to ensure that data can be verified and managed effectively. This proactive approach to data management reflects our commitment to maintaining a secure and reliable system.

QA, DEV, and Design Notes

QA Notes

• Null (No specific QA notes provided)

DEV Notes

• Null (No specific DEV notes provided)

Design

• Null (No specific design notes provided)

Conclusion

Overall, the addition of CRUD functionality for schedules and the implementation of load testing represent significant enhancements to FECFILE. These updates streamline data management, improve system stability, and ensure a robust platform for our users. The meticulous approach to data creation and the comprehensive testing strategy demonstrate our commitment to delivering a high-quality product. This project underscores our dedication to continuous improvement and our focus on meeting the evolving needs of the FEC.

For more details, you can check out the full ticket and images here: FECFILE-2420

And if you're curious, the Pull Request can be found here: https://github.com/fecgov/fecfile-web-api/pull/1637

Stay tuned for more updates, guys! We're always working to make FECFILE better and more efficient for everyone.