Everything-as-Code explained: How modern DevOps teams automate infrastructure, policy, testing, and more

Modern software development moves fast—but scaling safely and sustainably is another story. As systems become more complex, and teams grow more distributed, one principle is changing how top engineering orgs manage everything from infrastructure to policy to performance: treat it all as code.

This blog dives into the everything-as-code mindset—where it came from, how it works, and why it’s shaping the future of DevOps.

What is everything-as-code?

At some point, every software developer runs into the same friction: the code runs fine locally, but something breaks when it hits a different environment. Maybe a config file didn’t load. Maybe a setting was tweaked manually in staging. Maybe a production environment was “special.”

This is exactly what everything-as-code aims to solve.

Everything-as-code (EaC) or X-as-code (XaC) is a mindset that treats not just your application code—but your infrastructure, policies, testing, deployment, configuration, and monitoring—as version-controlled, human-readable files. In other words: if it can be defined, you define it as code. If it can be automated, you automate it. If it can be reviewed, you put it in Git.

The result? Fewer surprises, more consistency, and faster time to ship. Developers don’t have to guess how things are configured or how services are deployed because it’s all right there, in code.

Where it started: infrastructure-as-code and the rise of automation

The movement started with infrastructure-as-code (IaC). As companies shifted from physical servers to cloud platforms like AWS, Azure, and GCP, provisioning infrastructure by hand became painful—and error-prone.

Instead of clicking through cloud consoles (a practice now jokingly called “ClickOps”), teams began writing files that declared what infrastructure they needed: EC2 instances, load balancers, networks, storage volumes, databases. Tools like Terraform, AWS CloudFormation, and Azure Bicep made it possible to define entire production environments using code.

These files became part of the codebase. They could be tested, reviewed, versioned, and reused. Over time, what used to be complex, multi-step deployments turned into a single terraform apply.

This shift wasn’t just about infrastructure. It was about control—and bringing the entire deployment lifecycle under the same discipline as software development.

Beyond infrastructure: the growing ecosystem of “X-as-code”

Once infrastructure was in code, the natural question followed: what else should be? The answer turned out to be: almost everything.

Configuration-as-code

System settings, application flags, environment variables—they all change how your software behaves. With configuration-as-code, these values live in structured files like YAML or JSON and are deployed with your app.

That means:

• No more hunting down mystery configs in different systems
• Rollbacks are as simple as a Git revert
• Developers can confidently work across different environments

Platforms like Jenkins, Kubernetes, and Spring Boot all embrace this model. Configuration is no longer tribal knowledge, it’s content your team can reason about.

Pipeline-as-code

Instead of setting up CI/CD jobs through a GUI, developers now define build and deployment pipelines as code. GitHub Actions, GitLab CI, CircleCI, and Jenkins all support pipeline-as-code using YAML or Groovy.

This makes pipelines:

• Easier to maintain and replicate
• Auditable and secure
• Flexible across teams and projects

Your ci.yml file becomes the blueprint for how your application moves from commit to production.

Policy- and security-as-code

Manual security reviews can’t keep up with modern release cycles. That’s where policy-as-code comes in. Tools like OPA, Sentinel, and Kyverno let teams define policies using code—and enforce them automatically.

Example: You might define a rule that says all storage buckets must be encrypted. When someone tries to deploy unencrypted storage, the pipeline fails with a clear, code-defined response.

This lets companies enforce security at scale, without slowing down development.

Testing-as-code

Performance, integration, and unit testing have long been part of development. But test scenarios themselves? Those used to live in third-party tools or spreadsheets.

Now, testing is code too.

At Gatling, we believe load testing should be versioned and automated like everything else. Our Java, Scala, and JavaScript SDKs let you define user flows as code—and run them directly from your CI pipeline.

That means:

• Developers can own performance from day one
• Testing becomes part of every deployment
• Teams can spot regressions early, not after a customer complains

Load testing as code unlocks continuous performance validation.

Observability-as-code

Dashboards, alerts, and metrics aren’t just for SREs anymore. With observability-as-code, teams define monitoring resources in code and deploy them alongside applications.

For example:

• Grafana dashboards defined in JSON
• Datadog alerts managed via Terraform
• SLOs stored in version control using OpenSLO

This keeps observability consistent and replicable across services and environments.

Docs, data, and everything else-as-code

Even documentation is being versioned as code (think: Markdown in Git + static site generators like Docusaurus). Some teams manage their analytics pipelines, API gateways, and cost governance the same way.

Everything that changes, everything that matters is becoming code.

Why everything-as-code works

Treating your entire system as code isn’t about complexity. It’s about reducing it.

Here’s what teams gain from an everything-as-code approach:

Consistency across environments

You don’t want your application behaving differently in staging than in production. As-code ensures that your configuration, infrastructure, and policies are the same across every environment.

Version control and auditability

Code means history. Who changed what, when, and why. If something breaks, you can trace it. If something works, you can replicate it. Version control isn’t just for applications—it’s for systems.

Automation and speed

Manual steps slow teams down. Code removes bottlenecks by automating infrastructure, deployment, testing, and more.

Better collaboration

When developers, operations, and security teams all work from the same repo, everyone has visibility. No more silos. Everyone can contribute, review, and improve the same system.

Predictability and confidence

Code is predictable. It does the same thing every time. That means fewer surprises, more confidence in your releases, and better service for your customers.

But it’s not magic: common pitfalls to avoid

Everything-as-code is powerful but it’s not without challenges.

Here are a few traps to watch out for:

Steep learning curve

• Steep learning curve: Tools like Terraform, Kubernetes, and OPA have their own languages. Teams need time (and support) to learn them. Don’t assume everyone can ramp up instantly.
• Siloed adoption: Putting your infrastructure in code doesn’t help if only one person knows how it works. As-code should be a shared responsibility—not a black box.
• YAML fatigue: Let’s face it: complex configuration files can become hard to manage. Use modules, reuse patterns, and document your intent. Code should make things clearer, not murkier.
• Policy sprawl: Policy-as-code can become a mess if every team writes their own rules in isolation. Define shared policies, reuse templates, and use the right tools for visibility and enforcement.

What’s next: the future of everything-as-code

This isn’t just a trend. Everything-as-code is evolving into the backbone of modern engineering organizations.

Here’s what’s coming next:

• AI-generated IaC and policies, helping teams bootstrap faster
• Smart pipelines that self-adjust based on code context
• Continuous compliance with real-time feedback
• Platform engineering that exposes all this functionality through internal self-service tools
• Org-as-code? Maybe one day, even company policies and workflows will be stored in Git

One thing is clear: companies that codify their systems will adapt faster, scale safer, and serve their customers better.

Why this matters for teams using Gatling

At Gatling, we built our load testing engine with this mindset from day one.

Our “test-as-code” approach lets developers:

• Write performance tests alongside application code
• Version and review tests in Git
• Run load tests as part of CI pipelines
• Deploy confidence—not just code

With Gatling Enterprise Edition, teams get enhanced functionality like distributed test infrastructure, advanced dashboards, and analytics that align technical response time metrics with business SLAs.

In a world where performance is a feature, testing has to be automated. And testing has to be code.

Final thoughts

Everything-as-code isn’t just a new tool in your stack. It’s a way to run your stack.

It brings clarity, consistency, and control to systems that used to rely on manual processes, best guesses, or long-lost documentation.

And most importantly, it gives developers the power to define, own, and evolve the systems they build—just like they do with application code.

In order to ship faster, safer, and smarter, your team needs more than the right tools. You need the right model.

Everything-as-code is that model. Let’s build it.

Want to see it in action? Book a demo and we’ll show you how.

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