In today’s digital age, businesses rely heavily on their IT operations to stay competitive and meet the growing demands of customers. As businesses become increasingly reliant on technology, the skills required to manage IT operations must evolve as well. For these reasons and more, the ITOps skills that matter most today are different in many respects from those that were the most important 10 or 20 years ago.

The evolution of ITOps Skills is crucial due to the necessity of IT operations engineers being able to work with data technologies to ensure businesses can effectively leverage their data resources. Data is one of the most valuable assets held by businesses, and it must be managed efficiently to provide the insights needed to make key business decisions. IT operations engineers must have proficiency in big data platforms like Hadoop and Spark, and understand data management tools such as Cassandra, MongoDB, and MySQL.

Software-defined networking, which enables the creation of abstract, virtual networks on top of physical network infrastructure, has exponentially increased the complexity of modern networks. Therefore, modern IT Ops engineers need to have the necessary skills to manage and maintain these complex networks. They need to be adept at working with software-defined networking solutions like VMware NSX and Cisco ACI.

Modern IT Ops engineers need to be able to manage large-scale distributed environments, such as Kubernetes clusters. Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. Working with containerized environments is becoming increasingly common, and the ability to manage them is an essential skill for modern IT Ops engineers.

The ability to understand complex cloud architectures, work with cloud-specific tools, and troubleshoot cloud performance issues are essential skills for modern IT Ops engineers. Cloud computing is a critical component of many modern IT operations, and engineers need to understand how cloud computing can be used to deliver scalable and reliable applications.

Although IT operations engineers aren’t usually responsible for security, they do need at least basic security skills. Knowing how to secure networks and applications is a crucial part of any IT operations role. Therefore, IT operations engineers need to have a solid understanding of security best practices, including how to secure networks, identify threats, and mitigate risks.

Project Management Skills for IT Operations Teams

As IT operations grow increasingly complex, the ability to manage IT operations projects becomes increasingly important. IT operations teams need to understand which IT systems and features the business requires, how much money the business can invest in those systems, and how to update those systems over time to ensure they continue meeting changing business needs. IT operations teams need to have strong project management skills to deliver projects on time and within budget.

In particular, IT operations teams need to understand business requirements, budgeting, resource allocation, system upkeep, and maintenance of IT systems. Understanding the business requirements involves identifying business goals and aligning IT operations with those goals. Budgeting and resource allocation involve understanding how much money and resources the business can invest in IT operations projects. System upkeep and maintenance involve ensuring that IT systems are running smoothly, are up-to-date and secure, and are delivering the expected results.

Systems Engineering in IT Operations (ITOps)

Systems engineering can assist IT operations teams in managing complexity, reducing costs, and aligning IT with business needs. The structured approach of systems engineering covers the entire lifecycle of complex systems, from design to implementation and maintenance. This is accomplished by breaking down complex systems into smaller, more manageable components and optimizing each component individually to improve overall system performance.

Systems engineering also ensures that IT and business are aligned by taking into consideration the business requirements and matching them against IT operation projects. Integration with the business ensures that IT operation projects contribute directly to the business goals and objectives.

Benefits of IT Ops Skills

An IT operations team that possesses all the skills described above can bring various benefits to a business. These benefits include technical expertise, analytical skills, collaboration skills, planning skills, and the ability to continuously improve IT operations and business operations.

Technical expertise is essential to ensure that IT operations projects are delivered as expected. Analytical skills are necessary to identify issues and provide effective solutions. Collaboration skills facilitate teamwork and communication among team members, vendors, and customers. Planning skills enable IT operations teams to optimize the use of resources and manage projects effectively. Finally, the ability to continuously improve IT operations and business operations ensures that the IT operations team can adapt to changing business requirements and stay ahead of the competition.

In conclusion, modern ITOps skills have evolved significantly over the last decade, driven by the emergence of new technologies, increased complexity, and growing business requirements. Today’s IT operations engineers need to be proficient in managing complex networks, working with big data platforms and cloud technologies, and possess project management skills. Systems engineering provides a structured approach to the design, implementation, and maintenance of complex systems while ensuring that IT and business are aligned. An IT operations team that brings all of these skills to the table provides significant benefits to businesses by optimizing the use of resources and enhancing the overall efficiency and effectiveness of IT operations.

Explore more

Agentic AI Redefines the Software Development Lifecycle

The quiet hum of servers executing tasks once performed by entire teams of developers now underpins the modern software engineering landscape, signaling a fundamental and irreversible shift in how digital products are conceived and built. The emergence of Agentic AI Workflows represents a significant advancement in the software development sector, moving far beyond the simple code-completion tools of the past.

Is AI Creating a Hidden DevOps Crisis?

The sophisticated artificial intelligence that powers real-time recommendations and autonomous systems is placing an unprecedented strain on the very DevOps foundations built to support it, revealing a silent but escalating crisis. As organizations race to deploy increasingly complex AI and machine learning models, they are discovering that the conventional, component-focused practices that served them well in the past are fundamentally

Agentic AI in Banking – Review

The vast majority of a bank’s operational costs are hidden within complex, multi-step workflows that have long resisted traditional automation efforts, a challenge now being met by a new generation of intelligent systems. Agentic and multiagent Artificial Intelligence represent a significant advancement in the banking sector, poised to fundamentally reshape operations. This review will explore the evolution of this technology,

Cooling Job Market Requires a New Talent Strategy

The once-frenzied rhythm of the American job market has slowed to a quiet, steady hum, signaling a profound and lasting transformation that demands an entirely new approach to organizational leadership and talent management. For human resources leaders accustomed to the high-stakes war for talent, the current landscape presents a different, more subtle challenge. The cooldown is not a momentary pause

What If You Hired for Potential, Not Pedigree?

In an increasingly dynamic business landscape, the long-standing practice of using traditional credentials like university degrees and linear career histories as primary hiring benchmarks is proving to be a fundamentally flawed predictor of job success. A more powerful and predictive model is rapidly gaining momentum, one that shifts the focus from a candidate’s past pedigree to their present capabilities and