Today, you can use DevOps to make your AI delivery modem more effective. The fact of the matter is that flexibility, scalability, high quality, and speed have become hallmark elements for enterprises to drive growth. Gartner reports that 40% of professional DevOps teams will use infrastructure monitoring applications paired with AI by 2023.

In the quest to achieve digital transformation, DevOps teams focus on infrastructure apps that come with integrated artificial intelligence to power up their IT operations. According to a Deloitte report, startups that provide AI-based software development apps have increased by $702 million in a single year.

You may not realize it but the next competitive drive stems from artificial intelligence in the DevOps landscape. It is, after all, a rising technology that has had significant growth in a few years. More support, use cases, and benefits of AI-based automation make it ideal for DevOps. In time, there is a good chance more companies will integrate artificial intelligence into DevOps principles.

What is DevOps and its Advantages?

DevOps refers to a combination of practices that integrates software development and IT processes. DevOps makes it possible to test, build, and release efficient software. DevOps collects continuous feedback from the process and fills out inconsistencies between operations and development.

Typically, DevOps is famous for generating a multitude of data. This data becomes useful to monitor and streamline various processes and tasks. In this day and age, teams cannot handle massive data load and this is where AI comes into the picture.

It is hard to separate digital transformation from computing and AI is highly useful to make calculated and logical decisions. Ultimately, AI speeds up production and increases precision at the same time. Today, AI can automate a wide range of business processes that save time and boost efficiency. It is the main reason industry experts believe that it will be hard to separate DevOps from artificial intelligence in the foreseeable future.

Through DevOps engineering, companies enhance their processes and become more adaptable. It is vital to understand that AI makes machines highly intelligent. Once machines are accurately programmed, they start to mimic possible human actions for simple and complex tasks.

Benefits of DevOps

Here are essential perks for companies that decide to adopt the DevOps for their operational processes:

1. Ensure Stable DevOps Environment

Usually, the release of new updates or features can impact productivity standards. With modern-day DevOps practices, companies can balance their overall operations and ensure a stable work environment.

2. Ensure Faster and Frequent Deployment

One of the perks of DevOps is that it allows DevOps teams to make regular, instant, and fast delivery updates. This approach allows organizations to establish a robust presence in the market.

3. Automates Repetitive Tasks

A high degree of automation for repetitive tasks leads to more innovation. Unlike the traditional model, DevOps helps companies identify the main issues accelerating overall DevOps efficiency. Once automation tests repeated flaws, DevOps teams get more wiggle room to brainstorm new ideas.

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4. Improved Product Quality

DevOps improves collaboration across operation and development teams. Consequently, it simplifies the process to collect feedback leads and improve the overall product quality.

5. Minimizes Production Cost

With continuous integration and collaboration, DevOps minimizes the product and management costs for each department. In short, DevOps makes it possible to centralize new updates and maintenance.

6. Promotes Business Agility

With DevOps, companies can ensure agile business processes and get a competitive edge in the market. With more scalability, enterprises can transform their entire business.

7. Ensures High Productivity and Transparency

Once you cut out silos and focus on collaboration, it is bound to foster more communication across team members. Adopting DevOps practices also increases efficiency and productivity for all employees.

8. Ensures Consistent Software Delivery

Through the DevOps approach, all departments work together to maintain operational stability. This approach makes the undistributed and faster.

9. Effective Problem-Solving Approach

One of the hallmark aspects of using DevOps is that it allows organizations to address their technical issues in software management effortlessly.

AI’s Influence on DevOps

The production processes revolve around data and scanning through an endless volume of data at high speed requires AI capabilities.  Gone are the days when teams had to bear the burden of high workloads and compromise productivity.

Instead, companies can use AI and automate different aspects of the production processes. AI has also made automation for administrative and security aspects more efficient. It allows organizations to check more vulnerabilities and avoid potential breaches.

With AI computing, enterprises can make analytical and data-backed decisions efficiently. Whether it’s efficient app progress, software development life cycle, quality assurance, or early detection of issues, AI has had a positive impact on DevOps.

DevOps teams can use AI at scale via the operationalization models and across the production. Furthermore, DevOps paired with AI makes sure that the teams are using the proper AI-based delivery model to increase flexibility and make the digital transformation. DevOps integrated with AI supports continuous delivery and deployment of models at higher quality, stability, scalability, and speed.

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How Can Companies Apply AI and Optimize DevOps?

Ideally, your company should have a proper roadmap before you can see the transformative results of DevOps and AI. Here are some of the considerations that can help you optimize DevOps with AI:

Evaluate Your Needs First

When it comes to AI, most organizations understand the urgent need to move to a new model. But moving from traditional to the modern model can become complicated. So, before your company integrates AI for DevOps, make sure to assess relevant requirements to make the final transition. 

Roll Out Effective DevOps Culture

Once you implement an effective DevOps culture, you will be able to develop and collaborate better. Make sure there is a unified perspective across departments or teams and set specific priorities to ensure AI integration with DevOps works out.

Collaboration and Budget Planning

Make sure to measure every change and encourage more collaboration among teams. You should be able to break down silos and have foster more communication to ensure easy access to data. Similarly, make the right estimations and then plan your company’s budget. Before you decide to adopt an AI model for DevOps, take into account the potential expenses your company will have to bear throughout the integration process.

