Published on January 16th, 2022 | by Daniel Jackson


How Automation is Changing DevOps for the Better

The DevOps philosophy of communication and interaction between development and operations naturally lends itself to the automation of DevOps processes. In essence, the fewer time developers and operations managers spend on repetitive tasks and back-and-forth talks over bug fixes, the more time they have to innovate for your company.

Enacting the cultural shift to a DevOps mindset poses enough of a challenge on its own, and you may be intimidated by the idea of shaking up your existing workflows by integrating automation.

But automation ultimately provides several benefits that outweigh the initial growing pains in the long run. Here’s how automation can benefit your business right now and how it’s pushing DevOps into the future.

What is DevOps Automation?

First things first, let’s clear up the relationship between DevOps and automation.

Automation clearly serves the overall goal of DevOps: reducing friction, miscommunication, and overall development-to-launch time for developers and operations teams. Automating business processes and clarifying lines of communication between the people who build your product and the people who keep it running directly leads to a smoother development experience overall.

To that end, automation has become the biggest tool for enacting DevOps systems. However, it’s not the only tool and it doesn’t magically guarantee success on its own.

For example, successful DevOps integration requires channels of communication between the two teams and free access to each others’ logs and data to track down bugs. DevOps remains as much a mindset and set of cultural standards as it is a nuts-and-bolts set of protocols between teams.

To understand how automation improves the state of DevOps, let’s take a look at some of the processes most typically automated in the name of DevOps integration.

What Kinds of Processes Get Automated?

One of the biggest tenets of DevOps is increasing productive communication between teams and creating a quality assurance feedback loop to prevent lengthy delays in patch delivery. Some of the most common forms of DevOps automation include:

  • Continuous Integration (CI)
  • Continuous Delivery/Continuous Deployment (CD)
  • Infrastructure management
  • Monitoring (infrastructure, software, and logs)

Of these processes, monitoring holds some of the most obvious benefits. Monitoring servers to ensure they stay below load capacity, for example, prevents unexpected outages. Automatic monitoring of logs also helps you identify issues before customers have to file a formal bug report, so that ideally you can reduce the turnaround time for fixes.

However, it’s worthwhile to examine CI/CD and infrastructure management in more detail to better grasp how automation improves these processes.

Automation and CI/CD

Continuous Integration and Continuous Delivery/Continuous Deployment form a system of automated code testing and deployment that leads to cleaner, more functional code to your customers at a faster rate.

Because CI automates build and performance tests for each update before it becomes integrated, it ensures that all updates feature reliable code. When development teams approve code updates on a daily basis, the value of CI shines. Without rigorous testing before integration, devs may end up wasting time on wild goose chases tracking down which update caused the problem.

CD, in either form, delivers this rigorously tested code to your customer as soon as it passes approval. This speeds up the delivery process and reduces the wait time for customers expecting updates.

Automated Infrastructure Management

When it comes to scaling infrastructure, businesses frequently struggle to quickly deliver what their devs need while maintaining network security. Any delays in getting devs the infrastructure environment necessary for building to begin end up passed on to team members involved in later steps of the development process.

Automation eases the strain of scaling by standardizing infrastructure environments. Instead of manual configuration of servers, tools for Infrastructure as Code (IaC) automatically build environments and test them according to the same principles as CI/CD. In the same way, automation reduces the need for operations to manually manage infrastructure documentation and monitoring.

A more concrete, smaller-scale example of infrastructure automation is automated denials, which deny code changes that would push infrastructure costs or computational stress over a certain threshold. This avoids unexpected strain on servers and lowers the possibility of a surprise outage.

How Automation Improves DevOps Systems

Automating your DevOps processes improves the efficiency of your DevOps system in three major ways:

Reducing Human Error

The most direct benefit of all, reducing human error, will cut out hours of post-launch bug fixing and backtracking during production. This is the area where automation has been picking up the most steam for a long time in business operations, far beyond DevOps.

