18 Oct Big Data and DevOps – Using Flexible Development Models to Maximize Data
Big data is a major point of discussion when businesses explore digital transformation. In theory, gathering information from a wide range of unstructured and structured sources should help companies build efficient, streamlined operations using digital apps and services. Going digital makes it easier to gather data from diverse locations, and having apps and services in place to leverage that information enables companies to make both real-time and strategic decisions with data in hand.
In practice, the big data value workflow is not quite so clean. Things can get messy when you have huge quantities of information in place, and it can be easy for businesses to run into a situation where they lack the ability to effectively take action on the information they gather. This is where DevOps methodologies come into play.
What is DevOps?
The simple answer is that DevOps is an IT structural model in which development and operations teams collaborate with one another on an ongoing basis in order to inform decision-making and guide how solutions are developed, rolled into production and managed on a day-to-day basis. DevOps is, of course, much more than that. Some other key attributes of DevOps include:
- Cultural change: Segmented development and operations teams have led to varied priorities across the two groups and getting them to work together demands cultural change in which the disparate units within an IT department work toward shared goals instead of functioning in isolation from one another.
- Agile development: Agile almost always goes hand in hand with DevOps, as implementing more flexible, responsive and scalable development strategies makes it easier to get operations teams involved at various stages in development to offer input and help refine the code to ensure it will work well in the production environment.
- Speed: All of the operational, cultural and structural changes that go into DevOps add up to create an IT department that can get work done quickly without sacrificing quality. Code is developed in light of the unique attributes of the IT configuration and choices regarding the production environment are often made with app requirements in mind. This collaboration fuels rapid app releases that drive business innovation.
What does DevOps mean for big data?
There are a few major challenges that come with big data, but one of the greatest is what to do with the trends, key metrics and other information that is gleaned from a large-scale analytics program. While some robust apps and services may integrate with your backend to allow big data systems to feed conclusions directly to end users, chances are that you will face a need to create custom solutions – whether by altering existing apps or developing proprietary apps from scratch – to make the most of big data.
“DevOps accelerates the development cycles that let you create value through analytics.”
Implementing a DevOps model accelerates the development cycles that are put into action when creating apps that will support your big data programs, letting you create value through analytics. While DevOps is vital here, finding success with the strategy hinges on having the right supporting technologies in place.
Technologies that support DevOps advances
A few solution types are especially important when engaging with a big data program, with standout technologies including:
- Cloud services: Cloud-based app platforms provide a foundation upon which developers can create and test code as quickly and efficiently as possible. A cloud system eliminates the need to roll out new infrastructure to support each development project, reducing costs and boosting developer performance.
- Unified communications: Getting development and operations teams to collaborate isn’t just a matter of cultural change, it also comes down to solving plenty of logistical challenges that keep these teams apart. In particular, you need to empower users to communicate naturally within their everyday work and not have to put much effort into collaboration. Advanced communications platforms play a vital role in breaking down walls between your various IT teams.
- Service desk software: Robust IT service desk software can serve as a hub for development and operations teams to share knowledge, collaborate when solving problems and track a wide range of issues. The visibility offered by service desk systems is vital when establishing DevOps capabilities.
Big data can fuel value creation, but only with robust development strategies existing in the background. Managed services providers can help companies access and optimize the technologies they need to enact a DevOps structure within their IT department and get more out of their analytics efforts.