Move Detection Constants Out From Workers To Common Storage

Introduction

In software development, especially in large-scale applications, it's common to encounter issues related to data consistency and maintainability. One such issue arises when detection constants are hardcoded within workers, making it challenging to manage and update these values across the application. This article proposes a solution to move detection constants out from workers to a common storage, improving the overall maintainability and scalability of the application.

Problem Statement

The current implementation of detection constants within workers leads to several issues:

• Tight Coupling: Workers are tightly coupled with the detection constants, making it difficult to modify or update these values without affecting the workers.
• Data Consistency: With detection constants scattered across multiple workers, ensuring data consistency becomes a challenging task.
• Maintenance: Updating detection constants requires modifying multiple workers, increasing the maintenance burden.

Proposed Solution

To address the issues mentioned above, we propose creating a table in Postgres to store detection constants. This approach offers several benefits:

• Decoupling: By storing detection constants in a separate table, workers become decoupled from these values, making it easier to modify or update them without affecting the workers.
• Data Consistency: With detection constants stored in a single location, ensuring data consistency becomes a straightforward task.
• Maintenance: Updating detection constants requires modifying a single table, reducing the maintenance burden.

Design Overview

The proposed solution involves the following components:

• Postgres Table: A table in Postgres will be created to store detection constants. This table will have columns for the constant name, value, and any other relevant metadata.
• API Endpoint: An API endpoint will be created in api-general to deliver detection constants to workers. This endpoint will retrieve the required constants from the Postgres table and return them to the workers.
• Workers: Workers will be modified to retrieve detection constants from the API endpoint instead of hardcoding them.

Implementation Details

The implementation details for the proposed solution are as follows:

Postgres Table

A table named detection_constants will be created in Postgres with the following columns:

API Endpoint

An API endpoint will be created in api-general to deliver detection constants to workers. The endpoint will have the following characteristics:

• GET Request: The endpoint will accept a GET request with a query parameter constant_name to retrieve the required constant.
• Response: The endpoint will return the detection constant in JSON format, including the name, value, and metadata.

Workers

Workers will be modified to retrieve detection constants from the API endpoint instead of hardcoding them. The modified workers will have the following characteristics:

• API Call: The workers will make a GET request to the API endpoint with the required constant name as a query parameter.
• Constant Retrieval: The workers will retrieve the detection constant from the API endpoint and store it in a local variable.
• Usage: The workers will use the retrieved detection constant instead of the hardcoded value.

Benefits

The proposed solution offers several benefits, including:

• Improved Maintainability: By storing detection constants in a separate table, updating these values becomes a straightforward task, reducing the maintenance burden.
• Enhanced Data Consistency: With detection constants stored in a single location, ensuring data consistency becomes a straightforward task.
• Increased Scalability: The proposed solution allows for easy addition of new detection constants, making it an ideal solution for large-scale applications.

Conclusion

In conclusion, moving detection constants out from workers to a common storage improves the overall maintainability and scalability of the application. The proposed solution involves creating a table in Postgres to store detection constants, an API endpoint to deliver these constants to workers, and modifying workers to retrieve constants from the API endpoint. The benefits of this solution include improved maintainability, enhanced data consistency, and increased scalability. By implementing this solution, developers can ensure that their application remains maintainable, scalable, and efficient.

Future Work

Future work on this project may include:

• Implementing Data Validation: Implementing data validation to ensure that the detection constants stored in the Postgres table are valid and consistent.
• Adding Support for Multiple Constants: Adding support for retrieving multiple detection constants from the API endpoint.
• Integrating with Other Components: Integrating the proposed solution with other components of the application to ensure seamless functionality.

References

• [1] GitHub Repository: worker_general (https://github.com/ScrapingAnt/worker_general)
• [2] GitHub Repository: worker_curl (https://github.com/ScrapingAnt/worker_curl)

Appendix

The following appendix provides additional information related to the proposed solution:

Postgres Table Schema

CREATE TABLE detection_constants (
    id SERIAL PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    value VARCHAR(255) NOT NULL,
    metadata JSONB
);

API Endpoint Code

const express = require('express');
const app = express();

app.get('/detection-constants/:constant_name', (req, res) => {
    const constantName = req.params.constant_name;
    const constant = getConstantFromPostgres(constantName);
    res.json(constant);
});

function getConstantFromPostgres(constantName) {
    // Retrieve the constant from the Postgres table
    // ...
}

