A Little Help From My Friends Part 2: A Review of Past Tech Tools and Insights on New Technology Trends

A lot can change in five years. Especially when we’re talking about technology.

In December of 2015, I asked a few Credera technology leaders to make predictions about the most promising technology trends. They were prompted with the question: “What is the best new tool or technology that you’ve used in the past year? What problem does it solve?” They shared their predictions for the technologies they believed would change the landscape.

We’re throwing it back to evaluate their assessments, name a 2015 winner, and give them a chance to make new predictions about where they see technology trends going in the next five years.

Jason Goth, Chief Technology Officer

2015 Prediction: Kubernetes

“I believe that Kubernetes will evolve to allow for multiple network implementations, which will solve many problems. But services go hand in hand with these networking improvements and are a great tool for distributed environments.”

2020 Review: Kubernetes

I’m excited to see the adoption that Kubernetes has had since the original article in 2015. It’s an excellent platform for automating, scaling, and managing complex, micro services-based applications. I believe this adoption is driven largely by support from the large cloud services providers (AWS/Microsoft/Google). My one caveat is these environments are growing increasingly complex. But going forward, I believe extensions such as Helm, Kustomize, and Istio (or Kubernetes itself) will reduce some of this complexity.

2025 Predictions: Edge Compute Solutions

Looking forward, I see a trend toward more interactive interfaces beyond traditional browser-based applications and apps using technologies such as voice, AR/VR, etc. So my picks for the future trends are three technologies that are somewhat interrelated and used to create these new experiences.

Honorable Mention: AI/ML

I’ll start in third place with the broad category of artificial intelligence (AI)/machine learning (ML). While many may argue this has arrived already, I would say AI/ML’s current usage is largely isolated to a narrow set of use cases while the tools to run and manage AI/ML solutions at scale are still immature. I see things like TensorFlow Extended (TFX), KubeFlow, and cloud-based solutions from the large providers making it easier to adopt, manage, scale, and distribute AI/ML solutions for voice processing, image recognition, etc.

Honorable Mention: XR

In second place is the rapid adoption of augmented reality (AR)/virtual reality (VR) (collectively “XR” now), spatial technology, etc. I see technologies like ARKit, ARCore, having many more commercial uses over the next few years.

Winner: Edge Compute Solutions

But solutions based on these building blocks will need to be distributed out to the edge. Even with the rise of 5G, most use cases for AI/ML or XR will need to run on local devices such as Internet of Things (IoT) devices, cars, headsets, etc., to allow for disconnected use and faster processing. As things get more distributed, the ability to manage and secure solutions out at the edge at scale will become more and more important. So my first-place winners are edge compute solutions such as AWS Greengrass or Azure IoT Edge.

John Jacobs, Partner

2015 Prediction: Vagrant

“It makes setting up a local dev environment fun again. You can have a full stack up and running in minutes in a very production-like way (running separate VMs with the right OS version, packages, etc.). One person sets it up and commits their Vagrantfile and everyone else can just “vagrant up” instead of spending minutes (no wait… hours, no wait… days) setting up their dev environments. I can’t think of a greenfield project we would start today without it.”

2020 Review: Vagrant

Jason and Kubernetes won the last round hands down. Although the specific tools I talked about back in 2015 may not have won the day, the broader category of infrastructure, deployment and test automation has matured since then. According to the 2019 State of DevOps Report from Google and DORA, high performing organizations are using automation to eliminate manual, repetitive tasks like environment provisioning, deployment, and testing. At Credera, we’ve seen clients save thousands of hours of developer time, significantly improve their engineering cultures and reduce developer turnover, simply by automating these repetitive, error-prone tasks. I’m particularly encouraged by the level of adoption we’ve seen lately in large enterprises.

2025 Prediction: Consumer Data Privacy & Protection

Looking forward, I think there are big changes coming in consumer data privacy and protection, and it’s going to be challenging for many technology organizations to keep up. I see three major contributing factors:

1. Public policy is trending toward tighter consumer data protection, disclosure requirements and easy consumer opt-outs with stiff penalties for violators (GDPR, CCPA, etc.).

2. Consumers are more aware than ever of the personal data companies have about them and what they are doing with it.

3. Recent high-profile breaches are keeping data security and privacy top of mind for both consumers and regulators.

This trend may not be sexy like AR/VR, AI, ML or IoT, but it could prove costly for companies that don’t have a well-defined strategy for managing and protecting customer data. Tech companies like Facebook have a ton of data about us and they are heavily impacted by regulations like CCPA, but they also have young systems with modern architectures, which positions them well to respond to regulatory and consumer demands. Many established companies and enterprises are not well positioned—they may have customer data spread out across mainframes, on-prem databases, cloud databases, and SaaS platforms, all of which needs to be protected, curated, and potentially purged upon request. Organizations should consider making proactive changes to their customer data architectures so they can respond quickly and accurately to changing regulations and consumer sentiments.

Micah Blalock, Senior Architect, Open Technology Solutions

2015 Prediction: Spring Boot

OK, to be fair, I didn’t actually participate in the last article, but in 2015 my vote would have been for Spring Boot. Pivotal’s convention-over-configuration solution made is simple to build web applications that run like compiled executables. No need to deploy and run WAR files on a separate, shared application server.

2020 Review: Spring Boot

Spring Boot has been a big success, but Jason was right about Kubernetes. Kubernetes is a force multiplier, making it simple to build complex, scalable systems from small, simple services. Kubernetes is now supported across all major cloud vendors and has a large ecosystem of supporting tools to extend platform capabilities and reduce complexity.

2025 Prediction: Python

I can hear the groans and I get it. Python is not exactly new technology. But if you don’t use Python today, I think you’ll be using it daily within the next five years. Why? Because Python is the language of AI, ML, and data analytics, and they’re going to be eating the software that drives your business today.

The major cloud platforms all have zero or low-code tools for building simple flows to do image recognition, natural language processing, sentiment analysis, data transformation, and analysis. These “toys” exist primarily to whet the appetite for what’s possible. But just as Kubernetes made it easy to build complex systems from simple services, Python makes it easy to combine these platform tools with pipeline or orchestration frameworks and a few of the more than 200,000 Python packages to create incredibly complex process flows for analyzing language, processing images, or performing data analytics.

I believe we’ve only seen the tip of the AI/ML analytics iceberg. So start learning Python as soon as possible. The differentiator in tomorrow’s market may be those who can quickly build amazing systems from today’s toys.

Moving Forward

As technology constantly changes, it’s fun to look back and see how far we’ve come—even in just a few short years. If you ever have a question or need help navigating this changing landscape, let us know at findoutmore@credera.com. Odds still are that one of my friends at Credera can help you.

• Spring Boot
• Machine Learning
• Python
• Artificial Intelligence
• XR