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Rainforest QA 2018 Predictions: Taking a look back and forward in the world in DevOps

VMblog Predictions 2018

Industry executives and experts share their predictions for 2018.  Read them in this 10th annual series exclusive.

Contributed by Derek Choy, CIO, Rainforest QA

Taking a look back and forward in the world in DevOps

In 2017, the world of DevOps experienced a historical industry shift thanks to the heightened role of IT within the enterprise, as well as the advent of disruptive technologies such as AI, machine learning and IoT.

After working directly with developers and companies of all sizes throughout the year, I've outlined my biggest takeaways, as well as what the future holds as more businesses look to incorporate today's most advanced technologies in their DevOps processes.

The biggest surprises in 2017

In 2017, AI and machine learning adoption failed to meet the hype. This isn't necessarily a surprise, but it is noteworthy due to the fierce debate over the last year. Prominent CTOs, CIOs and others, such as Elon Musk and Stephen Hawking wondered if AI would "take over," and discussion raged on how robots could uproot jobs en-masse and how people and companies can protect themselves against the "dangers of AI." Despite this, progress and development in AI did not materialize as expected. In the enterprise, AI and machine learning began adoption, but not at the scale and extent predicted.

CI-CD was hindered by bureaucracy in 2017. Despite the declared priority of continuous integration / continuous deployment (CI-CD) among technology decision makers at large enterprises, its adoption was slower than expected. Heads of Engineering became evangelists for its ability to automate difficult, labor-intensive processes, but deployment was not as pervasive as expected. Having said that, small businesses and organizations, known for being more nimble, were able to adopt CI-CD practices and were able to cut costs and save time in their software updates and releases.

On the horizon for 2018

In 2018, CIOs will figure out how to scale DevOps without scaling engineering teams. We've reached a critical inflection point in DevOps adoption. CIOs will face pressure in 2018 to ensure their businesses are releasing software at speed and quality, without adding cost. CIOs are adopting DevOps as a solution, but there are still many elements of DevOps that are very human intensive. In 2018, CIOs will figure out how to automate DevOps to scale teams while meeting business goals for headcount and recruitment.

In 2018, AI will help companies scale and will take on a higher percentage of work. In 2018, business leaders will push to make the business run more efficiently and will turn to AI and machine learning to help. Companies will also turn to AI to help scale and do jobs instead of adding headcount. We will see AI developments and research move from the scientific/abstract concept phase to more practical. As a result, enterprises will use AI and machine learning to push the limits of maximum efficiency -- more work will be completed by AI or machine learning.


About the Author

Derek Choy 

Derek Choy, CIO, Rainforest QA

At Rainforest, Derek Choy is responsible for driving product and technical innovation and scaling Rainforest's globally distributed engineering, product and professional services teams. Before joining Rainforest, Choy was vice president of engineering for Aria Systems, scaling a similarly distributed engineering team by 10X, which supported revenue growth of more than 20X. Prior to Aria Systems, Choy was director of software development at eBay, where he led product development for its billing platform, and was responsible for streamlining processes across several teams. Choy has also held senior engineering and management positions at Accenture and AT&T.

Published Friday, December 22, 2017 7:25 AM by David Marshall
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