How Do Big Data and DevOps Work Together in Global Enterprises

How Do Big Data and DevOps Work Together in Global Enterprises

As enterprises strive to become more agile, they are re-evaluating their application development and deployment processes. In this quest for agility, two terms have emerged – Big Data and DevOps. 

While Big Data is a term used to describe the large volume of data that organizations generate, DevOps comprises of software development practices that can shorten the software development life cycle and provide continuous delivery. DevOps consulting focuses on helping businesses and organizations manage their data more effectively.

Though these two concepts are different, they are complementary to each other and can be used in tandem to create a more efficient application development process. 

Now we will take a closer look at how Big Data and DevOps can be used together to achieve better results.

How Big Data Can Help in DevOps?

There are multiple ways in which Big Data can help in DevOps: 

By Automating the Process of Gathering Data

In most enterprises, the process of gathering data is manual. This not only leads to errors but also slows down the process. 

With Big Data, it’s possible to automate this process, thereby reducing errors and increasing efficiency. 

By Providing Visibility Into the Entire Process

During the software development process, there are multiple stages – requirements gathering, coding, testing, etc. It’s difficult for enterprises to get visibility into all these stages with traditional methods. 

However, with Big Data tools, it’s possible to get visibility into every stage of the software development process. 

DevOps consulting helps Development and Operations teams to collaborate better and identify issues early on, thereby reducing the time to market for new applications and helps with digital transformation for enterprise level businesses. 

By Facilitating Real-Time Collaboration

In traditional application development processes, teams work in silos and there’s very little collaboration between them. 

It’s possible for teams to collaborate in real-time and make changes to the code as required. This increases transparency and eventually leads to faster turnaround times for new applications. 

By Helping in Root Cause Analysis

In traditional application development processes, it’s difficult to find the root cause of an issue since there’s no visibility into all aspects of the process. 

It’s also possible to quickly identify the root cause of an issue by analyzing all the relevant data points. This helps Operations teams fix issues quickly and prevent them from happening again in the future. 

By Providing Predictive Analytics

Most enterprises use reactive methods for managing their IT infrastructure. This means that they wait for an issue to happen before taking steps to fix it. 

However, as any expert in DevOps consulting would say, with Big Data tools like Kubernetes, it is possible to predict when an issue is going to happen and take steps to prevent it from happening in the first place. This helps Operations teams save time and resources which can be used for other purposes. 

Final Thoughts

In conclusion, we can say that Big Data and DevOps are a winning combination for global enterprises. When used together, they can help enterprises become more agile and reduce the time to market for new apps.

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