Prototype Callable Workflows For Nightly Archive And Cleanup Workflows

by ADMIN 71 views

Introduction

In an effort to reduce duplicated code and improve the maintainability of our nightly archive and cleanup workflows, we propose the creation of separate, callable workflows to run the actual, executable steps of these processes. This approach will allow individual scripts to focus on defining the table/dataset names and the time to run, while the callable workflows handle the complex, repetitive tasks.

Background

Our current workflow architecture is based on a series of scripts that perform specific tasks, such as archiving and cleaning up data. While this approach has served us well, it has led to duplicated code and increased complexity as the number of scripts has grown. By introducing callable workflows, we can break down these complex tasks into smaller, more manageable pieces, making it easier to maintain and update our workflows.

Benefits of Callable Workflows

The use of callable workflows offers several benefits, including:

  • Reduced duplicated code: By separating the complex tasks into individual workflows, we can reduce the amount of duplicated code and make it easier to maintain and update our workflows.
  • Improved modularity: Callable workflows allow us to break down complex tasks into smaller, more manageable pieces, making it easier to understand and maintain our workflows.
  • Increased flexibility: With callable workflows, we can easily add or remove workflows as needed, without affecting the rest of the workflow architecture.

Prototype Workflow Design

For the prototype, we will create two separate workflows: "BQ archive" and "Cleanup". These workflows will handle the actual, executable steps of the nightly archives and cleanup processes, respectively. Individual scripts will then need to define the table/dataset names and the time to run, while the callable workflows handle the complex tasks.

Workflow Matrix

While a workflow matrix could be used to achieve a similar result, we have chosen to use separate, callable workflows instead. This approach provides a more flexible and maintainable solution, as we can easily add or remove workflows as needed.

Prototype Implementation

For the prototype, we will create the following scripts and convert a small number of less-important games to test-run for a few days before converting the remaining workflows to use the callable workflows:

  • BQ archive workflow: This workflow will handle the actual, executable steps of the nightly archives, including data ingestion, processing, and storage.
  • Cleanup workflow: This workflow will handle the actual, executable steps of the cleanup process, including data deletion, archiving, and logging.
  • CARBON_CYCLE workflow: This workflow will be converted to use the callable workflows, allowing us to test the new architecture with a small number of games.
  • NITROGEN_CYCLE workflow: This workflow will also be converted to use the callable workflows, providing further testing and validation of the new architecture.
  • WATER_CYCLE workflow: Finally, this workflow will be converted to use the callable workflows, completing the prototype implementation.

Implementation Details

To implement the prototype, we will follow these steps:

  1. Create the BQ archive and Cleanup workflows: We will create two separate workflows, one for archiving and one for cleanup, using the callable workflow architecture.
  2. Convert CARBON_CYCLE to use the callable workflows: We will convert the CARBON_CYCLE workflow to use the callable workflows, allowing us to test the new architecture with a small number of games.
  3. Convert NITROGEN_CYCLE to use the callable workflows: We will convert the NITROGEN_CYCLE workflow to use the callable workflows, providing further testing and validation of the new architecture.
  4. Convert WATER_CYCLE to use the callable workflows: Finally, we will convert the WATER_CYCLE workflow to use the callable workflows, completing the prototype implementation.

Testing and Validation

To ensure the success of the prototype, we will test and validate the new architecture with a small number of games. This will involve:

  • Testing the BQ archive and Cleanup workflows: We will test the new workflows to ensure they are functioning correctly and as expected.
  • Testing the CARBON_CYCLE, NITROGEN_CYCLE, and WATER_CYCLE workflows: We will test the converted workflows to ensure they are functioning correctly and as expected.
  • Validating the results: We will validate the results of the testing to ensure that the new architecture is meeting our requirements and expectations.

Conclusion

Introduction

In our previous article, we introduced the concept of prototype callable workflows for nightly archive and cleanup workflows. This approach aims to reduce duplicated code, improve modularity, and increase flexibility in our workflow architecture. In this article, we will answer some frequently asked questions (FAQs) about the prototype callable workflows.

Q&A

Q: What are callable workflows?

A: Callable workflows are separate, reusable workflows that can be called from other workflows to perform specific tasks. They allow us to break down complex tasks into smaller, more manageable pieces, making it easier to maintain and update our workflows.

Q: Why do we need callable workflows?

A: We need callable workflows to reduce duplicated code, improve modularity, and increase flexibility in our workflow architecture. By separating complex tasks into individual workflows, we can make it easier to maintain and update our workflows.

Q: How do callable workflows work?

A: Callable workflows work by defining a specific task or set of tasks that can be called from other workflows. When a workflow calls a callable workflow, it passes the necessary parameters and receives the results of the task.

Q: What are the benefits of using callable workflows?

A: The benefits of using callable workflows include:

  • Reduced duplicated code: By separating complex tasks into individual workflows, we can reduce the amount of duplicated code and make it easier to maintain and update our workflows.
  • Improved modularity: Callable workflows allow us to break down complex tasks into smaller, more manageable pieces, making it easier to understand and maintain our workflows.
  • Increased flexibility: With callable workflows, we can easily add or remove workflows as needed, without affecting the rest of the workflow architecture.

Q: How do we implement callable workflows?

A: To implement callable workflows, we need to:

  1. Create the callable workflows: We need to create separate workflows that define the specific tasks or sets of tasks that can be called from other workflows.
  2. Define the parameters and results: We need to define the parameters that will be passed to the callable workflow and the results that will be returned.
  3. Call the callable workflow: We need to call the callable workflow from the main workflow, passing the necessary parameters and receiving the results.

Q: What are the challenges of implementing callable workflows?

A: The challenges of implementing callable workflows include:

  • Defining the parameters and results: We need to carefully define the parameters that will be passed to the callable workflow and the results that will be returned.
  • Testing and validation: We need to thoroughly test and validate the callable workflows to ensure they are functioning correctly and as expected.
  • Maintaining and updating the workflows: We need to make sure that the callable workflows are properly maintained and updated to reflect changes in the workflow architecture.

Q: How do we test and validate callable workflows?

A: To test and validate callable workflows, we need to:

  • Thoroughly test the callable workflows: We need to test the callable workflows to ensure they are functioning correctly and as expected.
  • Validate the results: We need to validate the results of the callable workflows to ensure they are accurate and reliable.
  • Monitor and troub: We need to monitor and troubleshoot the callable workflows to ensure they are functioning correctly and as expected.

Conclusion

Callable workflows offer several benefits, including reduced duplicated code, improved modularity, and increased flexibility. By implementing callable workflows, we can break down complex tasks into smaller, more manageable pieces, making it easier to maintain and update our workflows. In this article, we have answered some frequently asked questions (FAQs) about the prototype callable workflows, providing a better understanding of this approach and its benefits.