Creating CI/CD Pipelines Effortlessly using ChatGPT

In the fast-paced world of software development, continuous integration and continuous delivery (CI/CD) pipelines have become crucial for efficient and reliable software deployment. However, building and maintaining these pipelines can be a daunting task, requiring extensive knowledge and expertise. But what if there was a way to simplify this process and make it more accessible to developers of all skill levels? Enter ChatGPT, the groundbreaking language model developed by OpenAI. In this article, we explore how ChatGPT can effortlessly guide developers in building robust CI/CD pipelines, revolutionizing the way software is delivered.

What is DevOps?

DevOps team is a combination of the Development team and Operations team working together in order to accelerate the time to market and quality of the software development. DevOps way of working is more a shift in the mindset which has a major effect on the team and organization’s way of working. With the DevOps mindset, there are no silos between the development and operations teams. DevOps team mainly focuses on the automation to increase the reliability by enabling continuous integration, and continuous deployment pipelines.

Image 1 : DevOps Lifecycle 

DevOps Lifecycle mainly consists of setting up an automated and collaborative environment to discover, plan, build, and test the artefacts. Once the artefacts are downloaded, they can be deployed to their respective environments. Throughout the DevOps lifecycle, the complete team has to work closely to maintain the alignment, velocity, and quality of the deliverables.DevOps implementation mainly involves below activities :

• Discover product
• An iterative approach for agile planning
• Build pipelines for branching, merging, and workflows for the development process
• Automated Testing using CI pipelines
•  Deployment using release pipelines
• Operationalize and manage end-to-end IT delivery
• Continuous monitoring of the deployed software
• Continuous feedback and improvements for future release

ChatGPT for DevOps

• Automation: DevOps Tools like Jenkins, Ansible, Terraform, etc provide workflow automation. On the other hand, we can use chatGPT to automate the below DevOps activities that require manual intervention.
• Automation Testing: Testing scenarios and automated testing can be enabled using the chatGPT as a part of the continuous build pipeline.
• Release documentation: Maintaining documentation for each feature is a manual and tedious task. With the help of chatGPT, we can write code in any language to create an automated documentation for each release. With ChatGPT, we can generate code for bicep templates and YAML for Azure DevOps, Terraform , Jenkins, and Lambda code for the DevOps activities. 
•  DevSecOps Implementation: Security is a critical factor in order to develop any software. ChatGPT can be used to monitor cloud resources, manage and detect security vulnerabilities , and scan for networking issues, open ports, database, and storage configurations as per the industry standards and requirements.
• Continuous Monitoring: Customised dashboard for monitoring is a key metric for proactive monitoring and taking data-driven decisions. We can create a dashboard using the chatGPT to generate code including a variety of components such as charts, graphs, and tables.

Let’s now ask chatGPT for each of these steps to create a DevOps process flow for a software project. The first step is to set up the Azure DevOps repository structure including the branching policies, and pre, and post-deployment approval:

Image 2: Azure Devop Repo structure & branching policies

As you can see, a recommendation from ChatGPT is to create a new Azure DevOps repository with proper naming conventions. In order to set up the branching policies, we need to configure the build validations, set up the reviewers, status check, and work item linking in the Azure Boards.

Image 3: Azure DevOps Continuous Integration Pipeline

Here, we have requested chatGPT to create a YAML continuous integration build pipeline in Azure DevOps including the code quality checks and testing. ChatGPT provides us with a YAML pipeline that has multiple stages - one for sonarqube, one for fortify code quality checks, one for automation testing, and one to download the artefacts.

 Once the CI pipeline is ready, let’s ask ChatGPT to build IaC(Infrastructure as a Code Pipeline) to deploy Azure services like Azure Data Factory and Azure Databricks.

Image 4 : Azure DevOps Continuous Deployment Pipelines

Here, we can see the step-by-step process to build the continuous deployment pipelines which are using shell script to deploy the Azure Data Factory and Azure CLI to deploy the Azure Databricks. This pipeline also has an integration with the branches to include and it is using variable groups to create a generic pipeline.

 Let’s see how we can build monitoring dashboards using chatGPT:

Conclusion

So chatGPT is not a threat to the DevOps engineers but it will boost up productivity by embracing the technology to set up and implement the DevOps way of working.  In order to get the desired results, detailed prompt input should be provided to generate content from chatGPT to meet the expectations.

Author Bio

Sagar Lad is a Cloud Data Solution Architect with a leading organization and has deep expertise in designing and building Enterprise-grade Intelligent Azure Data and Analytics Solutions. He is a published author, content writer, Microsoft Certified Trainer, and C# Corner MVP.

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