AI, with its ability to learn and provide invaluable insights that enable higher efficiency and productivity, has found its place within the DevOps ecosystem. The convergence of the two has led to a new era of development addressing not only the issues businesses face but also improving DevOps capabilities. According to the recent statistics by Gartner, by 2023, approximately 40% of DevOps teams will incorporate AI into their IT operations platforms. 

While DevOps teams can use AI in developing, testing, monitoring, enhancing and releasing, AI can enhance DevOps processes and workflows in a number of ways. In this blog, we will dive deeper into how DevOps teams can take advantage of AI to bring their processes to a much higher level and we will touch upon future trends that will shape the use of AI. We will also try to uncover the best tools you need to use to enable DevOps with AI. 

Here are the best ways DevOps teams can leverage the power of AI:

Continuous security and compliance 

Automation plays a big role in generating and running test cases and this is where Devops can take advantage of AI. Here are a few best practices which organizations can implement in their DevOps strategies to continuously improve their software security: 

Integrate AI into the testing process to enable autonomous testing — This way, you can optimize existing testing efforts, eliminate test coverage overlaps, and accelerate progress towards defect prevention. 

Automate compliance requirements — Through automated compliance tests, you can verify that all the requirements have been fulfilled and that you can now proceed with the production. These tests can be of different complexity, ranging from comprehensive frameworks to simple test collections. 

Automate quality gates — Automated quality gates help automatically verify whether a software component meets all the requirements so that all the features can be deployed to production. 

Improved decision-making 

AI can process vast amounts of data and provide actionable insights for the teams which further helps them identify trends, patterns and anomalies. This helps DevOps teams, particularly in financial institutions, to make fact-based decisions. Here are a few steps you should take to establish a data-driven culture in DevOps: 

• Leverage the existing data source
• Provide relevant stakeholders with the data automatically
• Focus on data-driven solutions for impact 
• Consider the power of DevOps 
• Measure the impact of DevOps through data-driven approaches

Streamlining repetitive procedures through intelligent automation 

AI can bring enormous benefits in terms of automating routine tasks such as configuring resources and provisioning, monitoring infrastructure and deploying applications. This provides DevOps teams with more time to concentrate on strategic work and more complex tasks. On top of this, AI, for instance, can allow DevOps teams to focus on more technical issues by using AI-powered chatbots to handle customer inquiries. 

Continuous monitoring 

By constantly monitoring applications and infrastructure, monitoring enabled through AI can warn DevOps teams of potential issues before they occur and become serious. This can help not only improve performance and dependability of programs, but also reduce downtime and cut costs. 

Efficient troubleshooting of defects 

Rigorous software QA processes are required to eliminate bugs and errors. QA tools powered by AI increase efficiency in identifying potential failures within applications. According to Delloite’s report, the implementation of AI has significantly accelerated the application delivery process, which resulted in 72% reduction in time-to-restore. Also, DevOps teams have taken advantage of AI to optimize performance, configure app settings for customer deployments. 

Cost-reduction 

One of the biggest advantages of AI is automation. By automating processes and procedures, a lot less people are required to do their job which directly leads to more cost savings.

Resources optimization 

From using capacity planning to predict future resource needs to allocating resources with AI-powered load balancing systems, AI can help optimize resources in many different ways. By analyzing potential future issues, AI can enable you to plan usage of resources more efficiently and faster. By reducing the number of resources, you can also reduce costs and focus your efforts on something that brings value. 

Enhancing customer engagement 

Through AI, DevOps teams can have a valuable insight into customers’ needs and requirements and use those insights to enhance customer satisfaction and enhance customer journey in the long run. By understanding customers’ pain points, DevOps teams can pinpoint the areas which need improvement and then bring customer satisfaction to a whole new level. 

Best AI-enabled DevOps tools

Virtual assistants: Virtual assistants can help automate monotonous operations such as running code modifications 

Chatbots: AI-powered chatbots can help developers resolve issues more quickly

AI-powered testing tools: Developers can use these tools to automatically test modifications to the code to ensure there are no bugs 

AI-enabled monitoring tools: These tools can help detect issue

Frequently Asked Questions on how DevOps teams can take advantage of AI

How can AI enhance the quality of software developed by DevOps teams?

AI can be used to analyze the code as it is being written providing valuable feedback and suggestions on how to improve the code. It also helps identify issues and troubleshoot them more efficiently. 

How can DevOps teams implement AI in their workflow?

Prior to implementing AI, DevOps teams should consider and analyze their goals and needs and then choose technologies and tools that would perfectly meet those needs. Ideally, DevOps team should have trained AI experts on their team and they should focus their efforts on establishing DevOps best practices for using the technology. 

How Can AI Improve The Efficiency Of DevOps Teams?

Through automating repetitive tasks, such as testing and deployment, AI can free up time for developers to focus on more important tasks.

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