In this blog, we are going to explore How can a DevOps team take advantage of artificial intelligence (AI)? to build the right workflow.
AI can assist DevOps teams in the whole process of testing, coding, releasing, and displaying programs, and make them more efficient.
AI also helps the DevOps teamwork more effectively through increased automation, supporting the ability to problem solve and making it easier to work together as a team.
Therefore, how can a DevOps team take advantage of artificial intelligence? In this article, I will share with you 5 ways that artificial intelligence will change your life as a DevOps engineer
This article will help you see how AI can improve the efficiency of your DevOps team and bring you closer to reaching optimal efficiency as a whole.
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What is Artificial Intelligence(AI)?
The term artificial intelligence was first introduced by John McCarthy in 1956, He defines it as the science and engineering of making intelligent machines.
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Today, artificial intelligence is more and more used to describe computers capable of performing tasks that usually require human intellect, such as visual perception, speech recognition, decision-making, and translation between languages.
And how can a DevOps team take advantage of AI? Artificial Intelligence(AI) has been around for many years but only recently has it become widely available and affordable enough for use on everyday devices like smartphones or smart speakers.
Most people don’t realize how much they are using AI on a daily basis because they are not aware of its presence. Some examples include Google Translate or Apple’s Siri feature.
These technologies have made our lives easier; however, their capabilities still have room for improvement when compared to human ability.
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What is DevOps?
DevOps is an approach to software development that emphasizes communication, collaboration, and integration between software developers and information technology (IT) professionals.
It aims at establishing a culture and environment where building, testing, and releasing software is quick, continuous, and more reliable.
The term DevOps was first used in 2009 by Patrick Debois at Agile 2009, The term was then adopted by some as a way to unify various ideas and projects within the agile software development community with shared goals.
Many people consider DevOps as part of a wider set of principles and practices called agile infrastructure.
Although its main focus is on application deployment, it also includes other practices that make it easier for organizations to develop their applications faster while maintaining high-quality standards.
Why is AI needed in DevOps?
They would have to use it to improve the application performance and delivery, reducing costs and improving quality altogether.
The AI can be used to support DevOps teamwork more effectively through increased automation, supporting the ability to problem solve and making it easier to work together as a team.
AI helps DevOps teams in the whole process of testing, coding, releasing, and displaying programs so that they are more efficient.
And it can help the DevOps teamwork more effectively through increased automation, supporting the ability to problem solve and making it easier to work together as a team.
How AI is doing the Transformation of DevOps?
How can a DevOps team take advantage of artificial intelligence (AI)? AI is basically software that mimics human reasoning or problem-solving capabilities.
The most important thing to know about DevOps is that it has nothing to do with AI, Though plenty of people think they’re synonymous, they’re not.
AI is one of many technologies transforming DevOps, but it’s a particularly interesting case because it will impact each phase in its development.
Early on, AI could help automate some tasks that are time-consuming and require skill (such as doing code reviews), freeing up employees to work on more important things.
Eventually, they may even eliminate some jobs or take over others altogether.
Later, AI tools could provide assistance in automating tasks such as deployment or test execution.
It learns based on data or experience and can make decisions and predictions accordingly.
Top Benefits of AI in DevOps
While there are many ways that AI and machine learning (ML) can improve DevOps workflows, these three areas below demonstrate some of their key advantages: (1) Automation, (2) Problem-Solving, and (3) Creating Effective Teams.
1. Automation
The benefits of automation, in general, are well known in software development, but they’re even more important when you consider how much time it takes to complete certain tasks by hand.
For example, if your team is manually testing new features or code changes before they go live, AI tools like Applitools Eyes will be able to do it faster and more efficiently than any human could.
2. Problem-Solving
When faced with an issue, humans tend to rely on problem-solving skills that have been developed over years of experience.
However, machines don’t have preconceived notions about how things should work; they can take a fresh look at problems from multiple angles and come up with innovative solutions that may not occur to people.
