As 2014 gets into full swing, Hadoop is increasingly being used for applications that are integral to daily business operations. No longer is Hadoop viewed by some organizations as just a platform for big data proof-of-concept applications. IT leaders should be developing a strategy for production-ready infrastructure, now, so they are ready to leverage the emerging technical advances that make Hadoop more capable of supporting business-critical big data applications.
Inspired by Google’s MapReduce, Hadoop has earned its stripes as a platform supporting large-scale computing for Yahoo, Facebook and other Internet giants. However, until now it hasn’t been universally considered mainstream technology, in part because of v1 technical constraints and the scarce technical skillsets Hadoop requires.
But in my view, Hadoop is ready for production, particularly with the release of v2 and when delivered via a managed services model. Here’s why:
- With technical enhancements in v2, Hadoop has transitioned from a batch-processing model to a multi-use platform for crunching data in many more ways, making it ready for real-time big data applications.
- Explosive data growth is challenging organizations to scale big data operations at the speed of business after initial use cases prove successful. When Hadoop is delivered through a managed services model, organizations accelerate delivery without worrying about large capital investments, lack of in-house skills, data center constraints or implementation success.
- Emergence of a big data best practices stack, encompassing an infrastructure layer, a data layer and an insight layer, ensures delivery of big data applications in the context of an organization’s overall information architecture. (I will have more to say about this emerging stack soon.)