DevOps is now becoming the modern work culture followed by several development companies worldwide. It is a tool with the cultural philosophies and practices used to speed up the system development life cycle. Apart from that, DevOps practices help development companies to deliver high-quality software or products consistently.
Unlike other development-supportive tools, DevOps supports agile methodology, which is best for enterprises, developing software and products. Experts have projected the global market size of DevOps is USD 14,969.6 million by 2026, at 19.1% CAGR.
The advancement of AI/ML technology has emerged with DevOps to make it more vulnerable for enterprises to develop future-proof products in the recent past. Artificial Intelligence (AI) has numerous things to deliver to the IT sector, and it keeps evolving year by year. The introduction of AI technology in DevOps will improve the process efficiencies and consolidate the entire development operations.
This blog briefs about the transformation of DevOps tools across the globe because of the implementation of AI technology.
What is DevOps?
Before getting into the core topic, let’s discuss some basics about DevOps. DevOps is a combination of tools, processes and technologies that compound Development (Dev) and Operations (Ops). The tool unifies the developing people and processes involved in the development lifecycle and modern technology to deliver quality software that will provide more value to the consumers in all terms.
DevOps plays a significant role in the product development life cycle, IT operations, quality engineering, and product security. The tool coordinates and collaborates with the entire department’s operations to develop a better and more reliable product or system. It transforms the traditional infrastructure of a company and introduces automation & accelerates processes involved in the business operation. This enables companies to deliver and serve better to their consumers.
In addition, it helps companies to achieve their goals faster and to compete in the market effectively. Take a look over the 6 phases of the DevOps development lifecycle.
1) Planning
2) Building
3) Continuous Integration & Delivery
4) Monitor & Alert
5) Operate
6) Continuous Feedback
As mentioned earlier, DevOps is a combination of people, tools, and culture, so every person in the development team must understand the value. However, a typical team structure followed by several companies acts as an operational barrier and makes it hard to adopt a DevOps culture. The upcoming section briefs about the challenges of DevOps. Take a look.
Common Challenges Companies Face Because Of DevOps
Many companies across the universe see DevOps as a challenge instead of an opportunity to grow. The typical team structure followed by companies fails to understand as DevOps is a never-ending development process that requires continual improvement. Companies can take their product development lifecycle process to a new level with DevOps.
Here are the lists of a few common challenges companies face during the implementation of DevOps and what to do to overcome those challenges.
1. Development & Operations:
The ultimate aim of DevOps is to bring a collaborative workforce to deliver quicker and better results. But different teams involved in the development process fail to understand the concepts, making it more difficult.
The developing team always plays with code and tries some innovative coding processes to develop a better product. However, the operation team always looks for the highest quality in all aspects of the products, including their features and functionalities. So, they always consider developers using untested codes and start testing the product by considering them sloppy products. This delays product launch because two different teams work with different mindsets and objectives.
Companies should blend the development and operation teams with a single mindset to achieve business goals to overcome this challenge.
2. Cultural Changes
Workplace culture determines the maximization of productivity. Implementation of DevOps forces workplace culture to witness a high amount of changes. Being a separate culture, DevOps collaborates with the existing work culture of a company and makes it hard for the team to adapt quickly.
To overcome this challenge, business stakeholders should teach their workforce and prepare them to face the changes. In general, cultural change in a company is not a short-term process. So business leaders running a development company should start with proper training programs to team their team before DevOps implementation.
3. Process Change
Almost every development company has its guidelines and frameworks for software development. However, implementing a DevOps tool that unifies the development process to improve work efficiency will be tough for companies to stick with their uniqueness. This is because there is no central team and any fixed frameworks to follow for the development process offered by the DevOps tool.
In such cases, companies might face challenges when their teams with different mindsets and skill-sets work together in the development process. This may lead to work ethics conflict and significant delay in productivity.
Business leaders or companies should let their development teams and process teams choose their framework to overcome this challenge. By doing so, there won’t be any conflict in project development.
