Automation: 5 issues IT teams need to keep an eye on in 2022

IT Jobs: 7 Hot Automation Skills in 2022

As a skill category, automation now covers the gamut of virtually any IT job title.

From “traditional” IT positions (such as a software developer, system administrator or security analyst) to more recent titles such as DevOps engineer, cloud platform engineer or site reliability engineer (SRE), automation skills are relevant – and often in demand – in a multitude of technological roles today.

So, if you are looking to strengthen your attractiveness on the IT job market, building automation skills are definitely a good way to do it. Automation skills have the added benefit of portability – if you don’t want to be pigeonholed into a particular title or function, automation practices and technologies can pave the way for other roles in the future as well.

7 job skills in IT automation

“Automation Skills” is a broad category, of course. We break down seven subsets of IT automation, including non-technical attributes that pair well with relevant technology skills, that IT leaders and recruiters say are in high demand at the moment.

1. DevOps-focused tools and practices

DevOps and automation are deeply connected; as a result, many of the skills and technologies commonly associated with DevOps are also required for automation-focused roles in general.

“DevOps has become the standard methodology for software development and cloud implementation, so those who don’t understand DevOps principles and practices will have a hard time,” notes Clyde Seepersad, SVP and GM, training and certification, The Linux Foundation. “More and more professionals are realizing this and that the combination of Kubernetes and Linux technologies with DevOps practices leads to superior results. I only see that this realization expands further in the future ”.

If you have a solid DevOps track record, this will appeal to many hiring managers who are looking to bolster their automation skills. From the point of view of tools, a particular area seems to emerge: infrastructure as code.

[ Understanding automation: What is Infrastructure as Code? ]

If you have a solid DevOps track record, this will appeal to many hiring managers who are looking to bolster their automation skills.

“One of the most important approaches to automation is infrastructure as code,” says Chris Nicholson, head of the AI ​​team at Clipboard Health. “Infrastructure as Code makes it easy to start and manage large computing clusters, which in turn makes it easier to quickly introduce new products and features and scale in response to demand.”

Kelsey Person, senior project manager at recruiting firm LaSalle Network, agrees: Experience with infrastructure as code (and other DevOps tools) appears in a resume right now, because it indicates the knowledge and skills needed to help drive important automation initiatives elsewhere.

“One skill we’re seeing more in demand is knowing DevOps tools, aka Ansible,” says Person. “It can help organizations automate and simplify tasks and can save time when DevOps developers and professionals install packages or configure many servers.”

[ Download the eBook preview: Ansible for DevOps ]

2. Scripting languages

The ability to write home automation scripts is a mainstay of automation-centric jobs – it’s essentially the skill that never goes out of style, even as a wider range of tools (like some robotic process automation software ( RPA) and low-code or no-code tools) allows non-developers to automate some previously manual processes.

As Ansible senior product manager Chad Ferman recently wrote at Enable Sysadmin, “Having the ability to competently script with the platform’s built-in language (PowerShell for Windows or Bash for Linux) is a great place to start.” IT automation skills are developed.

[ Read also: 8 skills you need to be successful in IT automation. ]

Indeed, these are good starting points, but there are more automation-compatible languages ​​that could be useful in a variety of roles.

Ferman points to Python as a universal language for increasingly sophisticated automation work. It has become a benchmark in data science, for example, but the language can be applied to a wide range of automation use cases.

“Another key skill is writing Python scripts for web scraping to quickly accumulate and organize useful data,” says Nicholson. “Our recruiting team does this because we have such ambitious hiring needs. The landscape of data on job seekers is truly fragmented and isolated. “

3. Containers and Kubernetes

Kubernetes has become a heavy anchor in the sea of ​​cloud platforms and tools. Its adoption and use continues to grow because (among other reasons) the trend towards containerization continues unabated. According to Gartner, approximately 75% of global companies will run containerized applications in production in 2022. Rapid management of containers in production on any type of scale requires orchestration, of which automation is a significant part.

[ Related read: 5 Kubernetes trends to watch in 2022. ]

And 72% of IT leaders surveyed as part of Red Hat’s Global Technology Outlook 2021 said they expect an increase in container utilization.

