Information technology operations—more commonly referred to as IT operations or ITOps—is the process of implementing, managing, delivering and supporting IT services to meet the business needs of internal and external users.
ITOps is the core function of the IT department, which usually reports to the chief information officer. It is one of the four functions (along with technical management, application management and service desk management) defined in the IT Infrastructure Library (ITIL), the de facto industry standard best-practices framework for IT service management.
ITOps is at the forefront of IT service delivery, one of the most important cogs in the machinery that keeps an organization running. Businesses and their customers have become so reliant on instant access to IT services—data, software applications, public cloud and private cloud resources—that even a small interruption to these services can have far-reaching and costly consequences.
In recent years, ITOps tasks have been increasingly taken on by AI software, forming a new sub-field of IT operations called AI operations, referred to as AIOps.
AI capabilities such as natural language processing (NLP) and machine learning (ML) models are being used to automate ITOps tasks like collecting and aggregating huge volumes of data, separating and prioritizing significant event alerts from the noise of IT operations data, and correlating data to identify root causes and propose solutions.
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Whether it’s the financial industry, telecommunications or retail, today’s businesses and their customers rely on immediate access to applications and expect seamless customer experiences. This requires optimal performance from applications and the supporting IT resources that the applications run on, such as public cloud and private cloud infrastructure, data, networks and services. Even a brief IT outage can have a significant impact on business operations and quickly become costly. The primary role of IT operations is to ensure the smooth performance of IT and business technologies so that business operations can proceed uninterrupted.
The responsibilities of ITOps include:
- Managing resources: ITOps keeps IT infrastructure running. This includes hardware, software and networking infrastructure, as well as the apps that run on them. ITOps teams are responsible for managing and provisioning IT infrastructure resources for DevOps teams and maintaining service delivery and operation for customers and partners. This includes administering private, public and hybrid cloud environments, data center locations and equipment, operating systems, internet connectivity, firewalls and network security and other IT infrastructure components.
- Optimizing IT infrastructure: ITOps also looks for ways to improve infrastructure and performance while safely reducing cost. To do so, teams document hardware configurations and implement configurations that ensure optimal performance, as well as manage IT workloads, implement software, hardware and operating system upgrades, and assess the impact of proposed infrastructure changes.
- Ensuring application performance: ITOps plays a critical role in collaborating with line-of-business owners and application owners to ensure application performance. ITOps often assembles a recommendation of resourcing decisions for application owners to make sure that applications receive the compute, storage and network they require to prevent slowdowns and outages.
- Service desk support: Although the service desk is its own subset of the IT department in some organizations, support in others is handled by ITOps. Managing the help desk and ticketing system, troubleshooting issues and addressing the root cause of IT-related problems all fall under this support umbrella.
- Incident and security management: ITOps not only focuses on the day-to-day availability of IT services, but also develops plans for safeguarding future availability should problems arise. This includes performing data backups, restoring systems after an outage, developing a disaster recovery plan, establishing metrics for evaluating performance, auditing and working on regulatory compliance.
ITOps is often confused with IT operations management (ITOM) since both are closely involved in keeping IT services up and running. While ITOps refers to the people, roles and tasks related to IT service management, ITOM refers to the management processes and tools used to maintain the technology components, computing requirements and business processes companies use each day. ITOps teams oversee the services within the IT environment as well as the availability of all resources and IT applications, whether this is in day-to-day tasks or longer-term strategic planning. ITOM, a subset of ITOps, comprises the routine processes that ensure the overall quality, efficiency and user experience of IT resource delivery and the tools used to accomplish this goal.
DevOps aims to speed the delivery of higher-quality software by automating and integrating the efforts of development and IT operations teams. By linking these previously siloed units, organizations can build a software development and delivery process with continuous communication, collaboration and shared responsibility. The result is faster workflows and streamlined processes that meet software users’ ever-increasing demand for frequent, innovative new features and uninterrupted performance and availability.
In the DevOps model, IT teams support the software development and testing process by providing configuration, installation and troubleshooting support, database management and network infrastructure management. They also ensure that the infrastructure is meeting the needs of the development team. One way this is accomplished is by using Application Resource Management tools to guarantee applications have the resources they need, when they need it.
Throughout the DevOps lifecycle, both IT and development teams work to identify dependencies and test for issues, often by using automation. DevOps and ITOps use Application Performance Monitoring (APM) and observability tools to automatically analyze the root cause of issues and receive immediate feedback at each step of the software delivery pipeline when deploying new code or making changes to the system. This collaboration allows continuous delivery and deployment pipelines to flow smoothly and efficiently, enabling faster time to market for new applications and enhancements.
AIOps is the application of AI capabilities, such as NLP and machine learning models, to automate and streamline operational workflows. AIOps not only creates opportunities for automation and efficiency, but also directly addresses a significant challenge facing IT teams today. IT infrastructure components, applications and performance monitoring tools generate huge volumes of IT operations data—volumes that increase rapidly as organizations undertake digital transformation and adopt cloud computing services and hybrid cloud environments. Gartner estimates that the average enterprise IT infrastructure generates two to three times more IT operations data every year.
To better manage and leverage this data, IT operations teams are relying less on domain-based IT management tools and manual monitoring and intervention, and turning increasingly to data-driven, AI-powered automation.
AIOps enables IT operations teams to be more agile and responsive by helping to:
- Collect and aggregate huge volumes of both structured and unstructured data generated by multiple IT infrastructure components, applications, performance-monitoring tools and service ticketing systems
- Use automatic baselining to detect anomalies, moving users away from rules-based systems, toward dynamic, easy-to-use AI and ML systems
- Reduce ticket volume, group events and anomalies, and separate and prioritize significant event alerts from surrounding IT operations data
- Deliver the analyzed context of incidents, stitched across the full enterprise estate
- Correlate historical and real-time data to identify root causes of problems and propose solutions
- Automate labor-intensive IT processes and proactively mitigate high impact triggers
- Develop insights quickly with pre-trained models that accelerate time-to-value
- Improve mean time to detection and mean time to resolution through enhanced visibility and automated incident management and response
- Create operational efficiency and safely reduce IT cost by driving dynamic resourcing automation to meet real-time demands with zero waste
- Build a library of automation policies that further reduces manual management and processes
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