In this digital era, continuous integration (CI) and deployment (CD) are key in DevOps. How? The practices automate the software development cycle, including code changes, production deployment and delivery acceleration. According to researchers, the serverless computing market is expected to reach 50.86 billion USD by 2031 with a CAGR of 22.8%. If you implement CI/CD for serverless apps, you can boost system efficiency, automate processes and reduce overhead.
And you know what? Serverless computing is more scalable and efficient than other manual processes. So, it’s time you shift to the pipeline in this modern DevOps era. Let’s delve into – how serverless CI/CD plays a significant role in DevOps.
Why Should You Adopt CI/CD for Serverless Deployment?
You can refine deployment and code delivery (with an automation process) using the CI & CD pipeline. If you are a new developer, CI can help you with code source integration so that you can push the code into production.
Nevertheless, continuous delivery can help with the deployment part. You can automate its utilization and also test for software with CD. In short, these processes help the business drive value and speed up the project lifecycle.
Faster Deployment
Speed is the most essential part of the current digital landscape. Of course, with the use of modern technology, there has been a rapid increase in the deployment of software. Likewise, serverless CI/CD offers faster deployment, as it accelerates the code deployment pace and time to market.
As you know, the testing is automated, so the code is auto-deployed. This process can help you release the software into the production cycle many times at a good pace. Also, automation reduces manual labor tasks, increasing productivity.
Reduces Delivery Costs
A company always looks for ways to reduce development and delivery costs. Here is where serverless CI/CD plays a significant part. The pipeline is adept at reducing human intervention across the DevOps lifecycle.
You can save your time and resources with features like source control, added code management, testing, etc, to deliver the software. Isn’t that great? Also, with a successful automatic pipeline, you don’t have to work on code fixes again and again.
With the codes in place and the process automated, you can easily focus on other vital operational tasks. By doing so, you can also maximize the return on investment for the company.
Improves Code Quality
Do you know what is the most significant aspect of software development? Well, it is none other than code quality. One notable reason why you should adopt serverless CI/CD in DevOps is code quality.
Of course, the most essential process you require is CI-CD. With the said pipeline, you can integrate code into a shared repository, which can help you conduct code testing at the same time.
Also, with a common repository, you can share what you built with your entire team. With a collaborative work setup, you can identify errors and bugs before the code makes it to the final production. With improved code quality, you will be able to deliver an improved software version.
Simplify The Rollback Process
What if something goes wrong while typing? You use an undo option, right? The rollback process is simple with the option. Likewise, you have a rollback option in the CI/CD process.
With the rollback feature, you can recover fast if you fail at a task. Isn’t that time-saving? The pipeline helps you push code into production, and if an issue arises, you can roll back to the step.
Of course, the rollback feature saves resources and time. You and your team can fix code errors at a faster pace with the feature.
Cut Down On Debugging
As you know, there are two main aspects of software development – debugging and code testing. Testing is a reason why most software releases are delayed.
If there is a delay, it affects the goodwill and time to market. This is certainly not a piece of good news for the company. Earlier testing was conducted manually, which was time-consuming.
If you use serverless CI/CD in DevOps, you will be able to cut down the manual amending and testing time. Automated processes help improve the software delivery time, which is a plus.
Improves Accountability
Do you know the Serverless CI & CD pipeline works on an unambiguous approach? Meaning, the pipeline offers real-time visibility into the entire software development lifecycle.
Of course, with continuous feedback and testing, you always stay in the loop. Also, the feedback report allows your team to stay on track. You can learn about the project status from the report.
Once there is transparency, you will know about build failures and code issues. Also, you will know about the architectural gridlocks in your project. Ideally, you can check the project status and take accountability for the same.
Boost Performance Metrics and Reduce Backlog
There was no way you could have known how the code worked in real time earlier. But things have surely changed after the CI/CD deployment process.
With the pipeline, you can easily monitor the performance and efficiency of the app. Also, with the metric data, you can get actionable insights.
With the help of this pipeline – you have the time to do manual things that otherwise you can’t do on a manual basis. Also, you can fix the code functionality & improve the quality (with the pipeline). The best part is that you can fix non-critical issues before they become critical, and make it to the final production stage.
Wrapping up
Serverless CI/CD comes with many advantages – cost, scalability and easy deployment. Also, integrating serverless deployment in your pipeline can enhance early error detection and promote a faster release cycle.
By integrating with the CI/CD pipeline, you can achieve consistency across the entire project lifecycle. Now that you are aware of how serverless CI/CD is changing the DevOps landscape, it’s your time to leverage its benefits.
CI/CD pipeline is indeed the best approach to managing serverless functions in DevOps. Lastly, you can build the CI/CD workflows and automate the processes for service, language or AI model deployment.
