Why DevOps Technology is the Best Option for Enterprises
DevOps has shifted the paradigm of Information Technology industry. It has evolved big time and has become the main focus in the world of software. According to Statista, there is a 17 percent increase in DevOps adoption in the year 2018, and it is expected to grow even further in 2019. Here are a few points which make DevOps an ideal technology for enterprises in the future:
Focus on DevOps assembly lines: Continuous Integration (CI) pipelines show the entire project, from source control to production. Enterprises are focusing on continuous delivery rather than continuous integration. Efforts are being undertaken automate the whole software development process.
Automation: There are six stages in a DevOps cycle. The key is to apply automation between these stages. Enterprises are looking to apply automation as it will make the application less error-prone and fast. Organizations are also looking for zero-touch automation in the future.
Adoption of microservices architecture: Microservices don’t create any dependencies as they are independent entities. If something goes wrong, it doesn’t break any other systems. Companies are increasing microservices architecture in their DevOps platforms. It will help to improve the runtime and assist in the efficient delivery of products and services.
Kubernetes is going to emerge: Because of its ease of use, kubernetes has become one of the fastest growing container technologies. The offerings of kubernetes have helped it to build a great open source community around it.
DevSecOps: Security has become the main concern for companies as the CI/CD pipeline has made it possible to employ rapid changes according to a customer’s demand. Companies need to build security into the software from the beginning as the CI/CD pipeline can also be automated. DevSecOps applies security feature at the beginning of an application’s lifecycle which makes the system less vulnerable and brings security closer to IT.
AI and ML in DevOps: Artificial intelligence and machine learning techniques can process a significant amount of information in the very short span of time. IT can also complete repetitive tasks, freeing the employees to do more targeted work. These techniques can draw patterns in the unorganized data and suggest solutions if they find any problems.