If you’re not closely related to big data and work with it, you may think that DevOps has nothing to do with Big Data. However, you’re wrong! Let us see How DevOps is useful for Big Data.
Well, let us first have a brief overview of what DevOps is.
DevOps is the combination of tools & practices that help an organization increase its ability to deliver applications and services. This increased speed helps an organization to compete more effectively and cater to its customers.
Under DevOps, the development and operations team works closely as a single unit where the developer works from developing an application until its operations commence.
The teams integrate to use practices to automate the processes as much as they can, which makes their task more manageable.
Benefits of DevOps:
- Speed of accomplishing tasks
- Delivering faster updates
- More reliable
- Developing processes at scale
- Ownership and Accountability
Now, we know what DevOps is and what some of its benefits are. Let us know why DevOps matters.
Both software and the internet have transformed the world ever since the evolution of the latter.
Earlier people used software and tools for support purposes in running a business, but now it has become an integral part of many organizations.
Organizations use software to increase their efficiency and for cost-reduction purposes as well. So, to give support to the software and development of new one DevOps comes into play.
Let’s know in short, what is Big Data?
Big Data is a collection of sophisticated and massive data sets. The big data team includes big data engineers, experts, and data scientists.
It comes with many challenges. Generally, large data sets create these challenges. Sometimes, they are challenging to manage and maintain, but big data has numerous advantages, too.
Big data allows an organization to gain more answers to queries as more information is present in data sets where more answers mean an organization can tackle more complex problems.
DevOps for Big Data
The main aim of the DevOps team is to develop and deliver more efficient software. Including data experts with the DevOps team in the software delivery process can be a plus point when it comes to optimizing the ongoing development processes.
Since big data projects are more challenging, the data experts provide valuable contributions by integrating with the DevOps team throughout the software delivery pipeline.
They help in establishing data transparency while ensuring data security.
What are the applications of DevOps in Big Data?
Effective Planning for Software Updates
Before designing/developing an enterprise-grade application or software, a developer needs to have an understanding of the types of data that they will require for the application and how much it will be.
It will be better for a developer to know this as soon as possible, and this can only happen when the developer is in contact with a data expert.
The data experts are well engaged with the data sets and can help the developer in designing or updating the software accordingly, and they can also help the developer in planning for future updates.
Low chances of Error
When software is developed, developers rigorously test it, and the related-problem to data causes constant errors. this error rate keeps on increasing as the complexity of the software increases with the increase of data in it.
Here comes the collaboration of DevOps and Big Data into the game.
The Data scientists/experts and the developers identify those errors in the early stages, which saves time and effort for both teams. Moreover, it makes it easier to find further errors in the application/software.
The DevOps philosophy states that a development-friendly environment that resembles a real-world environment should be created, but that’s not possible when big data comes into play.
The development-friendly environment is difficult to create when a developer has to involve big data in the development of software, which consists of many complex data sets, which further contain many types of data.
The data experts help the developers know the types of challenges the developer’s team is going to face while creating such an environment and producing the software.
Accuracy in feedback
After an application or software is produced and released, some data is collected. Now, this data is analyzed, and the teams determine which part of the software is doing well and in which areas the software lacks.
This data is beneficial as it sets up a base for the next update of the software/application. The data that is collected for analysis includes app health, i.e., its memory usage, CPU usage, user’s location, no. of users using the app, etc.
Well, DevOps and big data are two different departments in an organization but DevOps and big data teams can work together and benefit each other by streamlining the processes.
By integrating DevOps with the data team, the development of software can become an easy task, and the organization can become more efficient in producing such applications/software.
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