The Ultimate Impact of DevOps and Machine Learning in 2016
Monday, January 04, 2016
We recently visited with Christian Beedgen, CTO at Sumo Logic, to discuss impact of DevOps and machine learning for the upcoming year.
As the co-founder and CTO of Sumo Logic, Christian has 15 years experience creating enterprise software architecture. Prior to Sumo Logic, Beedgen served as Chief Architect for event-based products at ArcSight and was co-founder of Gigaton, an infrastructure software company enabling distributed file management solution over IP-enabled networks
ADM: What is the top trend IT leaders should expect in 2016?
Beedgen: In 2016, DevOps will play a role in any business that relies on information technology to compete. While DevOps has existed in many organizations for a while, next year it will emerge as the dominant approach to software and service development and deployment.
ADM: What is driving the increasing adoption of DevOps?
Beedgen: IT leaders have realized the benefits are far too great to ignore. Much like the advantages public cloud offers (scalability and quicker time to product delivery), DevOps empowers teams – from a cultural perspective – to effortlessly enable agile, efficient processes. DevOps folds IT and delivery into the agile approach that has replaced previous development approaches in all but a few niches.
ADM: Where does security fit in here? How does SecDevOps comes into play?
Beedgen: Security must be built into the culture, process and technology from the beginning. In the age of APIs and automation a lot of the security of a service can be automated, too. I believe that security teams will join forces with DevOps teams to help secure new application architectures with embedded security capabilities that leverage integrated machine data analytics.
ADM: There’s been a lot of discussion about machine learning – have we finally reached an era where this will become mainstream? Where do you see machine learning headed next year?
Beedgen: While this certainly is not an overnight phenomenon, in the year ahead the line between the work of machines and humans will continue to fade. Machines will enable greater productivity among teams and businesses through the advances that machine learning and automation can offer. A necessary component to augment human contributions, machine learning will finally give humans the power to review millions of bits of data.
ADM: What benefits will machine learning offer IT?
Beedgen: Increasingly, businesses will adopt machine learning technology for its usefulness in augmenting human understanding of complex interaction and large data sets by uncovering the unknown unknowns.
ADM: What’s the top priority on your customers’ minds as we head into the New Year?
Beedgen: How can we accomplish more, faster? Every organization faces a resource shortage these days – be it talent, skills or otherwise. I regularly hear from customers that in general, their number one need is for solutions and processes that simplify, automate and enhance data-driven decisions.
For example, we have a number of customers with online-facing businesses who are working towards – or in the midst of – transitioning to the cloud. They need to get scalable, real-time visibility into their entire stack as they transition their infrastructure to better trouble shoot potential issues and minimize impact to customers.
ADM: What is a trend most organizations are likely overlooking but should take advantage of in the year ahead?
Beedgen: While thinking about log data may seem too far in the weeds for most tech industry professionals, next year we’ll see it emerge as the most underrated opportunity for IT. As all businesses look to gain useful insights from their data analytics, log management will be a key solution for monitoring, managing and gathering insights.
Organizations will even go so far as leveraging log management for business intelligence in real time. I predict we’ll even see more vendors try to move into the log management space, and more organizations trying to use log management to make sense of their big data mess.
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