Increasing Productivity

Once the most repetitive and easy-to-botch tasks are automated, your employees can focus on the work that truly requires a human touch. This ultimately leads to better software, since your devs can spend more time working on fresh projects and features and less time cleaning up older code and chipping away at menial tasks.

On the operations side, IaC smooths the transition as software changes hands from development to operations. The standardization of development and infrastructure environments leads to less miscommunication, confusion, and time spent tracking down errors.

Image by Freepik

Faster Fixes and Lower QA Time

Lastly, creating a feedback loop between operations and development speeds up the QA process. Automated testing reduces the likelihood that your code will need desperate last-minute fixes, and automated log documentation and monitoring makes addressing bugs easier and faster.

How DevOps Automation Improves Customer Experience

When you automate your DevOps processes, your workflow improvements get passed on to your customers.

Customers get frustrated in proportion to how long they have to wait for software to become usable again. The combination of fewer human errors and faster QA time keeps this frustration to a minimum.

The work time devs gain from automation leads to bigger, more innovative updates delivered with fewer delays and greater consistency. This keeps customers engaged and satisfied with your product.

Overall, automation can lead to sizable returns in the form of customer satisfaction and retention.

How Do You Decide What to Automate?

Hypothetically, any DevOps processes that can be automated should be—and you have your pick of a wide array of software to get the job done. But identifying what DevOps processes most need to be automated is the key to integrating automation successfully.

One of the most difficult aspects of DevOps integration is uniting both teams without operations getting all the attention. Your developers will just remain in their corner and tap away at their keyboards as if nothing changed.

Successful automation begins with an audit of your current development and operations workflows, analyzing how each team’s time gets used, and where they commonly experience breakdowns in communication.

It also requires getting teams on the same page both technologically and culturally, so your product doesn’t become an “Ops problem” as soon as it leaves your developers’ hands.

Trends in DevOps Automation

If automation already plays such a large role in DevOps today that the two frequently get conflated, expect worse confusion as the field grows. The role of automation in DevOps will only expand from here.

In particular, machine learning/artificial intelligence holds great promise for automation and the addition of security teams into the DevOps fold will introduce new workflows to DevOps teams.

Machine Learning and Artificial Intelligence

Artificial intelligence makes for an automating tool that is as powerful as it is versatile. As a subdiscipline of artificial intelligence, machine learning allows an application to adapt itself based on datasets provided by devs or through its own experience.

Machine learning has applications in many of the same processes as standard automation. Some current uses include monitoring infrastructure usage and capacity and code completion algorithms, which reduce development time by auto-completing functions, classes, and other aspects of code.

It’s hard to overlook the price tag attached to integrating machine learning and artificial intelligence in 2022. Still, they make up one of the most exciting avenues for DevOps automation to grow in the future.

DevSecOps Automation

Another promising development is DevSecOps, which integrates security into the DevOps relationship. Automation for network security can take on processes like code analysis to detect security risks, cyberattack simulations, and vulnerability testing.

In 2020, a study by StackOverflow found that 44% of organizations had at least one dedicated DevOps specialist. Expect to see more DevSecOps roles emerging (and new tools to interface with their challenges) as the field continues to expand.


DevOps continues to grow from its humble origins as a vague idea to a complete area of study performed between an increasing number of dedicated professionals. Automation has been the major engine behind this growth, as it proves the feasibility of DevOps and promises further innovation as more businesses adopt it.

While integrating DevOps automation can seem daunting at first, successful automation yields major benefits in the long run. Any business can benefit from reducing human error and QA time with increased productivity and customer satisfaction. Don’t be afraid to take the leap.

Cover Photo by Freepik

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About the Author

Daniel is a community manager for NI (formerly National Instruments), where they create the tools needed for companies to Engineer Ambitiously™. His current interests are at the intersection of software engineering and DevOps. Outside of work, he is a marathon runner and is working on his first novel.


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