Worker Code

const axios = require('axios');

async function retrieveDetectionConstant(constantName) {
    const response = await axios.get(`http://api-general/detection-constants/${constantName}`);
    const constant = response.data;
    return constant;
}
```<br/>
**Move Detection Constants Out from Workers to Common Storage: Q&A**
=================================================================

**Introduction**
---------------

In our previous article, we proposed a solution to move detection constants out from workers to a common storage, improving the overall maintainability and scalability of the application. In this Q&A article, we will address some of the frequently asked questions related to this proposal.

**Q: Why do we need to move detection constants out from workers?**
----------------------------------------------------------------

A: Detection constants are hardcoded within workers, making it challenging to manage and update these values across the application. By storing detection constants in a separate table, we can decouple workers from these values, making it easier to modify or update them without affecting the workers.

**Q: What are the benefits of storing detection constants in a separate table?**
-------------------------------------------------------------------------

A: Storing detection constants in a separate table offers several benefits, including:

*   **Improved Maintainability**: Updating detection constants becomes a straightforward task, reducing the maintenance burden.
*   **Enhanced Data Consistency**: With detection constants stored in a single location, ensuring data consistency becomes a straightforward task.
*   **Increased Scalability**: The proposed solution allows for easy addition of new detection constants, making it an ideal solution for large-scale applications.

**Q: How will we retrieve detection constants from the API endpoint?**
-------------------------------------------------------------------

A: Workers will make a GET request to the API endpoint with the required constant name as a query parameter. The API endpoint will retrieve the detection constant from the Postgres table and return it to the worker in JSON format.

**Q: What if we have multiple detection constants that need to be retrieved?**
-------------------------------------------------------------------------

A: We can modify the API endpoint to accept a query parameter `constant_names` that contains a comma-separated list of constant names. The API endpoint can then retrieve the corresponding detection constants from the Postgres table and return them to the worker in a single response.

**Q: How will we handle errors when retrieving detection constants?**
-------------------------------------------------------------------

A: We can implement error handling mechanisms in the API endpoint to handle cases where the detection constant is not found in the Postgres table or if there is an issue with the API request. We can also implement retry mechanisms to handle transient errors.

**Q: What are the security implications of storing detection constants in a separate table?**
-----------------------------------------------------------------------------------------

A: Storing detection constants in a separate table does not introduce any new security risks. However, we should ensure that the Postgres table is properly secured and that access to the table is restricted to authorized personnel.

**Q: How will we migrate existing detection constants to the new storage solution?**
--------------------------------------------------------------------------------

A: We can create a migration script that retrieves the existing detection constants from the workers and inserts them into the Postgres table. We can then update the workers to retrieve detection constants from the API endpoint.

**Q: What are the next steps after implementing the proposed solution?**
-------------------------------------------------------------------------

A: After implementing the proposed solution, we can monitor the application's performance and ensure that the new storage solution is working as expected. We can also continue to refine the solution by adding additional features and error handling mechanisms.

**Conclusion**
----------

In conclusion, moving detection constants out from workers to a common storage is a crucial step in improving the overall maintainability and scalability of the application. By addressing the frequently asked questions related to this proposal, we can ensure that the solution is implemented successfully and that the application continues to meet the evolving needs of its users.

**Future Work**
--------------

Future work on this project may include:

*   **Implementing Data Validation**: Implementing data validation to ensure that the detection constants stored in the Postgres table are valid and consistent.
*   **Adding Support for Multiple Constants**: Adding support for retrieving multiple detection constants from the API endpoint.
*   **Integrating with Other Components**: Integrating the proposed solution with other components of the application to ensure seamless functionality.

**References**
--------------

*   [1] GitHub Repository: `worker_general` (https://github.com/ScrapingAnt/worker_general)
*   [2] GitHub Repository: `worker_curl` (https://github.com/ScrapingAnt/worker_curl)

**Appendix**
----------

The following appendix provides additional information related to the proposed solution:

### Postgres Table Schema

```sql
CREATE TABLE detection_constants (
    id SERIAL PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    value VARCHAR(255) NOT NULL,
    metadata JSONB
);

API Endpoint Code

const express = require('express');
const app = express();

app.get('/detection-constants/:constant_name', (req, res) => {
    const constantName = req.params.constant_name;
    const constant = getConstantFromPostgres(constantName);
    res.json(constant);
});

function getConstantFromPostgres(constantName) {
    // Retrieve the constant from the Postgres table
    // ...
}

Worker Code

const axios = require('axios');

async function retrieveDetectionConstant(constantName) {
    const response = await axios.get(`http://api-general/detection-constants/${constantName}`);
    const constant = response.data;
    return constant;
}