In a world with shifting paradigms that redefine the way organizations run, businesses continue to look for effective new ways to improve application development and delivery. According to Gartner, worldwide IT spending will reach $4.1 trillion in 2021 which is an 8.4% increase from 2020. As a result, IT no longer plays a supporting role in business operations, rather it has become a key business driver.

To keep up with the demands of digital-first organizations, IT operations are constantly changing to meet increasing workloads and complexity. In this article, we take a look at some Ops paradigms (DevOps, ContentOps, GitOps, MLOps etc.) at the core of every organization. 

AIOps

AIOps stands for artificial intelligence for IT operations. AIOps is a model that recognizes that advances in big data and machine learning are the keys to building new approaches in the rapidly evolving IT environment. The concept refers to a set of technologies that utilize analytics and machine learning (ML) to enhance and automate IT operations. 

AIOps platforms use big data to gather data from various IT operations tools and devices to detect and address issues immediately, instead of relying on outdated historical analytics. Businesses can improve the decision-making process for I&O roles by analyzing a large amount of operational data. With it, I&O leaders can enhance IT service management and automation and gain insights seamlessly throughout the application lifecycle.

AIOps encompasses three different IT disciplines to achieve its goal of delivering continuous improvements and insights: operations management, performance management, and automation.

ContentOps

ContentOps, or Content Operations, refers to the process of planning, creating, deleting, editing, scheduling, publishing, or archiving all types of content. It is the combination of people, processes, and technologies vital to the production, distribution, and maintenance of any organization’s content. 

Large organizations with many siloed departments rely on ContentOps specialists to manage digital content. These specialists ensure to clearly define the roles of the people involved and avoid any overlap, duplication, or gap in duties. Contributions to content creation are made only at appropriate times by each member. 

DataOps

DataOps combines Data management and IT operations. The DataOps practice aims to improve collaboration, integration, and automation of data flows among data managers and data consumers within an organization. With DataOps, the objective is to create predictability in the delivery and management of data, data models, and related artifacts, allowing for faster value delivery. 

DataOps is a collection of workflows, technical practices, and automation that enables analytic and data management teams to collaborate more efficiently, improve quality, and reduce cycle times.

By implementing DataOps, businesses can automate the creation, deployment, and management of data along with appropriate levels of governance. Furthermore, they use metadata to make data more usable and valuable in dynamic environments.

DevOps

DevOps refers to a set of practices that combines development and operations with tools that allow an organization to deliver applications more quickly. Essentially, DevOps streamlines the software development process and ensures quality delivery by improving collaboration between the development and operations teams.

DevOps represents a shift in IT culture by embracing agile, lean practices to deliver rapid IT services. The DevOps approach makes use of technology—automation tools— for continuous integration and continuous delivery, continuous testing, continuous deployment, continuous monitoring, and infrastructure as code processes.

DevContentOps

DevContentOps is a term that combines software development processes, content management and ContentOps processes, and IT operations to improve efficiency and collaboration for content-driven applications. DevContentOps helps to unify DevOps and ContentOps approaches by facilitating seamless collaboration between content managers, developers, and IT operations.

DevContentOps relies on a distributed repository that combines both content and code, with CI/CD and continuous publishing capabilities. Importantly, it enables content and code migration between multiple development and production environments. 

DevSecOps

DevSecOps combines the methodologies and principles of DevOps with a focus on security and stability. It integrates security, testing, and compliance throughout the entire DevOps pipeline. By testing and checking your application at every stage of development, DevSecOps ensures a thorough and secure deployment of an application. 

The goal of DevSecOps is to improve the workflow continuously, as DevOps does. The testing process is continuously improved by adding previously untested aspects of the application. Code review, security, and quality are all treated as the responsibilities of all stakeholders. 

GitOps

GitOps is a standardized approach to deploying, configuring, monitoring, updating, and managing infrastructure as code. GitOps keeps documentation, code, and any other information related to deployment in a version control system like Git, and makes updates automatically using automated directors.

With GitOps, developers can manage operation processes using their version control system and Git. To deploy, developers simply use pull requests or merge requests as they would for merging code.

ITOps

ITOps, or IT operations, refers to the framework and processes associated with the implementation, management, delivery, and support of IT services to meet the business needs of internal and external users. It is the umbrella term for all processes and services provided by an organization’s IT department.

MLOps

MLOps is a set of practices for reliably and efficiently deploying and maintaining machine learning models. It merges machine learning and DevOps in a continuous application development approach.

In MLOps, tests and the development of machine learning models are carried out on isolated systems. MLOps teams consist of Data Scientists, DevOps engineers, and Machine Learning engineers, whose task is to integrate algorithms into production. It is concerned with automating and improving production techniques while also addressing regulatory and business requirements.

NoOps

NoOps is the concept that operations can be completely automated, with zero need for software management. NoOps follows a trend that has been in development for over a decade now.

To achieve NoOps, enterprises must embrace automation, machine learning, and artificial intelligence to automate tedious, repetitive, and mundane tasks that employees do.

However, NoOps is an aspirational concept according to some industry leaders, rather than being a practical strategy. They argue that it is unlikely to replace all manual processes, whether internal or external.

SaaSOps

SaaSOps combines software-as-a-service and automated operations. It is a set of practices that refers to the way software-as-a-service applications are accessed, managed, and secured, and by doing so improve efficiency, collaboration, and employee satisfaction.

SecOps

SecOps or security operations is an approach that focuses on automating critical security tasks to ensure as much security as possible in applications. It is a movement born out of the need to integrate IT security and operations teams, and their technologies and processes to safeguard systems, reduce business risk, strengthen agility, and streamline operations. 

Choosing What Works For Your Company Culture

Deciding on a development approach for your business can be an arduous task. The sets of practices in this article are a great way to start proffering solutions to the application development lifecycle. 

Before any business can achieve their set goal of rapid and secure application development, it's necessary to embrace the practices that actually fit your organization. With just the right tools and approaches, you can increase productivity, reduce time-to-market, harden security, and efficiently track and monitor application development progress through the entire lifecycle.

No matter the approach you decide to choose, ensure to always review and revise your application development process to meet your organization's target goals.