Chapter 10: Making the Final Step to NoOps

Is it possible to execute IT operations without hands-on operations? Research and advisory companies, such as Gartner and Forrester, foresee an IT future based on NoOps. The big idea behind NoOps is that literally everything can be automated. It means an even bigger role for AI, and something called heuristic automation. How can an enterprise move to NoOps, and what is the role of an architect in this field? We will discuss this in this chapter.

After completing this chapter, you will be able to explain NoOps as a concept and why enterprises should adopt the principles of NoOps. You will learn what heuristic automation is and how it's driving the architecture of NoOps. The most important lesson that you will learn is that NoOps is not simply about having no need for any operations at all.

In this chapter, we're going to cover the following main topics:

• Understanding the paradigm shift to NoOps
• Understanding the...

Understanding the paradigm shift to NoOps

In the previous chapters, we discussed the introduction of artificial intelligence (AI) and machine learning (ML) into operations and development. In Chapter 9, Integrating AIOps in DevOps, we learned how an enterprise can leverage AI and ML in DevOps pipelines. The reason to do this is to make a lot of manual tasks obsolete through intelligent automation. NoOps takes all of this one step further: automate IT systems completely so there's no need for operators to manually intervene in the systems. How far away are we from that paradigm shift? In addition, is it realistic? We will discuss that in this section.

To answer the last question: NoOps seems to be more of an ideal than a real practice. The discussion around NoOps was initiated through the idea that teams could actually automate a lot of processes in development, especially regarding the deployment of applications. This started with services being provided as Software as a Service...

Understanding the role of AI in NoOps

In the previous section, we discussed whether NoOps provides a realistic way of operating for future enterprises. We've concluded that NoOps should be seen as both a concept and a way of thinking to leverage automation for operations. It's not about getting rid of operations as a whole – IT environments in enterprises have become too complex for that. Still, they have the challenge of using their IT talents in the most optimized way.

IT talent is becoming scarce, since the market demand for skilled and trained engineers is increasing at high speed. Because of this scarcity, the costs of staff are also increasing. To keep costs down and still be able to work as agile as possible, enterprise architects will have to search for other ways to operate IT. IT talent can then fully focus on developments.

However, operations will be needed. We need people to look after systems, and make sure that these systems are running stably...

Creating an architecture for heuristic automation

First, let's get a definition of heuristic: in the literature, it is referred to as applying a solution to an issue without the aim of being the optimal solution, but sufficient to fix the immediate problem that was discovered. Trial and error would certainly match this definition. The Hungarian mathematician George Pólya used the term in his book, How to Solve It, first published in 1945. He provided some practical ways of solving problems.

One of his principles is commonly used in architecture applying ML: if you don't have a solution, assume that you have a solution and see what it does. Keep the good stuff and analyze the bits that didn't work well. Try the iterated solution again and learn from it. This is the base of heuristic automation. It uses heuristic learning that can be leveraged through AI that is able to recognize and learn from patterns. AI will use algorithms and automation – it constantly...

Defining the roadmap to NoOps

NoOps is not a leap of faith. As with DevOps and AIOps, any next step requires a plan and a roadmap. Using the principles of heuristic automation and AIOps, we can leverage automation for intelligent automation, collaborating with cloud-native automation, and automated application deployment in CI/CD pipelines.

The following figure shows how NoOps consists of three major components. These three components are the roadmap to get to a level of automation where dedicated operations are no longer required. DevOps teams are end-to-end responsible for the development, deployment, running, and maintenance of the code, supported by fully automated processes and AI:

Figure 10.3 – Components of NoOps

The end state is predictive automation using predictive analytics that analyzes current data to eventually make predictions for the future. It includes the following:

• Scaling for future needs, for instance by analyzing...

Summary

In this chapter, we discussed the concept of NoOps – no operations. We discovered that the term might be misleading, since NoOps doesn't mean that the enterprise will no longer need operations at all. NoOps is a concept that leverages automation to its maximum potential. By automating development, deployment, and operations, scarce IT talent can focus on new features, since NoOps will help them by identifying and solving issues in IT systems fast. We've learned that NoOps (like AIOps) uses AI and ML. But NoOps also means that enterprises will need to embrace the shift-left mentality.

We've also learned that NoOps requires a specific type of architecture for heuristic automation: applying iterative solutions, learning from these solutions, and continuously improving them. We also discussed the different components of heuristic automation. In the final section, we explored a possible roadmap from DevOps to NoOps. We concluded that we already have the...

Questions

1. A system detects an unexpected issue, knows how to solve it from history or by learning, and eventually applies the fix automatically. What do we call this type of action?
2. What type of learning is typically used by AI-driven systems to automate remediating actions?
3. True or false: predictive automation is applied to scaling that predicts the future usage of systems.

Further reading

• Blog about NoOps on CIO.com by Mary K. Pratt: https://www.cio.com/article/3407714/what-is-noops-the-quest-for-fully-automated-it-operations.html
• Blog about heuristic automation of infrastructure by Ramkumar Balasubramanian: https://www.linkedin.com/pulse/heuristic-automation-infrastructure-ramkumar-balasubramanian/