4. Company’s Vision
The main objective of the DevOps tool is to create collaboration among multiple teams and process the project activities with a collaborative workforce. By doing so, the development lifecycle will be more efficient and can deliver high-quality products.
DevOps integrates multiple teams and carries out the development process under a single supervisor, unlike other development tools. So if any issue arises during the development process, business leaders should address it as a whole. However, business leaders and companies handle the issues differently by pointing them to the development and operation teams separately.
This shouldn’t be like that; it may lead to DevOps failure. Business leaders and companies should collectively discuss the issues and resolve them to avoid such problems.
Impact Of Artificial Intelligence (AI) in DevOps Tool
Modern businesses prefer a data-driven approach to their business process. However, handling a large volume of data in a quick phase would be a big problem for companies, especially in the case of using the DevOps tool, which unifies the entire development process together by collaborating with all teams. With the introduction of AI & ML, this issue will resolve and will lead to time reduction by reducing the human interface in handling data. Thanks to the automation procedure of AI & ML.
Apart from that, here are some benefits of AI and ML in DevOps. Take a look.
– Quality Checking: The automated process initiated by AI will deliver more effective quality checking. Also, it helps testers to build more comprehensive test patterns.
– Security: Integration of AI with DevOps will secure applications enormously. Based on the behavior pattern, AI eliminates the presence of unauthorized codes during the development process.
– Issues Identification: With the help of AI, the DevOps team will be able to identify the issues at an earlier stage and resolve it in time. This ensures the product meets the expected performance level.
7 ways AI is transforming DevOps
The AI-driven DevOps will explore the new potential and transform the entire DevOps operation to the next level. This section elaborates how DevOps transformed because of Artificial Intelligence (AI)
1. Improves DevOps Productivity: Introduction of AI in DevOps improves productivity significantly because of its autosuggest code segments. Also, the snippets used by the AI in the real-time process accelerate the development process. The automated process carried by AI increases the accuracy of data handling, owing to the error ratio decreases and productivity increases.
2. Improves Data Access: Often development teams using the DevOps tool suffer a lot because of unfettered access to the data. But this issue will be resolved with the introduction of artificial intelligence. The AI will liberate the data access among the teams by eliminating all the hassles involved in accessing the large data pool of an organization. In addition, AI can collect data from multiple sources and systems. Also, it organizes the collected data together, helpful for easy access and repeatable analysis.
3. Smart Resource Management: Artificial Intelligence (AI) in DevOps is well-known for its ability to automate the process and ease the process of repeatable tasks. By carrying out the repeatable tasks more efficiently, company resources can be utilized more efficiently. Also, AI keeps evolving to eliminate the complexity of introducing automation in the work process. This will reduce human intervention and allow employees to focus more on other productivity.
4. Fast & Accurate Error Debugging: Artificial intelligence in DevOps eliminates all the hassles involved in the debugging process. AI makes the error debugging process much simpler and less stressful. Apart from easy error debugging, DevOps with AI identifies and resolves the errors on its own. This saves a lot of time, leading to more productivity.
5. Supports Remote-style of Working: With the DevOps tool, remote working is a big challenge, but it can resolve easily with AI. AI increases the integration of data and workflows in a single platform. This allows employees to work remotely in the software development cycle.
6. Improves Collaboration: DevOps with AI increase the collaborative process between the development team and operation team with the minimum disruption of systems. Also, it empowers teams to view the entire system in a single unified way and allows them to understand the system completely. This enables the development team to identify the errors and rectify them easily.
7. Faster Root Cause Analysis: Often the developing team fails to detect the failure root cause and focuses on rectifying the errors. This will lead to the cause of other errors. However, DevOps with AI follows a specific pattern to determine the root cause of the failure. This enables teams to fix the root cause of the problem and eliminates the chances of repeated error occurrences.
Will AI Transform DevOps?
With the presence of AI in DevOps, DevOps would act as a perfect element to reduce human intervention in handling a large volume of data. Apart from fast data handling, AI in DevOps helps teams predict user behavior and experience for efficient project development.
Without any second opinion, the introduction of AI in DevOps will lead to a safe, efficient, and much faster software development lifecycle.
