IT Professionals Experiencing Substantial Shift in Responsibilities

The roles and activities performed by IT professionals have evolved dramatically over the past ten years due to the convergence of modern development technologies, cloud platforms, and as-a-service offerings that can significantly improve overall productivity.

Today, many of these professionals find themselves in hybrid roles that combine traditional development activities with activities that formerly were associated with operations professionals who historically had few or no development-oriented responsibilities. A new International Data Corporation (IDC) report provides an extended census and forecast with detail for both traditional IT operations roles and these new hybrid roles.

"The census data shows that a dramatic, once-in-a-generation shift in the composition of the IT workforce is underway. This shift is akin to what took place during the years from 1997 to 2002 when the emergence of the commercial internet and the .com era turned priorities upside down for much of corporate IT and led to the hiring of vast numbers of web developers and networking experts," said Al Gillen, Group VP, Software Development and Open Source, IDC. "The increased adoption of cloud computing is driving similar transitions today in IT teams supporting this modern deployment model."

In developing this data set, IDC used the following definitions to describe the roles broken out in the study:

DataOps uses a combination of technologies and methods with a focus on quality for consistent and continuous delivery of data value, combining integrated and process-oriented perspectives on data with automation and methods analogous to agile software engineering.

DevOps uses collaborative, agile approaches paired with extensive automation development pipelines, testing, infrastructure configuration, provisioning, security controls, and life-cycle continuous integration (CI) for continuous development and continuous delivery (CD).

DevSecOps uses a methodology that asserts that security needs to be prioritized at the beginning of the DevOps delivery pipeline. It enables DevOps teams, collaborating with security, to act as key stakeholders in defining and implementing security policies.

ITOps uses technology and methods to provide routine, scheduled tasks and unscheduled support activities related to IT systems. ITOps professionals may spend as much as 50% of their time engaged with business users in support, the elicitation of requirements, and performing contingent or secondary business tasks.

MLOps uses technology and processes to streamline and automate the entire machine learning (ML) life cycle. The key capabilities include managing and automating ML data and pipelines, ML code, and ML models from data ingestion to model deployment, tracking, and monitoring. MLOps uses similar principles to DevOps practices, applied to machine learning processes.

Platform engineering is a discipline of designing and building toolchains and workflows that enable self-service capabilities focused on managing and optimizing the software delivery process to deploy applications and services to cloud platforms.

Site reliability engineering (SRE) includes software engineers who build scripts to automate IT operations tasks such as maintenance and support. To enable efficiency and reliability, SRE teams fix operational bugs and remove manual work in rote tasks.

Systems administrators configure, maintain, and support computer systems and systems of systems using a variety of tools and methods appropriate to the system or systems of systems in use. They may spend as much as 50% of their time engaged with business users in defining key requirements, business goals, and adaptations needed to maintain fit for use and fit for purpose.

At a macro level, the study shows that a substantial shift in the responsibilities of IT professionals will occur over the next five years. The data indicates that IT professionals in the most purely operational roles are facing a transition to a more technical or focused role that very often may involve some level of software development work. Accordingly, the roles of IT operations and system administrators, respectively, are projected to decline at compound annual growth rates (CAGR) of -8.2% and -7.8% over the 2022–2027 forecast period. By comparison, the recently emerging roles of DataOps and MLOps are projected to have CAGRs of 17.9% and 20.1% respectively, although the growth is starting from comparatively small numbers.

DevOps and DevSecOps roles are also forecast to continue growing with DevSecOps roles showing a double-digit CAGR over the forecast period. DevSecOps roles will benefit from the growing application threat landscape and the dependence that organizations have on their software capabilities to be competitive, combined with the recognition that incorporating security as early as possible in the software development life cycle reduces costs and increases quality. DevOps growth will be muted somewhat by the growth in platform engineering roles, which will absorb some of these same functions.

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IT Professionals Experiencing Substantial Shift in Responsibilities

The roles and activities performed by IT professionals have evolved dramatically over the past ten years due to the convergence of modern development technologies, cloud platforms, and as-a-service offerings that can significantly improve overall productivity.

Today, many of these professionals find themselves in hybrid roles that combine traditional development activities with activities that formerly were associated with operations professionals who historically had few or no development-oriented responsibilities. A new International Data Corporation (IDC) report provides an extended census and forecast with detail for both traditional IT operations roles and these new hybrid roles.

"The census data shows that a dramatic, once-in-a-generation shift in the composition of the IT workforce is underway. This shift is akin to what took place during the years from 1997 to 2002 when the emergence of the commercial internet and the .com era turned priorities upside down for much of corporate IT and led to the hiring of vast numbers of web developers and networking experts," said Al Gillen, Group VP, Software Development and Open Source, IDC. "The increased adoption of cloud computing is driving similar transitions today in IT teams supporting this modern deployment model."

In developing this data set, IDC used the following definitions to describe the roles broken out in the study:

DataOps uses a combination of technologies and methods with a focus on quality for consistent and continuous delivery of data value, combining integrated and process-oriented perspectives on data with automation and methods analogous to agile software engineering.

DevOps uses collaborative, agile approaches paired with extensive automation development pipelines, testing, infrastructure configuration, provisioning, security controls, and life-cycle continuous integration (CI) for continuous development and continuous delivery (CD).

DevSecOps uses a methodology that asserts that security needs to be prioritized at the beginning of the DevOps delivery pipeline. It enables DevOps teams, collaborating with security, to act as key stakeholders in defining and implementing security policies.

ITOps uses technology and methods to provide routine, scheduled tasks and unscheduled support activities related to IT systems. ITOps professionals may spend as much as 50% of their time engaged with business users in support, the elicitation of requirements, and performing contingent or secondary business tasks.

MLOps uses technology and processes to streamline and automate the entire machine learning (ML) life cycle. The key capabilities include managing and automating ML data and pipelines, ML code, and ML models from data ingestion to model deployment, tracking, and monitoring. MLOps uses similar principles to DevOps practices, applied to machine learning processes.

Platform engineering is a discipline of designing and building toolchains and workflows that enable self-service capabilities focused on managing and optimizing the software delivery process to deploy applications and services to cloud platforms.

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Systems administrators configure, maintain, and support computer systems and systems of systems using a variety of tools and methods appropriate to the system or systems of systems in use. They may spend as much as 50% of their time engaged with business users in defining key requirements, business goals, and adaptations needed to maintain fit for use and fit for purpose.

At a macro level, the study shows that a substantial shift in the responsibilities of IT professionals will occur over the next five years. The data indicates that IT professionals in the most purely operational roles are facing a transition to a more technical or focused role that very often may involve some level of software development work. Accordingly, the roles of IT operations and system administrators, respectively, are projected to decline at compound annual growth rates (CAGR) of -8.2% and -7.8% over the 2022–2027 forecast period. By comparison, the recently emerging roles of DataOps and MLOps are projected to have CAGRs of 17.9% and 20.1% respectively, although the growth is starting from comparatively small numbers.

DevOps and DevSecOps roles are also forecast to continue growing with DevSecOps roles showing a double-digit CAGR over the forecast period. DevSecOps roles will benefit from the growing application threat landscape and the dependence that organizations have on their software capabilities to be competitive, combined with the recognition that incorporating security as early as possible in the software development life cycle reduces costs and increases quality. DevOps growth will be muted somewhat by the growth in platform engineering roles, which will absorb some of these same functions.

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Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

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The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

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As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

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Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

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