What is GitOps?

GitOps is a way to manage and update software systems by storing all the desired settings and code in a Git repository, then letting automated tools apply those changes to the live environment. It treats the Git repo like a single source of truth, so any change goes through a pull request and is automatically synced to the running system.

Let's break it down

  • Git: a popular tool for saving versions of code and files, letting many people work together and track every change.
  • Ops: short for operations, the work of keeping servers, containers, and other infrastructure running smoothly.
  • Single source of truth: one place (the Git repo) where the correct, up-to-date configuration lives, so everyone looks at the same information.
  • Pull request: a request to add or modify files in the repo; it’s reviewed and approved before the change is accepted.
  • Automated sync: software (often called an operator or controller) watches the repo and automatically updates the live system to match what’s written there.
  • Declarative: you describe what the system should look like, not how to get there; the tool figures out the steps.

Why does it matter?

Because it makes deployments faster, safer, and easier to understand. Every change is recorded in Git, so you can see who did what, roll back mistakes instantly, and reduce human error by letting machines handle the actual updates.

Where is it used?

  • Deploying containerized applications on Kubernetes clusters, where the cluster state is kept in Git.
  • Managing cloud infrastructure (e.g., AWS, Azure) with tools like Terraform or Pulumi that store IaC files in Git.
  • Updating edge devices or IoT fleets by pushing configuration changes through a Git-backed pipeline.
  • Continuous delivery pipelines in enterprises that require strict audit trails and reproducible releases.

Good things about it

  • Version control & auditability: every change is logged, reviewed, and can be traced back.
  • Fast rollbacks: revert to a previous commit and the system automatically returns to that state.
  • Consistency: the same repo drives multiple environments, reducing drift between dev, test, and prod.
  • Automation: reduces manual steps, lowering the chance of human error.
  • Collaboration: teams use familiar Git workflows (branches, PRs) to coordinate changes.

Not-so-good things

  • Learning curve: teams need to understand Git workflows, declarative configs, and the specific operators used.
  • Tooling complexity: setting up and maintaining the sync controllers can be intricate, especially for legacy systems.
  • Latency: changes only take effect after the controller detects the repo update, which may add a short delay.
  • Not a fit for all workloads: highly dynamic or stateful applications that require frequent, ad-hoc tweaks may struggle with a purely declarative approach.