Kubernetes, DevOps and more: Technology trends to watch in 2020

January 21, 2020

New decade, same challenges? If you’re feeling the pressure to grow your team and bring your organization into the future, the rate of technology change can often feel like it’s working against you, not with you. So we asked a few of our experts to shine a light on the technology trends that will matter most in the coming year, and where technology leaders and professionals should be investing their time. Here’s what you should be keeping an eye on in 2020:

Data storytelling

For organizations to succeed in data, it won’t take a mass hiring of PhDs to get you out in front, but rather upskilling your existing workforce to have a good combination of soft and hard skills. Data professionals do need hard skills, like Tableau, Qlik, Domo or other BI tools for data visualization. But the soft skills — the ability to communicate effectively, ask good questions of data, tell compelling stories and make well-supported decisions — are the secret sauce for data success.

Jordan Morrow, data and business intelligence expert

Data security

With major data breaches becoming a regular occurrence in the news, consumers are more aware than ever of what data they are giving away and what risk that could potentially bring. Implementing “security by design” principles is becoming a necessity for companies that store user data, because it’s no longer a question of if there will be a security incident, but when and what the scope and impact will be. 

Maureen Makes, engineering leader

Security automation

It will be critical for us to continue to lean on automation to help address pressing cybersecurity challenges. This will be driven by the need to find additional security skill capacity in order to free up valuable resources for higher value tasks, and the need to be smarter about how threats are identified and how incidents are detected using artificial intelligence and machine learning.

Richard Harpur, security expert and technology leader

Cloud agility

It takes time for an entire IT organization to grasp and embrace a “cloud-native mindset” — and even when fully informed, many IT organizations come to an overwhelming realization that moving from point A (on-premises) to point B (the cloud) is a much larger mountain to scale than they anticipated. To become agile, companies need to spend time understanding your applications in order to reduce complexity before moving those applications to the cloud, and make a concentrated effort to have employees build essential cloud skills.

David Davis, cloud computing expert

Hybrid cloud and multi-cloud

As the cloud market has matured, the biggest remaining prospective customers are from highly regulated sectors such as finance, healthcare and defense. Such customers are hesitant to shift entirely to the cloud, and are wary of dependence on a single provider, because they’re eager to retain control of critical portions of their infrastructure. Hybrid and multi-cloud solutions will solve for these concerns.

Janani Ravi, cloud expert and Pluralsight author


While Docker containers have exploded in popularity, there’s still not a whole lot that individual, isolated Docker containers can accomplish on their own. You need an orchestration layer to get those containers to work together, and that’s why Kubernetes is on the rise. Every tech professional today ought to be spending the time to learn Kubernetes, because container orchestration is here to stay.

Janani Ravi

Machine learning

Just as most organizations don’t need their developers to write database management systems, cryptography libraries or video decoders, most organizations don’t need their own unique battery of PhDs in computer science and computational statistics who can write machine learning algorithms. What’s far more important is the interdisciplinary ability to know when and how to use algorithms, treating technical skill in machine learning platforms and frameworks as an accelerator for existing business acumen and domain-specific knowledge. Rather than accreting these insights and expertise only around explicit “data scientist” roles, we need to move toward a democratization of data science itself — a more widespread uptake of machine learning skills and abilities.

Simon Allardice, Pluralsight author and technology expert


In 2020, we’ll see more organizations starting or continuing digital transformations, including a lot of changes in team structures, with flatter organizational models and dynamic structures becoming a priority for teams focused on faster flow. We’ll see advancements in tooling for automation, testing and monitoring, and software teams will have to focus more on the observability and resilience of their systems in the coming year. 

Jeremy Morgan, Pluralsight author

Technology skill development

If you want to increase velocity and create a competitive advantage within your company, you need to have this same mindset with your team’s tech skills. Your developers need a variety of skills, far more than ever before. Gone are the days of needing just “an SQL engineer” or a “front-end engineer.” You need people who can reasonably do both, and who have the skills to introduce the latest technologies into your org. You can’t just hire new engineers to solve this issue — you need to invest in your current talent.

Jeremy Morgan

Want to get your ear on the ground of trending technologies? Explore the Pluralsight Technology Index, which aggregates 23 billion data points on 850 technologies to give leaders the insights they need to take their organization into the future.