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A Practical NoOps Guide: How to Automate ITOps Work

Here are five categories of tools and practices that IT operations teams can leverage to come closer to the dream of NoOps.

Table of Contents
1. Infrastructure-as-Code (and Everything-as-Code)
2. Generative AI
3. Centralization and Aggregation
4. Cloud-Based and Colocated Infrastructure
5. Manual Operations
6. Guidance for Putting NoOps into Practice

It would be hard to find an engineer who doesn't wish for NoOps to become a reality. By fully automating IT operations work, NoOps promises to free engineers from the tedium and toil that distracts them from more interesting tasks.

But the challenge that no one has solved is how to actually achieve NoOps. And while IT Pro Today doesn't have a complete answer, we have prepared this NoOps guide to offer actionable tips on bringing NoOps closer to reality — even if you never quite get to an operations strategy that is completely and utterly automated.

So, keep reading for a guide to NoOps based on the technologies that IT engineers have at their disposal today. We break the discussion down by looking at different categories of tools and practices that IT operations teams can leverage to make NoOps — or something approaching it — happen in practice.

Related: What Is NoOps?

1. Infrastructure-as-Code (and Everything-as-Code)

One of the simplest and most important types of tools for achieving NoOps is infrastructure-as-code, or IaC. IaC makes it possible to automate complex, large-scale provisioning operations by writing code that defines how resources should be configured. From there, IaC tools apply the configurations automatically.

IaC has been around for years, but ITOps teams looking to achieve NoOps should keep in mind that modern IaC isn't strictly about provisioning infrastructure. Today, we live in an "everything-as-code" age where virtually any type of IT resource, process, or service can be automated using code — a practice that brings NoOps within reach.

2. Generative AI

Generative AI technologies such as ChatGPT and Copilot have generated a lot of buzz for their ability to automate complex tasks, like writing text and code, that once required genuine human effort (and still arguably do, but that's a debate for a different blog post).

For now, there hasn't been much discussion about applying generative AI technologies to IT operations. But if AI can write code, it could also potentially do things like parse log files, find the root cause of performance issues, and automatically remediate problems — all of which are tasks that operations teams would otherwise have to perform manually.

Related: AI-Assisted Coding: What Software Developers Need to Know

In that sense, generative AI should be a key component of any practical guide to NoOps. Tools designed to apply generative AI to NoOps may not quite exist, but it's a decent bet that they're on the way.

3. Centralization and Aggregation

Another key guiding principle for implementing NoOps is to centralize and aggregate IT resources as fully as possible.

By this, we mean unifying disparate systems and resources such that they can be managed centrally. Physical infrastructure should be unified using software-defined abstractions that make it possible to scale up or down without touching hardware, for example. As another example, workloads hosted in different clouds as part of a multicloud strategy should be integrated so that they can be monitored and managed using centralized tooling.

Related: Can AI Help Automate IT Operations?

Setting up centralization takes effort because there is no automated means of integrating complex, distinct systems (at least not yet). But once the centralization is there, operations work becomes significantly easier to automate because the automation tools can work from a centralized vantage point.

4. Cloud-Based and Colocated Infrastructure

One of the fundamental challenges of achieving NoOps is that hardware management is difficult to automate. Therefore, if you have to maintain your own physical infrastructure, you're going to have a hard time automating operations completely.

The solution to this challenge is to get rid of your on-premises infrastructure — by moving workloads either into the public cloud or (if you want the control of on-prem infrastructure without the responsibility of managing your own data center) into colocation.

When you get rid of on-premises hardware, you move a big step closer to NoOps.

5. Manual Operations

A practical NoOps guide wouldn't be complete if it didn't recognize that some amount of manual work will always be necessary. Even if it's only to set up automation tools or troubleshoot problems with automated processes, humans will always need to be a feature of the NoOps loop.

That's why ITOps teams pursuing NoOps should identify processes that they can't automate using tools like those described above, then determine how best to manage those manual processes within workflows that are otherwise automated. It's better to plan for manual work upfront than to automate as much as you can and only then figure out which processes fall through the automation cracks.

Guidance for Putting NoOps into Practice

The types of tools described above are examples of solutions that operations teams can leverage today to come closer to the dream of NoOps, even if they never fully do away with manual work.

And perhaps that's the key point: Complete NoOps may not be practical, but what is practical is leveraging the NoOps concept as inspiration for reducing manual effort as much as possible. Just as "the struggle itself towards the heights is enough to fill a man's heart," as Albert Camus wrote about Sisyphus, working toward NoOps is enough to bring practical value to modern operations.

About the author

Christopher Tozzi headshotChristopher Tozzi is a technology analyst with subject matter expertise in cloud computing, application development, open source software, virtualization, containers and more. He also lectures at a major university in the Albany, New York, area. His book, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” was published by MIT Press.
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