As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.
DevOps needs a mindset shift to save the overworked engineering collective. There’s a considerable discussion right now about the Great Resignation. But if you work in software engineering, you’re probably even more familiar with the Great Burnout.
Everything in the software development realm has sped up over the last few years. Engineers perform at a rapid-fire pace, with perfect accuracy, all day, every day. The demand for new, updated or better apps never slows down. But your DevOps team can only perform so fast.
DevOps is Overworked and Burned Out. No, Really.
A full 83% of software developers feel burnout from their work, while 81% reported an increase in burnout due to the pandemic. The most significant factors contributing to those feelings of burnout include high workload, inefficient processes and poorly-defined project goals and targets.
Overworking, overloading and burning out developers is a recipe for disaster; that’s resulted in job hopping and low productivity. Organizations need to shift their mindset about how we develop apps and nurture developers to make the future of software development sustainable.
The Burden of Uneven Engineering Demands on Your Bottom Line
Software delivery is only as sustainable as the level of workforce happiness. Today, the supply and demand for engineers is entirely lopsided and the chasm between the two continues to widen.
The highest number of SaaS companies worldwide exist in the United States. The vast majority (73%) of all U.S. businesses are planning to switch to SaaS in the near future; the demand to hire great engineers and find balance will continue to escalate for years.
Additionally, software developer employment is projected to grow 21% by 2028, faster than the average 5% projected growth rate for all occupations.
For engineers, this growth is excellent news. But for leadership, the uneven demand for engineers means it’s more important than ever to consider the pain points of your DevOps team and offer solutions to common issues, like overwork.
Infrastructure Needs to Change to Dampen DevOps Burnout
Throwing more money and more people at an already overworked engineering culture will not make the SDLC more sustainable nor help you hit business objectives.
If we take a page out of the “five whys” and dive into the root cause of universal DevOps burnout, there is a common thread in all software engineering approaches. DevOps, Agile, Six Sigma, Lean, Scrum, you name it–these are tried-and-true methodologies that fail if only the symptoms of our infrastructure issues are addressed. We need to reconsider our current tooling choices if we are to appropriately leverage these frameworks for sustainable development.
Organizations can deflect further engineering burnout and rebound by focusing on saving developers time and reducing toil: The labor engineers devote to repetitive, dull or manual tasks.
It’s necessary to advance infrastructure with automation and embrace next-gen tools that focus on developer experience to halt further DevOps burnout.
Let’s Try Something Different: Automate the API
There needs to be a mindset shift to save DevOps from demise. You can do this by taking a bottom-up approach and introducing more intelligent automation into your software development infrastructure.
Automation saves developers from mundane or low-value tasks and instead focuses their time and talents on planning, creating and delivering high-quality apps. By improving the quality of DevOps functions, engineers feel more valued and have more pride in their role in the company.
Automating tasks doesn’t just help the current DevOps team. Embracing automation frees up your existing workforce, requiring lower hiring demand while retaining confidence that their DevOps team is operating at peak efficiency. This approach tackles the root of the problem—too much work, not enough developers—and allows organizations to retain developers long-term by making their work lives more, well, livable!
Let technology do the mundane, so developers can apply their specialized expertise where it matters. Hire less but do more. Automate workflows so that developers can do their real work: Write code. Sidestep the employment demand issue and protect developers.
Of course, this approach doesn’t come without drawbacks. Even a near-perfect product can introduce failures if it requires too much customization by highly specialized developers. Then, costs begin to skyrocket because of the manual labor required for API development for customization and database management.
When done effectively, continuous development is a shining example of improving the infrastructure of DevOps and impacting burnout with automation. Continuous integration and continuous deployment (CI/CD) allow for faster feedback from your customer base, letting you turn around adjustments of features, add or remove things that actually fit and solve problems for your customers faster.
3 Next-Gen Development Tools to Save Your Team From Continued Toil
Tackle developer overload by incorporating the next-gen development tools designed to improve the developer experience. Make the workday more manageable, not more complex, with three emerging categories of development tools to fix DevOps burnout.
1. Automated Code Suggestions
Context-aware code completion tools suggest code to developers during the coding process. Automated code suggestions save developers precious time (and labor) thanks to fewer keystrokes and are designed to increase the speed of the entire coding process.
2. Instant API
With only a few lines of code, instant API connects your data to your app, helping to turn every developer into a backend dev. Whether you need to power a web app or a mobile app, hosting your API and databases in the cloud on one platform allows teams to configure, test and manage APIs without the all-too-familiar manual burden on developers.
3. Neural Networks
A branch of machine learning, artificial neural networks are computational models that extract meaning from complex or messy data to detect trends and patterns. Neural networks, while not perfect, can suggest improvements to coders as they write.
We are doing our engineering workforce a grave disservice by ignoring the Great Burnout and not addressing the shift needed to course-correct DevOps from the ground up. Without the necessary infrastructure automation advancements and adoption of developer-focused tools, teams will continue to battle against velocity demands and churn. It’s time to embrace a new mindset and usher in a new era of DevOps productivity and developer satisfaction.