Benefits of Integrating AI in DevOps
Artificial intelligence and DevOps are two different terms, but they are interdependent and interrelated. The future of a successful DevOps transformation mostly depends on AI. AI and DevOps – what are they? What are the benefits of AI that is helping to transform DevOps? You will be able to learn about all these things from this article.
What is Artificial Intelligence?
Artificial intelligence is how machines are made to behave and think like human beings. From beginning to end, it can completely mimic a human being to complete complex tasks.
What is DevOps?
DevOps is a set of practices to combine both developers and operators to perform together in developing software. It reduces the gap between the teams and speeds up the process.
DevOps Challenges
DevOps teams often face challenges like:
1. A high degree of complexity
2. Deal with the vast amount of data
3. Analyze the data and solve issues, etc.
Don’t worry. Integrating AI in DevOps provides multiple benefits to overcome these challenges.
AI in Transforming DevOps
AI with machine learning helps to resolve all the issues to transform DevOps successfully. Here are the benefits of integrating AI into DevOps:
1. Accessibility
DevOps teams continuously generate data. Members often find it challenging to manage and arrange them. AI helps to collect the data, organize them, and only provide the necessary information needed. ML analyzes the data and visualizes the trends.
2. Safety and Security
Organizations are always concerned about security issues. AI uses ML to scan previous data and learn about the patterns to detect internal and external threats. Then, it takes auto actions against threats using algorithms.
3. Testing
DevOps teams need to perform various testing to ensure quality. There are three main testing types: regression testing, user acceptance testing, and functional testing. AI can produce sufficient data and identify errors to enhance efficiency.
4. Alerts
DevOps teams receive multiple alerts per day. Manually handling all the noises on time is impossible. Some of these alerts are not necessary at all. AI separates the issues according to priority and sends the urgent one first. In some cases, AI auto solves less essential noises.
5. Feedback
Members are required to collect feedback from every stage to enhance the quality of monitoring tools. Artificial intelligence can auto collect feedback like matrix, datasheet, log files, etc., using machine intelligence. Developers use this feedback to improve the performance of the teams.
AI increases the efficiency of DevOps teams and helps in innovation, reduces errors, increases speed, productivity, and quality, and manages complex data. To survive in this complex software industry, integrating AI into the DevOps team is the best solution to follow.
