Artificial Intelligence (AI) has become something of a staple in modern life, it has proven to help and advance many different industries through machine learning, and DevOps teams are also reaping the benefits of these AI systems.

One of the most important areas is security and how AI is increasing efficiency throughout the software development process. AI is used to help identify and problem-solve a lot more quickly and efficiently compares to humans, which is why AI-enabled monitoring tools are being used to assist DevOps teams.

What is DevOps?

If you are not aware of what DevOps is, then you are not alone as it is not something that is well-known to the average person, so it may need a little bit of explaining for people to understand exactly what it is and how it can be used.

In basic terms, DevOps is a set of practices that enables software teams to develop, test, and deploy software faster and more reliably. It combines software development and IT operations, allowing for faster software releases and fewer errors.

It helps evolve and improve products at a faster pace, while also providing better reliability and security. DevOps also integrates development, operations, and quality assurance teams to create a more efficient work environment.

Companies often collaborate with DevOps consultants (for information on devops consulting click here) to leverage its true potential and ensure the successful implementation of DevOps practices. Needless to mention, DevOps is an invaluable tool for any organization that wants to stay competitive in the fast-paced and ever-evolving tech landscape.

What is Artificial Intelligence?

You may have heard of Artificial Intelligence more than you have with DevOps, as it is practically everywhere from healthcare to retail.

It performs multiple tasks that surpass human intelligence by working at extreme speeds to shorten time-consuming tasks and move a business or organization forward.

It can automate repetitive tasks, manage natural language processing, have speech recognition, conduct decision-making, and have visual perception, plus it can automatically test modifications by using AI-enabled testing tools to make sure there are no bugs in software (which is great for DevOps teams to use).

It has been around for a number of years, but it has suddenly had a boom, and it seems to be everywhere completing complex tasks and doling out automated testing.

Why Should Artificial Intelligence & DevOps Be Used Together?

Artificial intelligence will help out DevOps teams in big ways as it can help analyze data on resource utilization as well as be trained to recognize potential security threats, e.g. someone trying to access sensitive data.

AI will be able to support a DevOps team so they are able to work a lot more effectively by increasing automation, helping with problem-solving needs, and bringing them together as a team.

AI can be used to identify underutilized resources to see what else can be done and how they can optimize their usage.

Evidently, AI can be used to make things a whole lot easier for DevOps teams, so putting them together looks to be one of the best ways for automation to be used.

Implementing AI in DevOps

When you are planning on implementing an AI system into your DevOps, you need to think about a few things before doing so to make sure you are on the right path.

Management of Data

Data management is incredibly important when using AI, and when training AI models, DevOps teams need access to data sets, which have the potential to be time-consuming as well as expensive when going through the gathering and categorizing process.

AI will need constant upkeep and improvements when new data is gathered, so it has to be looked into carefully to see which areas are needed most and how they can be used.

Ethical Issues

AI systems are very intelligent machines, so when they start to advance, their judgments will also adapt which will affect actual people’s lives.

As AI is everywhere now, it is important that they develop a moral center to help make the best decisions for whatever software they are implemented in.

The Caliber of The Data

If DevOps teams want to have the artificial intelligence they use to function efficiently, then they need to make sure that high-quality data is being used. If the data is faulty then the AI will not make good judgments and cause issues to crop up.

How Can a DevOps Team Take Advantage of Artificial Intelligence?

Now you know what Artificial Intelligence is and the background of DevOps, it is now time to go in-depth on how they can be used together to create efficient and progressive output, from predictive maintenance to automating repetitive tasks.

Improved Decision-Making

AI can support DevOps teams by helping them make more informed decisions through the analysis of data which can help them gain insights that humans may have missed or not have seen right away.

An AI will see potential issues through pattern recognition and trends, after it has gathered this data, it will be able to offer solutions to resolve these issues, or let the DevOps team know what to do in certain cases.

Automation of Repetitive Tasks

Asking AI to perform repetitive tasks that are time-consuming can be incredibly beneficial for a DevOps team as they will be able to focus on other, more pressing, issues that will need their full attention.

Instead of focusing on looking at errors or performing everyday tasks that need to be done, Artificial Intelligence will be able to handle these in a quicker amount of time, so if there is anything that comes up, it can be flagged for the DevOps team to look at and sort out if needed.

Enhanced Security

Using AI to identify any security threats will help protect all systems from potential attacks that could lead to big security breaches within the team.

AI can alert teams to security breaches or threatening activity and tell them how they can handle it as well as recommend other ways that it can be dealt with.

Predictive Maintenance

This type of AI support will help with predicting if a certain type of software or equipment will likely fail so that teams can fix it before it gets any worse or breaks down completely.

Looking into things such as temperature as well as vibration data, then analyzing it, will help with seeing what could potentially happen.

After this has been noted, the scheduling of maintenance can happen without there being a break to fix problems that could have been handled earlier.

Conclusion

Now that you are aware of how a DevOps team can use Artificial Intelligence within their organization, you hopefully, know a lot more and can see what the benefits are for each side.

As the need for Artificial Intelligence grows, so many other areas are looking at implementing it to grow their business and support what they do. It will certainly continue to be a staple in years to come.