Big Data And AI Could Make Traditional Developers…Extinct?

Tom Taulli Tom Taulli
November 7, 2019 Big Data, Cloud & DevOps

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Back in 2010, a team of self-described “data nerds” founded Sumo Logic. The vision was to build a platform to deliver–as a cloud native service–machine data analytics for anybody.

It definitely turned out to be the right focus. Consider that today Sumo Logic analyzes 100+ petabytes of data on a daily basis (to put this into perspective, a petabyte consists of 1,000 terabytes or about five years of the Earth Observing System). The platform also performs 30+ million searches and handles a whopping 500+ trillion record queries every day.

Because of this, Sumo Logic has a unique view of some of the most important trends in technology. Here are just some of the interesting findings from the company’s latest annual report:

  • While AWS dominates the cloud, there was a 50% year-over-year increase in multi-cloud adoption in 2018.
  • Serverless has gone mainstream. About a third of enterprises use AWS Lambda in production.
  • Open source has turned the modern application stack on its head. Four out of six application infrastructure platforms include this technology.

Keep in mind that this report is not based on survey samples. Instead, the results are from the crunching of huge amounts of data from 2,000+ customers (the data was anonymized and included both cloud platforms and on-premise environments).

So What About AI?

Yes, AI is a big part of Sumo Logic. After all, this technology needs enormous amounts of quality data to get to useful insights for businesses.

For example, Sumo Logic’s annual report points out a surge in growth of the Intelligence Economy, as companies attempt to mine insights from end-customer behaviors. There is also a need for real-time feedback. Let’s face it, with the consumerization of technologies like Amazon.com and Uber, customers don’t want to wait.

Yet there is something else to consider: Sumo Logic’s own journey in building its technology and diving deep into data has taught it some important lessons. One is that enterprise customers want flexibility. To this end, Sumo Logic has made it possible to manage data out of the box or to allow for much more intensive approaches, say by using Jupyter Notebooks that are native to Sumo Logic.

The company has also realized that AI and Big Data are actually transforming the roles of traditional developers. It’s no longer just about jamming lots of code and creating full-blown applications, say with Java, C# or C++.

“Development has become more about scripting and assembling,” said Ramin Sayar, who is the President and CEO of Sumo Logic. The fact is that a lot of programming involves integrating other people’s code from sources like GitHub and Stack Overflow. The dirty little secret is that cut-and-paste is one of the most valuable skillsets!

This helps explain why the Python language has exploded in popularity. It allows for easily importing a wide array of packages but also focusing on discrete tasks–without the complexity of traditional code.

Oh, and then there are the low-code and no-code systems from companies like Appian. They have seen quick adoption because there is a nice balance between out-of-the-box technology and customization.

Success In The Brave New World Of Development

So with all the changes, how can you be effective with software development? What will work?

For Sayar, the key is about forming the right team. “Over the years, we have learned that there are three main roles,” he said. “There is a back-end developer, a data engineer and a data scientist. You need all three for solving data problems and use cases.”

Sometimes one person can fill both roles. “If someone can take on three, then he or she is a true unicorn,” said Sayar.

Yet it is extremely important for there to be cross-pollination within the team. This means that each member should have a basic understanding of the other roles. The bottom line is that the development process must not be an assembly line; rather, it should be a true collaboration.

“We want people who understand data and analytics,” said Sayar. “Part of this is about understanding statistics, like Bayesian inference, but also grasping the nuances of data. Those people that have these valuable skills will be the next generation developers.”

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