The CI/CD Pipeline Isn't What You Think: 5 Surprising Truths

We often talk about CI/CD as the engine of modern software delivery, a set of automated practices that let us build, test, and release code faster and more reliably. For many, the story ends there: write code, push it, and let the magic of automation handle the rest. This view, while not wrong, is like describing an iceberg by only its visible tip. It captures the general shape but misses the immense, complex structure hidden just beneath the surface.

Beneath the common understanding of CI/CD lie several counter-intuitive but crucial truths. These realities fundamentally change how we should think about, design, and leverage our pipelines. Ignoring them can lead to brittle automation, mismatched tools, and unforeseen risks. Understanding them, however, can transform a simple series of scripts into a strategic asset for your entire development organization.

This article pulls back the curtain on five of the most impactful of these truths. By exploring what CI/CD really is—and what it isn't—you can start building smarter, more resilient pipelines that deliver not just speed, but safety and genuine workflow efficiency.

1. It’s Not Just "CI/CD"—It's a Spectrum of Automation

The first layer of the iceberg to explore is the term "CI/CD" itself. It’s often used as a single, monolithic concept, but it actually bundles three distinct practices into one acronym. This can create confusion, as teams might say they're "doing CI/CD" when they are only practicing one part of it. Understanding the difference is the first step toward building a pipeline that matches your team's goals.

The journey begins with Continuous Integration (CI), the foundational practice where developers frequently merge their code changes into a central repository. Each merge triggers an automated process that builds the application and runs unit and integration tests to validate the new code. The primary goal of CI is to detect integration issues early and ensure the codebase is always in a buildable, testable state.

From there, we can progress to Continuous Delivery (CD). This practice extends CI by automating the release of validated code to a repository or registry after the build and test stages are complete. In continuous delivery, every change that passes the automated tests is packaged and made ready for production deployment. The crucial distinction is that the final deployment to the live production environment remains a manual, push-button step.

The final, fully automated stage is Continuous Deployment (also CD). It takes continuous delivery one step further by automatically releasing every change that passes all tests directly to production without any manual intervention. As the Red Hat documentation clarifies, "Continuous delivery stops short of automatic production deployment, while continuous deployment automatically releases the updates into the production environment." This distinction is vital. It forces a team to have an explicit conversation about its risk tolerance, the maturity of its testing suite, and the level of automation it is truly aiming for. But defining your automation goals is only half the battle; the next surprising truth is that the very platforms you use have goals that extend far beyond the traditional pipeline.

2. Your "CI/CD" Platform Can Automate Your Entire Workflow

Many developers see CI/CD tools as specialized runners for a linear set of tasks: build, test, and deploy. This view is becoming increasingly outdated. Digging deeper, we find that modern platforms, especially those tightly integrated with source control, are evolving into comprehensive automation engines for the entire developer workflow.

GitHub Actions is a prime example of this shift. It was designed from the ground up to be more than just a CI/CD executor.

GitHub Actions is a platform to automate developer workflows... and CI CD pipeline is just one of the many workflows that you can automate with GitHub Actions.

This shift is a natural evolution. As platforms like GitHub become the central hub for all developer activity—code, issues, pull requests, and project management—it makes sense for automation to expand beyond the pipeline to encompass the entire ecosystem, reducing context-switching for developers. You can use the same platform that builds your software to handle tedious, manual tasks, such as creating workflows that automatically:

• Label new issues as they are created.
• Sort issues and assign them to the correct team members.
• Send a welcome message to new contributors who open their first pull request.

This expanded scope reframes the value of these platforms. They are no longer just about getting code to production faster. They are about reducing cognitive load and eliminating friction from every corner of the development process. While these integrated platforms are powerful, their jack-of-all-trades nature reveals our third truth: for certain critical tasks, specialization is not just an advantage—it's a necessity.

3. No Single Tool Is the Best at Everything

In the quest for simplicity, teams often search for a single, all-in-one CI/CD tool that can handle every task imaginable. This desire, however, overlooks a critical reality at the heart of effective DevOps: specialization matters. The tool that excels at building a Java application is rarely the best choice for managing cloud infrastructure.

Just as restaurants may excel at a few popular specialty dishes, no CI/CD tool can build, test, and deploy absolutely everything to the same level of excellence.

