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Software Development Trends: What You Need to Know for 2020Reading time 8 minutes
An old teacher of mine used to say that one year in tech was equivalent to ten years for other industries, given how fast-paced the field is. That’s why it’s so hard to make predictions about software development trends. History contains many cautionary tales about those who tried and failed to do so. Who doesn’t remember the tale—most likely apocryphal—of Bill Gates, claiming that “no one will ever need more than 640K of memory?”
But since today I’m feeling bolder than usual, I’ll take the bait. Today’s post features some of my predictions for software development trends in 2020. In a year, we’ll see whether I was right or wrong. For now, enjoy it.
Do you want to know the best way to organize IT departments? Make it all about the project. In other words, organize your developers into product-oriented teams.
It’s not an entirely new discovery that product-oriented teams and organizations are the superior approaches. From a business point of view, it doesn’t really make sense to divide your talents into silos such as “Android Team,” “iOs Team,” “Web Team,” and things like that. That makes communication needlessly complicated, and it makes it harder to see the big picture of a given project. In such a scenario, when someone needs to gather information about a given project, they’d need to go across all of these different departments/teams.
The product-oriented approach continues to gain traction. That’s due to, among other factors, big companies promoting product-oriented teams or similar approaches (an easy example that comes to mind is Spotify and its Squads.) We’ll see such a trend continue to rise in 2020.
Python is everywhere. Web development? Check. With frameworks such as Django, Flask, and Web2Py, web development is, without a doubt, an environment well-served by the language. System administration? Check. The language’s versatility and light-weight feel to it make it a perfect choice for writing scripts to automate server administration tasks.
Data science? Also, check. Indeed, that’s one of the areas where Python shines the most, having many widely used libraries in that space, such as Pandas, NumPy, SciPy, TensorFlow, and many more.
According to the TIOBE index of programming languages, Python was the third most popular language in December of 2018. One year later, and it still occupies the same spot. Despite all of its known flaws, TIOBE is still a relevant index.
You still want a different source, though, right? Fine, I’ll give you two. First, GitHub. The 2019 edition of the annual “The State of the Octoverse” report ranks Python as the second language in the platform by repository contributors, outranking Java for the first time.
The final source? Stack Overflow. The 2019 edition of their annual survey, which was conducted with 90,000 developers around the world, showed some interesting results concerning Python. The language reached the #2 spot in the ranking of most loved languages. Also, for the third year in a row, Python is the most wanted language, which means that it’s the language that people who don’t work with wish they worked.
All of the above paints a very clear picture, at least to me. Python was the language of 2019, and I think it’s going to repeat the feat.
DevOps Morphs Into DevSecOps
Many experts consider DevSecOps to be the next stage in the evolution of DevOps. That’s a fair way to put it. As its name suggests, DevSecOps consists of DevOps plus an incredibly important but often overlooked component: security.
In other ways, DevSecOps is a different approach to security, one which adopts a view that everyone is responsible for security. Guided by this mindset, DevSecOps looks to incorporate security practices into a company’s DevOps pipeline. The idea is that security shouldn’t be left just for the last stages of the Software Development Life Cycle (SDLC).
And since we expect the global DevOps market to surpass $12 billion in size by 2025, the next few years—starting with 2020—are going to be the perfect moment for those who want to ride that wave to get ready.
Internet of Things Continues to Grow
Stop reading this post for a moment and take a look around you. How many devices connected to the internet you can see in the room you are right now? Five? A dozen? Now, think about what the answer would be ten years ago. And what about 20 years ago?
Why am I asking these questions? The Internet of Things (IoT), that’s why. That’s one of the most interesting and fastest-growing areas of technology. The number, forms, and shapes of internet-connected devices or gadgets we use has exploded in the last decade.
Such growth is expected to continue. A recent forecast by IDC says that, by 2025, there will be 41.6 billion connected IoT devices generating 79.4 zettabytes of data in 2025. We’ll soon probably see more IoT devices in health care, and smart home devices move to the office and an explosion in the number of digital voice assistants in use.
In short: IoT is on the rise, and it’s a much more than safe bet for 2020.
Predictive Analytics on the Rise
Finally, as the last trend covered in this article, we have predictive analytics. And what is that?
How does one predict the future? For instance, how did I reach the conclusions I present in this post? The short answer is that it boils down to observation. I observe the world around me. I gather and process information from the articles I read, the people I talk to, etc.
Of course, I’m limited by the amount of data I can process and store in my head. I’m just a human, after all.
But what about things that aren’t? What if we fed gigantic amounts of data to a [THING] and have it analyze it? That’s pretty much what predictive analytics is.
In short, predictive analytics means analyzing gigantic amounts of data in order to predict future events. It does that by combining several techniques such as machine learning, statistic, data mining, and more. Having that information, the sky is the limit for what companies can do. They can come up with better fraud detection methods. They can better manage their inventories. Last but not least, they can lower their costs and increase efficiency.
Predictive analytics is gaining momentum, and we see no signs of this trend slowing down next year. That’s because when businesses execute predictive analytics effectively, they become more agile, more efficient, and, most importantly, more profitable.
A Happy—and Connected—New Year for Software Development
What does the future reserve for us? As a wise green little man once said, it’s always in motion; thus, it’s difficult to see.
What we can do is to make educated guesses, though. Based on what we can see from the way the current scenario looks. We learn from it and project a little later into the future.
And what does the short term future look like? A hyper-connected, data-driven, AI-powered world, where new concepts divide the limelight with decades-old programming languages still growing strong.
In 2020, stay tuned to this blog, where you can find more posts on relevant topics you’ll want to know more about. Also, consider giving Plutora a try. It’s a solution that can help your organization improve its software delivery process, manage its test environments, plan deployments, and adopt predictive analytics. In other words: Plutora can help your organization get ready to face the challenges of the next decade of software development.