This means there is corresponding demand for Kubernetes talent, and the offer simply hasn’t arrived yet. As Seepersad told us recently, the hunt for IT professionals with Kubernetes skills is fierce. “There is no sign of slowing in terms of adoption of Kubernetes, and generally cloud-native.”

4. Test automation

Test automation is an important part of the larger shift to CI / CD pipelines – sure, the acronym means continuous integration and continuous delivery (or continuous delivery), but it could also be called “continuous automation”.

Mike Mason, global head of technology at Thoughtworks, says that while his consulting firm tries to remain agnostic about specific tools, test automation is a crucial category. Without it, teams will be much more difficult to ship quickly and frequently, two goals that seem to pervade today’s software world.

“Automation test capabilities are very important, whether it’s testing traditional software or testing RPA or low-code solutions,” says Mason. “The ability to automatically test new software releases is critical to achieving Continuous Delivery and achieving production value faster.”

Test automation (such as with integration, vulnerability scanning, and so on) is key to ensuring quality and reliability without introducing bottlenecks. It is not necessary to run a mature CI / CD pipeline to apply this principle.

“Automation testing capabilities can also help distinguish candidates during the hiring process,” says Person, adding that open source tools like Selenium and Cucumber are popular.

This skill area also intersects with n. 2: If you can write your own tests, highlight them as relevant.

5. Security automation

“Security will continue to be a priority for technology teams, which means more organizations are looking for employees with experience in security automation,” says Person.

Security automation is a huge category in its own right. (To that end, check out IT Security Automation – 3 Ways to Get Started.) It can mean anything from automated runtime security scans to automated lower-level incident repair, to entire processes and toolchains, to entire platforms for managing an organization’s security programs.

The security industry is full of acronyms, but two of them currently stand out on the job market in terms of automation experience, according to Person: “Companies are specifically looking for candidates who have experience with SOAR (Security Orchestration, Automation and Response). and Security Information and Event Management (SIEM), which both can help organize data, recognize threats and automate response to that threat. “

“Security will continue to be a priority for technology teams, which means that more and more organizations are looking for employees with experience in security automation.”

6. Algorithmic thinking

If you are a machine learning engineer, then you understand and work with algorithms already. Software engineers in general have a knack for logic and “if-then” processes. As automation use cases expand, however, Nicholson sees the ability to “think in algorithms” as a growing cross-cutting skill for more people, including non-technical people or IT professionals whose work does not require the writing a lot of code.

“By that I mean you have to think like a computer, taking small, precise steps through a decision tree: If X happens, then Y it should happen, ”says Nicholson. “Software engineers do it for a living, but non-software engineers are capable of it and that makes their lives a lot easier.”

Indeed, this is an area of ​​skills development that could be widely applied in many organizations: a financial professional who wishes to use RPA to automate repetitive work, and a process or business analyst who wishes to increase their value by learning to “talk IT” – and thus become a better translator between business and technical requirements.

“If you want to tell computers what to do, you have to learn to think like them.”

“If you want to tell computers what to do, you have to learn to think like them,” says Nicholson.

7. Communication, openness and integrity

Automation in the absence of “soft” qualities such as communication, openness, and integrity is more likely to cause problems.

When leadership does not effectively share its overall strategy (and how automation fits), for example, this can fuel fears of job loss and other automation anxieties. And that may just be the beginning of a much steeper downside.

As a result, hiring managers are increasingly looking for people who match these kinds of principles and traits (like communication or integrity) with their technical expertise. For similar reasons, these characteristics are also important in AI / ML, where problems such as bias could have important consequences.

“One of the challenges of automation work is that it’s a newer field for many organizations, so there are a lot of unknowns throughout the process,” says Person. “Companies need employees who will openly discuss any difficulties with these projects.”

While IT automation isn’t new, many of the ways it’s applied (and the tools to do it) are relatively recent, so the know-it-all attitude is not likely to appear on many wanted-after-skill lists.

“Everyone is learning about these tools and processes, so effective communication that doesn’t hide information will be key to addressing issues and ensuring projects stay on track,” says Person.

[Where is your team’s digital transformation work stalling? Get the eBook: What’s slowing down your Digital Transformation? 8 questions to ask.]

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