What is the difference between GitOps and CI/CD?

CI/CD pipelines have become the backbone of modern software delivery. Developers push code, automated tests run, builds complete, and deployments happen. But as infrastructure becomes more complex and deployment environments multiply, CI/CD workflows show their limitations. GitOps emerged as a response to these challenges, particularly for teams managing Kubernetes and cloud-native infrastructure.

The question developers face is whether GitOps replaces CI/CD or extends it. The answer depends on what you’re deploying and how you manage your infrastructure.

CI/CD: How deployment works

CI/CD combines continuous integration with continuous delivery (or deployment). The pipeline triggers when developers commit code to a repository. Automated processes then build the code, run tests, and deploy to production.

The workflow follows a linear path:

• Developer commits code changes
• CI server detects the commit and starts the build
• Automated tests verify the code
• If tests pass, the pipeline builds artifacts
• The deployment stage pushes changes to the target environment
• The application updates in production

This push-based model has served development teams for years. The CI/CD tool has credentials to access production environments and actively pushes changes when the pipeline completes successfully.

Feature flags can decouple deployment from release in CI/CD pipelines. You can push code that contains new features but keep those features hidden from users until you’re ready. This separation lets teams deploy continuously while controlling when functionality becomes visible.

GitOps: Infrastructure as code meets version control

GitOps takes a different approach by making Git the single source of truth for your entire system state. Instead of CI/CD tools pushing changes to production, GitOps uses a pull-based model where operators running in your environment continuously watch Git repositories and sync any changes.

The system is configured declaratively. You define what your infrastructure should look like rather than scripting how to build it. When you want to change your production environment, you modify configuration files in Git and commit them. A GitOps operator detects the change and updates the environment to match.

With GitOps and tools like ArgoCD or Flux, your Kubernetes manifests, Helm charts, and infrastructure definitions live in Git. The operator compares the desired state in your repository with the actual state in your cluster. When it finds differences, it reconciles them by pulling the latest configuration and applying it.

This inversion of control changes how deployments work. Your CI pipeline builds and tests code, then updates configuration files in a Git repository. The GitOps operator handles the deployment by pulling those changes. Production credentials never leave your cluster because nothing external is pushing to it.

Core differences between the two approaches

Deployment direction

CI/CD pushes changes from an external pipeline to your environment. The CI server needs credentials to access production and actively deploys when tests pass.

GitOps pulls changes from Git into your environment. An operator runs inside your cluster, watches your repository, and syncs changes automatically. The environment controls its own deployment.

Source of truth

In CI/CD pipelines, your source code repository holds application code, but your actual production state might drift over time. Manual changes, debugging sessions, or emergency fixes can create discrepancies between what’s in Git and what’s running.

GitOps makes Git the definitive source of truth for everything. Your entire infrastructure configuration lives in version control. The operator continuously checks that production matches what’s in Git. When drift occurs, the system alerts you or auto-corrects back to the declared state.

Credential management

Push-based CI/CD requires your pipeline to store credentials for every environment it deploys to. These credentials typically have broad permissions since they need to update production systems.

Pull-based GitOps keeps credentials inside the target environment. The operator only needs read access to your Git repository. This reduces the attack surface because production credentials aren’t exposed to external systems.

Change process

CI/CD triggers deployments when code merges. The pipeline runs automatically after the merge completes.

GitOps makes pull requests the mechanism for both code and infrastructure changes. Reviewers examine proposed changes before they merge. Once approved and merged, the operator applies them. This creates an audit trail where every production change maps to a specific commit and pull request.

What GitOps adds to your workflow

GitOps doesn’t eliminate CI/CD pipelines. It repositions them. Your CI pipeline still builds code, runs tests, and creates artifacts. But instead of deploying directly, it updates configuration files in a GitOps repository.

For Kubernetes environments, this separation provides benefits:

• Your cluster becomes self-healing. If someone manually changes a resource, the operator reverts it to match Git
• Rollbacks become git reverts. You can restore any previous state by checking out an earlier commit
• Drift detection happens continuously. The operator knows when production diverges from the declared state
• Multi-cluster deployments use the same process. You can manage multiple environments from separate Git branches or repositories

When you’re running infrastructure as code with tools like Helm, treating your configuration as declarative and versioned gives you reliability. The GitOps operator handles the complexity of applying changes incrementally and safely.

When teams use each approach

Traditional push-based CI/CD works well when:

• You’re deploying applications to non-Kubernetes environments
• Your infrastructure doesn’t change frequently
• You have a small number of deployment targets
• Your team already has established CI/CD pipelines and processes

Teams often use CI/CD pipelines with feature flags to manage releases. The deployment happens via the pipeline, but features remain controlled through flag configuration rather than infrastructure changes.

