DevOps, the integration of software development and IT operations, is a key factor behind swift and quality service delivery. As a result, and partly motivated by the COVID-19 pandemic, DevOps roles are high on the hiring list. This is why DevOps job postings grew by 443% between 2015 and 2019, according to the 2021 Bain and Company Technology Report.
Because of the demand, hiring DevOps engineers is a tricky business, as competent developers are in short supply. According to the 2021 DevOps Institute skills report, skill-related challenges were the main reasons IT leaders struggled to employ DevOps professionals in 2021. For those who do possess the desired skill set, the DevOps hiring cost is often high. DevOps engineers earned between $150,000 and $250,000 in 2021, according to Puppet's 2021 DevOps Salary Report. Puppet's report corroborates the results of ITPro Today's 2022 Salary Survey, which revealed IT engineers are primarily motivated by salary compensation.
Because of these DevOps hiring challenges, businesses are now adopting automated tools to reduce hands-on management. In fact, Tim Cassell, head of product at nOps, said DevOps needs automation as much as humans need air. "No [DevOps] job is complete until it's automated. … [Automation] is the only path to operating DevOps at scale," he told ITPro Today.
Transposit's 2022 State of DevOps automation report agrees with Cassell's position. More than 80% of Transposit's respondents said they have automated 50% of their engineering process, while another 48.4% plan to implement new automation tools in the next 12 months.
One of the high-demand automation tools is Render, a platform as a service (PaaS) for hosting apps and websites. Despite the rapid adoption of automation tools, successful automation will only happen when "people, processes, and tools all come together," Anurag Goel, founder and CEO at Render, told ITPro Today.
Organizational Structure Is Still a Problem
The enemy of DevOps is complicated processes. In the 2022 Transposit DevOps automation report, "too many manual processes" ranked as the second-highest DevOps barrier (49%) to resolving security incidents. Goel agrees. "The complexity of managing an ever-growing and ever-changing toolset and the lack of integration" is the major reason developers struggle with DevOps tools, he said.
Similarly, Cassell believes developers struggle because of organizational structure. "Developers are often too insulated from infrastructure and systems designs," he said in an email interview with ITPro Today.
The 2021 DevOps Institute skills report shines more light on Cassell's position, noting that siloed organizational structures frustrate DevOps collaboration. Mark Settle, a seven-time CIO, described the mismatch between developers and executives as "speaking in different tongues."
The DevOps Hiring Landscape Is Changing
The DevOps hiring landscape is experiencing a paradigm shift. Goel predicts "internal platforms" will replace DevOps in the next three years. He also believes "there will be fewer DevOps job openings because of increased automation," as companies look to streamline the software deployment process at a reduced cost.
Goel hinted that PaaS is leading automation adoption. "Companies are leveraging PaaS vendors more; they can keep their engineers working on the most modern stacks and solve higher-value problems while automating the lower-tier tasks. The shift toward modern techniques and automated tools is turning DevOps tools into LowOps," he noted.
Regarding the DevOps hiring landscape, Cassell said engineers need to bring more than DevOps skills to the table. To survive in the future DevOps market, engineers will need domain knowledge and product development capabilities, he said, urging engineers to expand their knowledge bank with varieties of infrastructure-as-a-service (IaaS) and PaaS tools.
"DevOps engineers will need to feel comfortable using low-/no-code tools for automation," Cassell added.
Automation Is the Way Forward
Automation simplifies tasks throughout the software development lifecycle (SDLC), as it uses specialized cloud-based software tools to manage repetitive tasks.
However, automated tools aren't magic wands — they require the right skill set for optimal output. According to the 2021 DevOps Institute skill report, knowledge of high-tech tools — like artificial intelligence (AI) and machine learning (ML) — is a must.
AI and ML provide fixes and actionable insights. In fact, nOps leverages AI and ML technologies to bridge the gap between finance and DevOps.
Cassell shared how AI helps with FinOps: "Our risk-free resource scheduling and cloud waste cleanup capabilities constantly learn from the usage patterns in customer environments using AI."
Both Render and nOps are keen to help developers achieve efficiency through automation. Goel claims Render's key differentiator is its ability to "completely automate and outsource the management of applications and data stores on Kubernetes." The functionality, Goel stressed, helps companies maintain complex applications without hiring many in-house developers.
Cassell said nOps' ultimate differentiator is affordable pricing. Unlike with other FinOps solutions, nOps' prices aren't based on cloud taxes. Instead, they depend on how much customers save by leveraging automation.
Although automation is the North Star, developers prefer automated tools that allow human intervention at critical points. The human-in-the-loop (HITL) approach enables engineers to address scenarios that aren't part of the original customization.
Cassell said nOps gives room for HITL to boost developer experience. "Our Git integration analyzes IaaC change sets or proposes optimizations. [Subsequently], teams can use the standard review process to apply their own critical judgment before promoting changes through the pipeline," he said.
About the authorKolawole Sam Adebayo is a Harvard-trained tech entrepreneur, tech enthusiast, tech writer/journalist, and an executive ghostwriter. He has 10+ years of experience covering various tech news stories, writing thought leadership blogs, reports, datasheets, and case studies. His areas of expertise include cybersecurity, AI, ML, DevOps, blockchain, metaverse, and big data for C-level executive audiences. He has written for several publications, including VentureBeat, Dark Reading, RSI Security, NWTechs, WATI Security, Draft.dev, and many more.