If you are an IT professional, you must have heard of the word DevOps at least once. Besides being on the rise, it is also a crucial part of the software industry. In fact, according to a survey conducted by Statista in 2020, 48.1% of respondents feel that DevOps is extremely important in scaling software development.
Although its implementation can be a bit challenging as it calls for advanced technologies and tools. A fusion of technologies such as Artificial Intelligence and Data Science can transform DevOps forever and for good.
But before diving into the “hows” let’s take a quick look at what DevOps actually is!
What is DevOps?
One of the reasons why DevOps is important is because it is a shared approach to the tasks performed by a company's development and operations teams, both of which are crucial departments. The term DevOps in itself carries “development” and “operations”.
In other words, you can say that DevOps is one of many techniques used to execute IT projects, in order to meet business needs.
This methodology is meant to improve the standard of work and process throughout the software or mobile app development. It is an infinite loop of planning, coding, building, testing, releasing, deploying, operating, and monitoring.
DevOps solves a number of challenges faced by a company such as:
- Releases that take too long
- Software that does not meet user expectations
- IT that limits business growth
Challenges in implementing DevOps successfully
DevOps surely is an approach that every company wants to implement but good things come with their own challenges. Organizations can face risks regarding data security in apps, variability in the testing processes, lack of communication, and many more.
Although these challenges can be overtaken easily by having a clear understanding of different practices and their specific principles.
But the challenges don’t cease here. One of the most serious challenges that most companies face during the implementation of DevOps is the adaptation of new technologies and tools in order to streamline the development, testing, and deployment of software or applications.
Luckily, AI can help be of great help in this scenario and can act as an accelerator for DevOps implementation and functioning.
Need for aligning DevOps with AI and Data Science
The need for aligning DevOps with the latest technologies such as AI and ML is now more than ever. With these technologies making waves in every branch of the IT industry, it’s time to implement them in the development and operations departments as well.
1. DevOps and AI
Many companies now have made it important to use AI for DevOps for the streamlined delivery of high-quality solutions. And we cannot agree more with this decision. As per research by Gartner, by 2023, 40% of DevOps teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability.
Implementation of AI in departments like testing and operations can do wonders for an organization. It can timely and efficiently detect errors and problems that in turn promise a better DevOps implementation.
2. DevOps for Data Science
DevOps and data science is another powerful combination. Disciplines like machine learning when introduced in DevOps, can help in the simplification of complex data sets and can also help in detecting inconsistencies in the data.
This can solve problems like slowing down the process. Sometimes there are QA errors or irregularities that interrupt the testing process. ML can solve these problems.
Data Science and AI in DevOps for better business outcomes
Both data science and artificial intelligence can completely revolutionize DevOps and can boost your company’s growth. AI helps in automating DevOps processes with apt consistency. Not only does it reduce errors in the automation processes but also there will be a lot of free valuable resources that can be used elsewhere.
AI also helps coders and programmers write better codes while also recommending solutions for errors. This will automatically make the quality of codes ten times better. Requirements management can be highly streamlined by AI which can be great for the entire project.
The tech market is ever-evolving. Hence organizations need to implement AI systems in their processes. AI and ML can help developers to know what they need beforehand thus accelerating DevOps strategies leading to better business outcomes.
Conclusion
DevOps is going to gain much more significance in the years to come. So it’s time to enrich this approach even further by integrating it with AI and data science. Both these technologies bring new dimensions to DevOps.
It is a great way of reaping the benefits of both these technologies while also keeping the company processes streamlined.
If you are looking for a firm that provides DevOps services equipped with the latest tools and technology, then look no further. Connect with us today.