Pull-based GitOps fits better when:

• You’re managing Kubernetes clusters
• You have multiple environments or clusters to coordinate
• Infrastructure changes happen frequently
• You need strict audit trails and change control
• You want to prevent configuration drift

Platform engineering teams building internal developer platforms often choose GitOps. It provides a golden path for shipping safely. A typical flow has developers pushing code, CI building and deploying to staging, automated checks running, and rollout policies applying based on GitOps configuration.

Combining both approaches

Many teams run hybrid models. Application code follows CI/CD with feature flags controlling what users see. Infrastructure and deployment configuration follow GitOps patterns.

Your CI pipeline might:

• Build and test application code
• Push container images to a registry
• Update image tags in a GitOps repository
• Let the GitOps operator handle the actual deployment

This combination gives you the speed of automated builds with the safety and auditability of declarative infrastructure management. Feature flags add another layer by letting you deploy code frequently while releasing features progressively.

Self-hosting tools on Kubernetes works smoothly with this model. You can pin chart versions in Git, test upgrades in staging, and get drift detection and automated rollouts through your GitOps setup.

Security and compliance considerations

GitOps reduces the blast radius of compromised credentials. In push-based deployments, if your CI server gets breached, an attacker potentially has direct access to production environments.

With GitOps, production credentials stay within the cluster. An attacker would need to compromise your Git repository and bypass pull request reviews to inject malicious changes. The audit trail from pull requests makes unauthorized changes visible.

The tradeoff is operational complexity. You need to run and monitor GitOps operators. These tools become critical infrastructure. Without them, your deployment process stops working.

What stays the same

Both approaches rely on automation, version control, and testing. Continuous integration remains essential. You still need to merge code regularly, run automated tests, and provide fast feedback to developers.

The shift is in how deployment happens and where control lies. CI/CD puts control in the pipeline. GitOps puts control in the target environment.

Feature management remains relevant in both models. Whether you’re using CI/CD pipelines or GitOps, decoupling deployment from release lets you ship code safely. You can push changes to production while keeping features hidden behind flags until you’re ready to activate them.

Making the choice

Start by examining your infrastructure. If you’re running primarily on Kubernetes and dealing with complex multi-cluster setups, GitOps provides tools designed for those environments. The declarative model and continuous reconciliation match how Kubernetes operates.

If your deployments span multiple platforms or you’re not in a Kubernetes-native environment, CI/CD with feature flags gives you flexibility without forcing infrastructure changes.

You don’t need to choose one approach permanently. Teams often start with CI/CD and adopt GitOps incrementally as their Kubernetes usage grows. The key is understanding what each approach optimizes for and where your team needs that optimization.

The trend in platform engineering points toward GitOps for infrastructure management while keeping CI/CD for application builds. Feature flags bridge the gap by giving you runtime control over what code does regardless of how it got deployed.

Trunk-based development works well with both approaches. Developers can merge to main frequently, and feature flags prevent incomplete features from affecting users. Feature lifecycle management ensures you track features from rollout to cleanup, avoiding tech debt.

FAQ

Does GitOps replace CI/CD?

No. GitOps changes how deployment happens but doesn’t replace the build and test phases of CI/CD. Your CI pipeline still builds code, runs tests, and creates artifacts. GitOps handles the deployment stage by pulling changes from Git rather than having the CI system push them.

Can I use feature flags with GitOps?

Yes. Feature flags work with both GitOps and CI/CD. GitOps manages infrastructure deployment, while feature flags control feature releases at runtime. Many teams use GitOps to deploy code and feature flags to control what users see.

Is GitOps only for Kubernetes?

GitOps works best with Kubernetes because the declarative model matches how Kubernetes operates. However, you can apply GitOps principles to other infrastructure using tools like Terraform.

What happens if the GitOps operator fails?

If the operator fails, new deployments won’t happen, but your running applications continue working. You should monitor the operator like any critical infrastructure. Most GitOps tools support high availability configurations to prevent single points of failure.

How do I handle secrets in GitOps?

Don’t commit secrets to Git repositories. Use tools like sealed-secrets, external-secrets, or your cloud provider’s secret manager. The GitOps repository references secrets by name, and the operator fetches actual values from a secure store.

Can I do emergency hotfixes with GitOps?

Yes, but you still go through Git. Make the change in your repository, merge it (possibly with expedited review), and the operator applies it. Some teams maintain separate paths for emergency changes, but bypassing Git defeats the audit trail GitOps provides.

Does GitOps slow down deployments?

The operator typically syncs changes within seconds to a few minutes. The delay depends on the operator’s polling interval. For most teams, this is acceptable. If you need faster deployments, you can configure webhooks to trigger immediate syncs on Git commits.

What’s the learning curve for GitOps?

If your team already uses Kubernetes and understands declarative configuration, the learning curve is moderate. The concepts differ from CI/CD, so expect a transition period. Start with a single application or environment before expanding to your full infrastructure.