The rise of big data in DevOps

The pandemic has generated a lot of shifts in the IT industry, including big data and how it is working alongside DevOps. Indeed, the situation has sped up the role of data analytics within DevOps, making developers, data scientists, and product managers work with each other.

IT teams have started to rethink the way they use big data and analytics, which is leading toward a merge of DevOps methodologies and data analytics. With the need of getting faster results and analytics insight, organizations had to put an emphasis on analytics reporting.

This shift also calls for alteration in operations and culture for IT, such as a definite move from waterfall to DevOps development. Developing and deploying big data apps require an iterative process, which doesn’t conform with the traditional waterfall methodology. However, many departments in IT are still using waterfall development. Hence, if these functions come together, there will be a more collaborative process of big data application development.

By doing this, there will likely be a creation of interdisciplinary functional teams rather than separate silos. End consumers might also become active participants on these teams. Moreover, the testing of big data apps might become more relative than absolute, which would be a major shift for traditional IT systems.

IT organizations should also start to shift towards supporting mission-critical big data applications for failover, priority maintenance, and continuous development. This could lead IT, teams, to support big data support, with relevant training in order to ease the change.