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Published Date: June 1st, 2022
NoOps, which stands for “no operations,” is the idea that an organization’s IT and data management can be handled entirely by automation, requiring no human intervention.
In data management and IT, organizations have embraced a number of concepts around the operations of various functions, including ITOps (short for IT Operations), AIOps (short for artificial intelligence for operations) and DevOps, (which brings together software development and IT operations to create a continuous, unified process of software development, testing and iteration).
In line with trends toward streamlining operations initiatives, organizations and service providers have increasingly turned toward automation as a way to deploy goods and services more quickly. NoOps emerged from the idea that if enterprises can use AI to increasingly automate their IT operations, then they might be able to use it to do the entire job — meaning manual intervention may not be needed in IT operations whatsoever, from patch management to backup activities and beyond.
This concept might be confusing to some business leaders aiming to reduce operational overhead but not knowing where to start or what solution would work best with their particular organization or teams. And many others may consider the idea of completely removing humans from the process unrealistic at best, seeing NoOps more as an aspirational goal than a blueprint to strictly follow.
NoOps experts claim it could not only take on the simpler, mundane tasks that IT departments handle but also the more complex processes and workflows now reserved for human workers. But is this going to eliminate the need for DevOps? Or is NoOps just a next step in its evolution? In this article, we’ll explore the problem NoOps addresses, how it’s impacting DevOps, and if and how AI automation is leading toward a NoOps future.
What problem does NoOps address? What concepts are behind the NoOps movement?
NoOps is based around various digital transformation philosophies that propose that software can perform the same tasks that the people of the IT department do. Essentially, both the dev and IT departments in almost any organization are service organizations that design, plan, provision and maintain IT infrastructure. Thus, some organizations view IT industry and operations professionals — especially those who oversee legacy systems — as an overhead expense to be tightly monitored, even as the demands on the IT department are increasing. On the other hand, as demands have grown, some IT organizations have responded by becoming more process-oriented.
As an answer to this conundrum, the NoOps approach aims to decrease the required Ops expertise an enterprise needs to keep pace with increasing demands on its dev and IT departments and enables developers to focus solely on writing and improving the product's code. It achieves this by implementing more processes and resources to improve the product, infrastructure, management, security and operations, evolving the platform to become completely automated. Ultimately, all operations become controlled by that particular automated system.
In many ways, NoOps represents a step forward in both innovation and efficiency. With NoOps, the developer team does not need to communicate with the system administrators regarding any infrastructural concerns. With the right tools, such as Platform as a Service (PaaS) in the cloud or Function as a Service, a NoOps environment can often achieve a faster deployment process than DevOps, making it an appealing methodology for startups, small-scale applications and Product as a Service companies.
Is AI automation leading to NoOps?
The increasing success of AI in IT Operations (AIOps) has inspired the NoOps movement in many ways. On the surface, they share some of the same goals: to automate mundane tasks, speed up mean time to resolution (MTTR) and allow faster, more efficient and more effective IT operations. Both AIOps and NoOps also give free time back to the IT operations teams so that they can focus more of their time, expertise and creativity on helping meet the higher-level needs of the business.
One area where AIOps and NoOps diverge is in the distinction between what can only be done by a human and what can be replaced by AI. As AIOps capabilities continue to evolve, the tasks it can accomplish without human interaction are becoming more numerous and complex. What’s more, AIOps does not currently apply to a much wider range of potential applications than NoOps and is not intended to replace human IT professionals. As a result, some experts feel that AIOps has a more realistic chance of achieving these shared goals than the NoOps approach.
It is worth noting, however, that the underpinnings of NoOps lie in the ability to provision and manage infrastructure as code. Without the ability to use APIs to manage underlying infrastructure, no amount of AI would be able to replace humans.
How does NoOps compare to DevOps?
DevOps is an approach to IT delivery that combines people, practices and tools to break down silos between development and operations teams. DevOps teams accelerate the development of applications and services and — with a more responsive approach to management of the IT infrastructure — can deploy and update IT products at the speed of the modern marketplace.
While DevOps focuses on the entire development lifecycle, NoOps has more of a focus on continuous delivery and provisioning, accelerating the process of implementing new equipment by removing unnecessary human intervention. Even proponents of NoOps often agree that DevOps includes a much more complex series of interactions over a longer period of time than the tasks NoOps can accomplish.
Here are a few ways in which DevOps and NoOps are aligned:
- DevOps practices require the collaborative efforts of both infrastructure experts and software experts.
- Both approaches aim to enhance the system lifecycle, from application development to deployment, through automation and improved methodologies. This increases delivery and deployment speed by streamlining processes across the lifecycle.
- NoOps cannot work independently of DevOps; they both need to be present to function seamlessly.
- NoOps and DevOps aim to improve the developer experience by creating and sustaining a self-service model.