This concept is best illustrated by comparing a general-purpose CI/CD tool with a specialized one. A generic platform might be perfectly capable of running maven build for a Java project. However, it will likely struggle with the unique demands of Infrastructure as Code (IaC). A tool like Spacelift, on the other hand, is purpose-built for IaC workflows (like Terraform, Pulumi, and Ansible), offering features like drift detection, policy enforcement, and dependency management that are simply absent in generic tools.

The insurtech company Kin discovered this firsthand, finding that a purpose-built platform was necessary to effectively manage the complexities of IaC at scale. Choosing the right tool isn't about finding one that can do the job; it's about finding the one that is designed for the job. Just as choosing the right tool is key, so is understanding that the pipeline you build with it is more than a simple script—it's a sophisticated safety system.

4. A Mature Pipeline Is a Risk Management Strategy, Not Just a Script

At its deepest level, a CI/CD pipeline is not just a sequence of commands like build -> test -> deploy. A mature pipeline is structured less like a script and more like a sophisticated, multi-stage safety net designed to manage the inherent risk of releasing changes to production.

Imagine a critical change is ready. Instead of a risky "big bang" deployment, a mature pipeline begins with a One-Box Deployment, cautiously exposing the change to a mere fraction of the production environment—perhaps 10% of hosts or even less. This tactical first step strictly limits the "blast radius" of any potential failure. If a catastrophic bug exists, its impact is immediately contained.

Once the new code is live on the one-box environment, it enters a Bake Period. The change is left to "bake" for a set time, perhaps a few hours, to catch latent bugs, memory leaks, or performance degradation that aren't immediately apparent. During this period, the system is under intense automated scrutiny, supported by a series of safety checks that act as tripwires. These include:

• Rollback Alarms: Automated monitors track critical metrics like error rates, latency, or even key business indicators. If any metric breaches a pre-defined threshold, an alarm triggers an automatic rollback to the previous stable version.
• Canaries: A canary is a function that runs on a constant interval in production, testing a core workflow with an expected input and verifying the output. If it ever fails, it provides an immediate, unambiguous signal that a critical user workflow is broken, triggering an alarm and a rollback.

This strategy fundamentally transforms the purpose of the pipeline. It is no longer just a tool for achieving speed; it is a sophisticated risk management system for achieving speed with safety. And such a sophisticated strategy can only be built upon a solid, well-understood foundation.

5. Where Your Jobs Run Is as Important as What They Run

Developers spend a great deal of time perfecting their pipeline configuration—the YAML file that defines the steps, commands, and logic. Yet, they often overlook an equally critical component: the underlying infrastructure where those jobs actually execute. The choice of execution environment has profound implications for performance, cost, security, and maintenance.

Different CI/CD platforms have fundamentally different architectural models:

• Jenkins: Uses a classic master/agent architecture. Agents can be permanent nodes (always-on servers) or dynamic cloud agents that are provisioned on-demand inside Docker containers or cloud instances.
• GitLab CI/CD: Relies on "Runners," which can be managed by GitLab or self-hosted. These runners often execute jobs inside isolated Docker containers.
• GitHub Actions: Executes jobs on servers fully managed by GitHub, offering a choice of environments including Ubuntu, Windows, and macOS.

The technical complexities in these environments run deep. For instance, a pipeline job itself might need to build a new container image. This "Docker in Docker" scenario—where the CI job itself, running in a container, must spawn another Docker daemon to build a new image—is a prime example of the deep environmental complexities that developers must manage, which are often invisible in the simple YAML file.

Whether you use a managed cloud service or self-host your runners, and whether those runners are VMs or ephemeral containers, is not a minor detail. This decision directly impacts your operational burden, security posture, build speeds, and monthly bill. The environment is not just a backdrop for your pipeline script; it is an active and critical part of your automation strategy.

Beyond Automation: A New Perspective on CI/CD

Seeing beneath the surface of the CI/CD iceberg reveals a strategic landscape far more nuanced than simple automation. These five truths are not isolated facts; they form a holistic framework for thinking. Understanding the spectrum of automation (Truth 1) allows you to select the right specialized tool (Truth 3) for the job, which increasingly can automate your entire workflow (Truth 2). This combination enables you to build a true risk management strategy (Truth 4), a feat that is only possible when you pay close attention to the foundational execution environment (Truth 5).

As you reflect on these truths, the essential question becomes not "Are we doing CI/CD?" but "How can we design our pipelines more intentionally?" Take a moment to consider your own workflows. Which of these surprising realities will most impact how you build, manage, and evolve your delivery process from this day forward?