3. Creating Effective Teams
Whether they know it or not, developers and IT operations team already use AI every day.
By bringing together different types of data into one place using visual dashboards, for example, teams can make better decisions more quickly.
This means less back-and-forth between departments, which makes collaboration easier for everyone involved.
How Can DevOps Use AI?
First, by automating manual tasks, means taking tasks currently performed by humans such as building/releasing code or troubleshooting production issues and having machines do them instead.
In addition to freeing up people for more valuable tasks, automation reduces errors and helps ensure consistent results from one job to another.
Second, by augmenting human problem-solving skills. By leveraging AI’s ability to process large amounts of data quickly and learn from past experience.
It is possible to help teams make better decisions faster when responding to problems in production environments.
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Top Functionality of AI use for DevOps
1. AI Can Help with Requirements Gathering
The first and most important part of developing any new software is figuring out what it needs to do.
Getting your requirements correct at this stage will help you build software that truly solves users’ problems and ideally, won’t create any new ones.
As AI systems get better at understanding natural language, requirements gathering with AI tools are becoming more common and accurate.
For example, IBM Watson Developer Cloud uses natural language processing to convert user input into structured data (like JSON) so developers can use it in their code.
This means less back-and-forth between stakeholders and developers, which saves time in building new features or fixing bugs.
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2. AI Can Help with Code Testing
While we should all be pushing for automated testing on our development teams, AI has already made great strides in that area.
AI will not only help to test code and improve its quality but will also assist with training developers on how to write better tests.
For example, AI programs like CodeDuck analyze existing code for bugs and train developers on how to write better tests based on feedback received from its analysis.
These programs have proven successful in reducing bug rates by as much as 50 percent! With fewer bugs, you’ll spend less time fixing issues and more time developing new features.
3. AI Helps with Automated Deployment
AI offers huge advantages for continuous deployment and automated testing, including easier collaboration and problem-solving.
With AI-assisted development, the software is tested at every stage in its development lifecycle to ensure that it’s ready to release.
If there are any problems with your code, you’ll be able to identify them quickly and fix them before they become major issues.
This saves both time and money since you won’t have to go back through your entire process just because one small part of your program isn’t working properly.
4. AI Helps with Monitoring and Alerting
When it comes to monitoring and alerting, AI tools are much better than humans. Instead of waking up at 3 AM because some line on an expensive machine is out-of-whack, let AI notify you if something is wrong.
In addition to more reliable monitoring and alerting, AI also makes sure your team doesn’t get overwhelmed with alerts.
After all, no one likes getting 20 emails about issues that aren’t urgent or important.
By using AI for monitoring and alerting, you give your team time to work on other projects without being interrupted by non-critical notifications.
In fact, you could say that today’s DevOps teams don’t really have time for non-critical tasks like manual testing.
Manual testing is slow and inefficient; not only does it take longer than automated testing (often 10x as long), but manual testing requires skilled engineers who are very hard to find in high demand and therefore very expensive.
5. Working Effectively as a DevOps Team
A DevOps team that works together, In order to streamline operations and take advantage of artificial intelligence (AI) in DevOps, effective communication is key.
Have One Voice When making decisions about where to automate or where optimize processes, it’s important for every member of your team to feel heard and part of a larger group effort.
If you don’t have one voice on your team, members may lose interest in contributing or communicating their ideas because they feel like they aren’t being heard.
AI can assist DevOps teams in the whole process of testing, coding, releasing, and displaying programs, and make them more efficient.
AI also helps the DevOps teamwork more effectively through increased automation, supporting the ability to problem solve and making it easier to work together as a team.
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Conclusion
If we summarize everything mentioned above, it is clear that artificial intelligence is a way to improve and enhance efficiency for both software developers and DevOps teams.
But to harness its full potential, you must see how you fit into that process. What are your best capabilities? How can AI support those skills? How could it help your team innovate more quickly or provide more clarity when needed?
By answering these questions and many others, your organization will be able to take advantage of artificial intelligence.
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