What is YAML?
YAML (YAML Ain’t Markup Language) is a human-readable data serialization language that has become the de facto standard for configuration files in modern DevOps and software development. Originally released in 2001, YAML was designed to be more readable than XML and simpler than JSON for configuration purposes.
YAML powers Kubernetes manifests, Docker Compose stacks, Ansible playbooks, GitHub Actions workflows, GitLab CI pipelines, CircleCI configs, OpenAPI/Swagger specs, and countless application configuration files. Its reliance on indentation rather than brackets or tags makes it visually clean — but also makes it sensitive to formatting errors that block deploys and break builds.
How to Use the YAML Validator
- Paste your YAML content into the input area — a Kubernetes manifest, a
.gitlab-ci.yml, a Helm values file, or any YAML document. - Click “Validate” or press
Ctrl+Enterto check syntax. - Review any errors reported with line numbers and a short explanation.
- Fix the issues and re-validate until the file is clean.
The validator checks the most common YAML issues: tab characters, inconsistent indentation, duplicate keys, malformed key-value pairs, and incorrect list syntax. Everything runs in your browser — no upload, no signup, no waiting.
Common YAML Errors and How to Fix Them
Tab Characters
YAML strictly forbids tab characters for indentation. This is the single most common YAML error:
# Wrong (uses tabs)
server:
port: 8080
# Correct (uses spaces)
server:
port: 8080
Configure your editor to use spaces instead of tabs for YAML files. In VS Code, set "editor.insertSpaces": true and "editor.tabSize": 2 for .yml and .yaml files.
Inconsistent Indentation
All items at the same level must use the same number of spaces:
# Wrong
database:
host: localhost
port: 5432
# Correct
database:
host: localhost
port: 5432
Duplicate Keys
YAML doesn’t allow duplicate keys at the same level. The second value silently overwrites the first, which can cause hard-to-debug issues — especially in Kubernetes manifests where a duplicated name or port field can change deployment behavior in subtle ways:
# Wrong - 'port' appears twice
server:
port: 8080
host: localhost
port: 3000
Missing Colon in Key-Value Pairs
Every key must be followed by a colon and a space:
# Wrong
name John
# Correct
name: John
Validating CI/CD YAML — GitLab CI, GitHub Actions, CircleCI
CI/CD pipeline files are where YAML errors hurt the most: a single bad indent in .gitlab-ci.yml or .github/workflows/deploy.yml means a wasted commit, a failed pipeline run, and a few minutes of waiting just to learn you forgot a colon.
Paste your pipeline file into this validator before you push:
- GitLab CI (
.gitlab-ci.yml) — catches syntax errors before GitLab’s own runner does. For full schema validation against GitLab keywords (stages,script,rules,needs,extends), use GitLab’s built-in CI Lint at<your-project>/-/ci/lint. The two together — syntax here, schema there — give you near-zero failed-pipeline noise. - GitHub Actions (
.github/workflows/*.yml) — most failures are indentation underjobs:orsteps:. Validate first, then trust GitHub Actions to surface anything more semantic when it runs. - CircleCI (
.circleci/config.yml) — same pattern. Run a syntax check here, thencircleci config validatelocally for the schema layer. - Bitbucket Pipelines, Drone CI, Argo Workflows — all standard YAML, all validated the same way.
The principle: every modern pipeline tool layers schema rules on top of YAML, but they all assume the YAML itself parses. Catching syntax errors locally cuts the feedback loop from “push and wait 90 seconds” to “Ctrl+Enter, fix, push once”.
Validating Kubernetes Manifests and Helm Charts
Kubernetes is YAML’s most demanding home. A misindented field in a Deployment manifest can silently change the behavior of an entire cluster, and the error you eventually see from kubectl apply rarely points at the real cause.
Use this validator as the first step before any kubectl apply:
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
spec:
replicas: 3
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: my-app
image: my-app:1.0.0
ports:
- containerPort: 8080
For Helm charts, validate Chart.yaml, values.yaml, and any templates/*.yaml (after rendering — helm template my-release ./chart). For kustomization.yaml, the same rules apply.
After syntax passes here, layer on schema validation:
kubectl apply --dry-run=client -f file.yaml— catches schema issues without touching the cluster.kubectl apply --dry-run=server -f file.yaml— adds admission-controller checks (RBAC, validating webhooks, OPA policies).kubeval,kubeconform, orkube-linterfor offline schema validation against specific Kubernetes versions.
Each tool checks a different layer. This validator covers the bottom layer — the YAML itself — and runs in your browser, so cluster credentials never leave your machine.
YAML Validator vs yamllint (CLI)
yamllint is the canonical Python CLI tool for YAML checking and is what most teams add to CI. The two tools have different roles:
| This online validator | yamllint (CLI) | |
|---|---|---|
| Setup | None — open the page | pip install yamllint |
| Syntax errors | ✅ | ✅ |
| Style rules (line length, spacing, document markers) | Basic | Configurable, strict |
| Custom rule files | No | .yamllint config |
| Best for | Quick one-off checks, paste-and-go | CI/CD pipelines, team-wide enforcement |
| Privacy | Runs entirely in your browser | Runs locally |
Use this validator when you want an answer in three seconds. Add yamllint to your CI when you want consistent style across a team. They’re complementary, not alternatives — many developers use both daily.
YAML vs JSON
| Feature | YAML | JSON |
|---|---|---|
| Readability | More readable | More verbose |
| Comments | Supported (#) | Not supported |
| Indentation | Significant | Not significant |
| Data types | Auto-detected | Explicit |
| Trailing commas | Not applicable | Not allowed |
| Multi-line strings | Native support | Requires \n |
YAML is generally preferred for configuration files that humans edit frequently, while JSON is better suited for data exchange between systems and APIs. Many tools accept both formats, and you can convert between them with a JSON ↔ YAML converter.
YAML Best Practices
Use Consistent Indentation
Pick 2 spaces per level (the most common convention) and stick with it throughout your project. Configure your editor and linter to enforce this.
Quote Strings When Ambiguous
YAML auto-detects types, which can cause surprises. Values like yes, no, true, false, null, 1.0, and 3:00 are interpreted as booleans, null, floats, or sexagesimal numbers:
# Dangerous - interpreted as boolean true
country: Norway
uses_yaml: yes
# Safe - explicitly a string
country: "Norway"
uses_yaml: "yes"
This is known as the Norway problem: country code NO becomes the boolean false in older YAML 1.1 parsers. Modern YAML 1.2 fixed many of these, but most tools (including some Kubernetes tooling) still target 1.1 quirks.
Use Linting in CI/CD
Add YAML linting to your CI/CD pipeline using yamllint or a similar tool. This catches formatting issues before they reach production. A misconfigured YAML file in Kubernetes or Docker Compose can cause an entire deploy to fail or, worse, succeed in unexpected ways.
Validate Before Deploying
Always validate YAML configuration files before applying them to production systems. This online validator gives you instant feedback for one-off checks; for automated workflows, integrate a YAML linting step into your build pipeline. The combination — pre-commit checks locally, CI enforcement on every push — eliminates almost all YAML-related deploy failures.