Bring Everyone Up to Speed

If you want your company to integrate AI to optimize DevOps, you will need to affirm and reaffirm that all team members are on the same page. On the surface, it may sound straightforward, but this consideration will probably take more time to integrate AI with DevOps.

If you want to transform your dedicated work environment, ensure team members and departments are ready to adopt the new model and bid farewell to the traditional tech setup. For instance, you can educate tea members about how AI would optimize DevOps.

Don’t Automate Everything

To take full advantage of artificial intelligence and optimize DevOps, you will need to make incremental organizational changes. Big changes have small beginnings and you need to make changes that can have a positive impact. In any case, the last thing you want to do is automate everything in the process that may make your DevOps tasks more complicated.

Focus on High User Satisfaction

Unlike traditional models, AI does not take days or weeks to collect feedback and roll out new updates or changes in the software. Companies can abandon the traditional approaches and test different development phases through AI to render high satisfaction.

Choose the Right Tools

Also, make sure to improve your security parameters and ensure continuous integration and continuous delivery.  The fundamental component to transform DevOps with AI also requires using the right tools. So, choose the tools that cater to “your” It environment.

What Issues Can AI Help Resolve in DevOps?

As an advanced technology, AI has become highly efficient to address and mitigating operational issues of DevOps. As industries continue to transform at an unprecedented rate, AI has become integral to resolve DevOps’ complexities.

Improved Security

DDoS (Distributed Denial of Service) has become highly active and targets all types of companies and sites. With artificial intelligence, DevOps teams use innovative and creative methods to identify, address, and manage security risks. For instance, DevSecOps can use AI to improve overall security and a centralized logging mechanism to detect any threats or anomalies.

Software Testing

DevOps teams use different types of testing like regression testing, functional testing, and user acceptance testing. A good chunk of data is rendered from various tests. With AI and machine learning, DevOps teams can identify the specific pattern and collect relevant data to ensure the right coding practices ad spot errors.

Fundamentally, AI improves the software testing and development process for DevOps teams. And teams can use AI-based data to boost efficiency.

Fast Data Access

DevOps generates a multitude of data that creates more issues for teams. With AI and machine learning, data accessibility becomes more flexible and allows DevOps teams to compile and test data from various sources. AI also helps teams to organize and analyze data to get the big picture.

Efficient Implementation

In the DevOps space, it takes human expertise to manage a dedicated environment. But the transition to a self-sustainable environment allows DevOps teams to perform tasks efficiently. Once AI comes into play, it requires minimal or no human intervention. It saves up time for teams to drive more innovation.

Feedback Loop

The fundamental DevOps function is to gather data from different phases. With machine learning monitoring tools, DevOps can leverage features like log files, performance matrix, datasheet, etc. DevOps can use these focused suggestions and use them for different purposes.

Dedicated Alerts

DevOps create a long list of alerts without priority tags. As a result, it becomes incredibly difficult for the team to process all alerts. Through AI and machine learning, teams can prioritize dedicated alerts using alert sources, alert intensity, and past behavior.

Can AI Replace DevOps?

In 2022, it is no secret that AI supports enterprises with improved service personalization, data protection, and customer interaction. A GitLab survey highlights that over 4,300 managers and developers believe that some companies release their code 10x times faster. In the survey, up to 80% of respondents agree that releasing code is faster through AI integration.

The truth is that AI is changing the methodology for DevOps teams to use and interact with data. And AI-based tools allow DevOps teams more freedom to make better decisions and trust shared tools to resolve technical errors. Still, the pairing of AI and DevOps is in the early stages and AI tools are not advanced enough to replace the entire DevOps anytime sooner.

In the age of information, AI facilitates DevOps teams to automate a variety of operations and processes. It would be fair to state that AI is bound to transform “how” humans perform tasks. As transformative as it may be, this “change” will be gradual rather than imminent for DevOps.

Nonetheless, the fact remains that DevOps and AI combo is the ideal way to code, test, and compile software efficiently. Not to mention, AI steps up the automation game for DevOps teams. Remember, AI can spot and resolve problems quickly and foster more collaboration and productivity among DevOps teams.

In hindsight, organizations need to view DevOps as the start of a business-centric journey that can become automated in the coming years. And as the IT environment becomes automated, DevOps teams need AI more than ever to manage complex tasks. Companies can expect the AI-based DevOps approach to kick off in the next five years. This transformation will radically transform human involvement and IT operations.

Final Thoughts

In 2022, DevOps and AI offer a transformative solution for enterprises. The good news is that many organizations that started to adapt and embrace AI solutions to make the most out of intelligent automation. Besides, it makes perfect sense to speed up development tasks and data preparation through AI and achieve scalability.

Of course, humans are not capable to process a large volume of information and compute endless operations. But DevOps can use valuable AI tools to computer and analyze the development and deployment process altogether. But before artificial intelligence can transform DevOps, organizations will have to view DevOps and AI in tandem.

When it comes to AI operationalization, there is still room to raise more awareness and address complex issues. The time is now to harness the power of AI and make it part of the business model. In retrospect, the DevOps future is bright and AI is at the centre of it.

Research & analytics team

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