However, while DevOps integrates development and operations skill sets, it is also difficult to achieve, especially in very large organizations. First, it presents challenges when developers and operations experts need to align on strategy and execution. DevOps requires infrastructure experts and software experts to work hand in hand — which means that the failure of one can cause the failure of the other. In a worst case scenario, this can result in the failure of the entire software development process. These types of obstacles led to questions in the proficiency of DevOps, which ultimately resulted in the emergence of the NoOps approach.
How does NoOps compare to ITOps?
NoOps aims to automate some aspects of ITOps that might currently involve human interaction. And like ITOps, NoOps will create a large number of logs, metrics and traces that require root cause analysis when things go wrong.
But while the success of AIOps has shown the potential for machine learning to make those processes faster and more efficient, ITOps does not aim to replace the human operator. Rather it is designed to provide the members of the IT team with data and information they can use to more effectively do their jobs — jobs that are often significantly more advanced, complex and dependent upon experience and imagination than AI-driven automation can currently handle.
NoOps shares many of the same goals with AIOps, automates aspects of ITOps, and touches on components of DevOps.
What are some of the potential benefits of NoOps?
The potential benefits of NoOps are on par with data-driven automation in any organization: ensuring uptime and security, preventing problems before they occur, increasing the efficiency of the IT organization and helping all stakeholders in the organization get the most value out of their data and their IT infrastructure.
Broken down, these benefits include:
- Maximized development time: To reduce friction between developers and infrastructure, NoOps completely automates the IT environment, requiring only a handful of developers to manage the project life cycle
- Full capacity of the cloud: NoOps uses cloud services and multicloud environments to minimize operations responsibilities by automating operations monitoring and maintenance. NoOPs implementation relies on PaaS, serverless computing and cloud computing, so the developer team doesn’t need to worry about resources and distributions.
- No manual intervention: With the level of automation in NoOps, there is little or no need for human intervention, greatly reducing or altogether eliminating the risk of human error.
- Cost-effectiveness: Because NoOps is a serverless computing model, consumers only pay for the duration of execution of functions and the number of executed functions. If a function is not executed, no charges are billed to the user.
- Increased productivity: NoOps allows both developers and operations professionals to invest more time in their respective job functions and become more productive, freeing them up for development and other high-level tasks that can lead to better business outcomes.
What are some challenges of NoOps?
One of the biggest challenges of NoOps is the ongoing pushback from those who feel that it is unrealistic and potentially dangerous to try to remove humans from the IT process. Even if NoOps is primarily used for provisioning and maintaining software and hardware, there are concerns around who will respond to issues that are beyond the capabilities of the automated systems. As IT infrastructures become more complex, many argue that the need for human oversight is greater than ever.
Beyond that, NoOps can potentially create additional issues, including:
- Increased workload on developers: There will always be a need to manage the infrastructure as well as the information about who uses services and the related cost, so there is no guarantee that NoOps will completely eliminate the need for the operations team. Thus these responsibilities could likely fall on the shoulders of the developers.
- Increased security risks and compliance issues: Because compliance regulations are applied to applications running on-premises or in the cloud, administrators would be required to communicate to the PaaS to close vulnerabilities, provide administrator access to sensitive information, and keep an eye on the activities of privileged users. Additionally, because the security team often relies on IT operations to manage network policy, administer identity governance, and enforce control, the elimination of the operations team would be offset by additional resources invested in security.
- Lack of compatibility: NoOps is not a universal solution, and as of now, several technologies are still not compatible with NoOps. Implementing NoOps is also not an effective option in cases where enterprises own their dedicated data centers.
- Learning gaps: With most of the now-automated responsibilities taken off their hands, administrators will be left to facilitate minor security patches and server management. The developers, on the other hand, will spend most of their time writing code, and testing and deploying it. This learning curve will continue to grow and evolve as the AI model is refined on larger data sets.
Benefits to NoOps include more uptime and security and preventing problems before they occur. But challenges can occur when designating responsibility for issues.
What types of companies will opt for NoOps?
NoOps is an excellent choice for software companies with an interest in scaling, optimizing development and automating everyday procedures. And advances in cloud computing have helped clear the path for enterprises of varying sizes to add NoOps into their existing processes and infrastructure. NoOps will most likely have a future and play a crucial role for many small businesses and Product-as-a-Service companies, helping them reach the market and become profitable faster.
Is NoOps a first step toward intelligent Ops?
Down the road, NoOps could potentially lead to intelligent Ops, where AI manages software with more accuracy — helping enterprises maintain smaller teams that are more productive and resilient as market demands steadily increase. Regardless of what the future holds, what seems clear is that the term will continue to evolve as vendors and analysts adjust their predictions and promises to line up with the practicalities of the technology.
While astonishing advances in automation have occurred over the last decade, we’re still a ways off from eliminating the human element. Also, it’s unlikely that NoOps will signify the end of DevOps altogether — a reliable methodology and discipline that has become ubiquitous in most large-scale applications.
However, it is safe to say that NoOps is a progressive step from DevOps. The future of NoOps is still uncertain and the concept may never get the traction some people might think it deserves. However, the experimentation it inspires may help organizations realize new benefits as they push their cloud and operations infrastructure to new limits.
