DevOps: A Modern Vehicle for Business Growth and IT Excellence

DevOps: A Modern Vehicle for Business Growth and IT Excellence
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by Sanjeev Kapoor 02 Aug 2021

For many years software development activities were isolated from the actual deployment and operation of software systems. This has radically changed since the advent of cloud computing i.e. more than ten years ago.  The development of cloud-based software systems is strongly dependent on the underlying hosting infrastructure, which led software vendors to consider an integrated approach in the development, deployment and operation of software systems and services. This has also led to the emergence and the rise of the DevOps (Development and Operations) paradigm to building and operating software systems.

DevOps refers to a set of practices that integrate software development and IT operations in a single set of activities. It emphasizes agility and communication between different teams and project stakeholders. DevOps practices have been proven to shorten development times and improve software quality. Moreover, they enable a Continuous Integration and Continuous Delivery (CI/CD) approach that makes enterprises extremely responsive to changes. For all these reasons, DevOps is the state-of-the-art approach to software systems development, deployment and operation. DevOps’s benefits translate to specific improvements to business competitiveness, which are ultimately reflected in business results.


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The Business Benefits of DevOps

The business benefits of DevOps are specific and span all areas of software development and deployment.  In most cases, they translate to cost savings and improved results. Specifically:

  • Reduced Downtimes: DevOps provides continuous visibility to IT Operations, including the ability to trace potential problems. This is salient for many business enterprises, as it prevents downtimes and saves costs associated with the disruption of IT and business operations. Nowadays, critical business operations are increasingly dependent on digital infrastructures. Hence, IT service disruptions are in many cases associated with brand damage and lost revenues.
  • Improved Software and Operations Quality: DevOps facilitates the early identification and correction of software bugs. This reduces their impact on IT and business operations. According to international best practices, the cost of capturing and correcting a bug in the requirements and design phases is orders of magnitude less than if the bug makes it to the production.
  • Effective Collaboration: DevOps is all about proper communication and collaboration between the various teams involved in the design, deployment and operation of software systems. A DevOps approach mandates the collaboration between different IT and non-IT departments such as sales, marketing, finance, accounting and human resources. This collaboration fosters a seamless flow of critical information between different teams. Collaboration improves productivity and avoids errors due to a lack of timely access to required information.
  • Agility in Business Operations: DevOps companies can gain timely insights in operational issues, which is a foundation for the fine-tuning and optimization of business processes. In this direction, organizations can specify and monitor proper Key Performance Indicators (KPIs). Likewise, they can establish DevOps-driven root-cause analysis processes aimed at identifying the IT-related causes of operational problems.
  • Customer Centric Processes: DevOps platforms provide support for customer-centric processes, which create and exploit a 360o view of the customer in order to improve marketing, sales and loyalty management activities. In particular, DevOps-based CI/CD processes boost the real-time integration of customer-related information in software systems to drive customer centric analytics and the creation of customer-centric products.


DevOps Derivatives

The success of DevOps solutions has given rise to the emergence of similar software development and deployment models i.e., models that are characterized by agility and integration of development and operations. These models can be considered as DevOps derivatives. In many cases they can be combined with DevOps technologies in the scope of modern cloud-based IT infrastructures and related development processes. Prominent examples include:

  • DevSecOps: DevSecOps is concerned with the integration of security practices in the conventional DevOps paradigm. It aims at ensuring that all stakeholders consider the security implications of their decisions and actions. In this way, DevSecOps makes everyone accountable for security and speeds up development tasks without compromising security. Furthermore, DevSecOps ensures the timely and frequent integration of security solutions in a software system. For instance, it enables daily patching in response to the proliferating security vulnerabilities of state-of-the-art software platforms.
  • MLOps: MLOps focuses on the reliable and effective deployment of machine learning models, as part of wider software systems and services. It has recently emerged due to the growing interest in machine learning and data science. MLOPs involves frequent communications between data scientists and operations teams, much in the same way DevOps boosts the collaboration between software developers and IT operations’ departments. Based on MLOps, software and machine learning systems stakeholders increase the quality and shorten the development cycle of machine learning pipelines. As such they ease the scalable deployment of machine learning models in large-scale production environments.
  • AIOps: AIOps comprises practices that boost the data-driven management of software development infrastructures, IT infrastructures, and related processes. It facilitates the extraction and use of insights about the underlying infrastructures towards increasing the agility of development and deployment processes. For instance, AIOps produces intelligent alerts whenever some abnormality in IT operations is detected. Likewise, it facilitates real-time performance monitoring of the IT infrastructure and automates the ever-important root cause analysis in case of problems. AIOps is destined to reshape and improve DevOps through automation. It will enable teams to save time and become more creative instead of dealing with tedious tasks like the analysis of log files.


Overall, the combination of development and operations tasks is an undeniable trend. DevOps is the most prominent manifestation of this trend and a foundation for the development of similar approaches. Companies can no longer afford to ignore the DevOps wave. In case they dispense with other legacy development approaches, they must consider their transition to DevOps. DevOps adopters must attempt to reinforce their DevOps practices through updates and improvement in the DevOps solutions that they already use. Furthermore, modern enterprises should also keep an eye in the evolution of derivative paradigms like MLOps, AIOps, and DevSecOps. These paradigms provide merit for certain types of activities that involve machine learning pipelines and cybersecurity respectively. In most cases they do not come to replace, but rather to complement and reinforce DevOps: The future of software systems is certainly agile and will combine development and operations.

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