YAML Schema Validator

Validate your YAML data against a JSON Schema definition. This advanced tool checks for correct structure, data types, and custom constraints, ensuring data integrity.

YAML Schema Validator

Validate YAML data against a schema definition

YAML Input

Schema Definition

Schema Syntax

Types: string, integer, number, boolean, any
Constraints: required, min:N, max:N, pattern:regex
Example: age: integer(required, min:0, max:150)

How YAML Schema Validation Works

YAML schema validation checks your YAML data against a JSON Schema definition. The schema specifies required fields, data types, value constraints, and structure rules. The validator reports any violations.

This tool parses both your YAML data and JSON Schema, then validates the data structure against schema rules. Errors include missing required fields, type mismatches, constraint violations, and structural issues.

What gets validated:

Required fields presence
Data type correctness (string, number, boolean)
Value constraints (min/max, pattern, enum)
Nested structure compliance
Array item types and counts

Schema versions: Supports JSON Schema Draft 7 and Draft 2020-12. Choose based on your schema version for accurate validation.

When You'd Actually Use This

Configuration validation

Validate config files against schema. Ensure application configurations meet required structure before deployment.

CI/CD pipeline checks

Add validation to pipelines. Catch configuration errors early in CI before deployment causes failures.

API request validation

Validate YAML API payloads. Ensure incoming YAML data matches expected schema before processing.

Kubernetes manifest validation

Validate K8s resources against schemas. Check Kubernetes manifests for required fields and correct types.

Data quality assurance

Ensure data quality in YAML files. Validate data exports, imports, and transformations against schemas.

Schema development

Test and refine JSON Schemas. Validate sample data against draft schemas during schema development.

What to Know About Schema Validation

JSON Schema is the standard. JSON Schema is widely supported for validating JSON/YAML data. Many tools and languages have JSON Schema validators.

Validation is structural. Schema validates structure and types, not semantic correctness. Data can be valid but still wrong for your use case.

Error messages are specific. Validation errors include JSON Path to the problematic field, making it easy to locate and fix issues.

Schemas can be complex. Advanced schemas use references, conditionals, and complex constraints. Ensure your schema is valid before validating data.

Pro tip: Start with simple schemas and add complexity gradually. Test each constraint with sample data to ensure it works as expected.

Common Questions

What is JSON Schema?

JSON Schema is a vocabulary for annotating and validating JSON documents. It works with YAML too since YAML is a superset of JSON.

Which schema versions are supported?

Draft 7 and Draft 2020-12 are commonly supported. Choose the version that matches your schema specification.

How do I write a schema?

Define type, required fields, and constraints. Example: { type: object, required: ['name'], properties: { name: { type: string } } }

Can I validate arrays?

Yes. Schemas can specify array item types, minimum/maximum items, and unique items constraints.

What about nested validation?

Fully supported. Schemas can define nested object structures with their own constraints at any depth.

Does it support custom formats?

Standard format validators include email, uri, date, etc. Custom formats may require additional validation logic.

Is my data secure?

Yes. All validation happens locally in your browser. Your YAML and schema never leave your computer.

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