Yaml file validation

Enter your YAML in the input box below and you'll immediately get its syntax validated. Enter YAML, get it validated. There are no ads or downloads, and everything works right in your browser. Made for developers by developers from team Browserling. A link to this tool, including input, options and all chained tools. Import from file. Export to Pastebin. Can't convert. Chain with Remove chain. Remove no tools? This tool cannot be chained. Yaml validator tool What is a yaml validator?

If there are mistakes, then it returns a detailed syntax error message that explains what happened. It also tells the position of error and displays the conflicting snippet. Yaml validator examples Click to use. Invalid YAML file. It displays and error and a explains what happened. Valid YAML data without any errors. All checks pass and you get a green badge.

Pro tips Master online yaml tools. You can pass input to this tool via? Here's how to type it in your browser's address bar. Click to try! All yaml tools. Didn't find the tool you were looking for? Let us know what tool we are missing and we'll build it!

Highlight YAML. Let's now run the validation against the base-valid. Now, let's consider the following manifest with a valid image repository:.

Run the same check with the above manifest and there will be no violations reported:. But what if you want to express more complex logic and checks? What if you could express those checks with a real programming language? Copper V2 is a framework that validates manifests using custom checks — just like config-lint. Instead, tests are written in JavaScript and Copper provides a library with a few basic helpers to assist in reading Kubernetes objects and reporting errors.

You can follow the official documentation to install Copper. Similar to config-lint , Copper has no built-in checks. Let's write a check to make sure that deployments can pull container images only from a trusted repository such as my-company. Now, to run this check against our base-valid. As you can imagine, you can write more sophisticated checks such as validating domain names for Ingress manifests or reject any Pod that runs as privileged.

You can see all available helpers here. In addition to not having to learn a custom language, you have access to the entire JavaScript language for writing your checks such as string interpolation, functions, etc.

To learn more, you can visit the official project website. If Javascript isn't your preferred language and you prefer a language designed to query and describe policies, you should check out conftest. Conftest is a testing framework for configuration data that can be used to check and verify Kubernetes manifests.

Tests are written using the purpose-built query language, Rego. You can install conftest following the instructions on the project website. Similar to config-lint and copper, conftest doesn't come with any in-built checks. As for the previous example, you will check that the container is coming from a trusted source. Let's now run conftest to validate the manifest base-valid. Of course, it fails since the image isn't trusted. The above Rego file specifies a deny block which evaluates to a violation when true.

When you have more than one deny block, conftest checks them independently, and the overall result is a violation of any of the blocks results in a breach. Other than the default output format, conftest supports JSON, TAP, and a table format via the --output flag, which is excellent if you wish to integrate the reports with your existing Continuous Integration pipeline. To help debug policies, conftest has a convenient --trace flag which prints a trace of how conftest is parsing the specified policy files.

The commands, push and pull allow publishing an artefact and pulling an existing artefact from a remote registry. Let's see a demo of publishing the above policy to a local docker registry using conftest push.

From another terminal, navigate to the conftest-checks directory created above and run the following command:. The command should complete successfully with the following message:. Now, create a temporary directory and run the conftest pull command which will download the above bundle to the temporary directory:.

You will see that there is a new sub-directory policy in the temporary directory containing the policy file pushed earlier:.

Unfortunately, DockerHub is not yet one of the supported registries. You can find out more about sharing policies and other features of conftest on the official website. Polaris can be either installed inside a cluster or as a command-line tool to analyse Kubernetes manifests statically.

When running as a command-line tool, it includes several built-in checks covering areas such as security and best practices — similar to kube-score. Also, you can use it to write custom checks similar to config-lint, copper, and conftest. In other words, polaris combines the best of the two categories: built-in and custom checkers. You can install the polaris command-line tool as per the instructions on the project website.

Once installed, you can run polaris against the base-valid. The above command will print a JSON formatted string detailing the checks that were run and the result of each test. The complete output is available here. Similar to kube-score, polaris identifies several cases where the manifest falls short of recommended best practices which include:.

Each check is either classified with a severity level of warning or danger. To learn more about the current in-built checks, refer to the documentation.

If you are not interested in the detailed results, passing the flag --format score prints a number in the range which polaris refers to as the score:. The closer the score is to , the higher the degree of conformance. If you inspect the exit code of the polaris audit command, you will see that it was 0.

But there are probably ways around that. I find Cerberus to be very reliable with great documentation and straightforward to use. Using the PyYaml to load a yaml document:. Try Rx , it has a Python implementation. From the Rx site: "When adding an API to your web service, you have to choose how to encode the data you send across the line. XML is one common choice for this, but it can grow arcane and cumbersome pretty quickly. Lots of webservice authors want to avoid thinking about XML, and instead choose formats that provide a few simple data types that correspond to common data structures in modern programming languages.

Unfortunately, while these formats make it easy to pass around complex data structures, they lack a system for validation. Yes - having support for validation is vital for lots of important use cases.

See e. As already mentioned, there is Rx , available for various languages, and Kwalify for Ruby and Java. You can load YAML document as a dict and use library schema to check it:. The YAML file has a tag support where we can enforce this basic checks by prefixing the data type. I did some research to define a schema of YAML. The idea is like we can validate the YAML with its corresponding schema for basic data type check. Also even our custom validations like IP address, random strings can be added in this.

This package best fits my requirements. I tried this with a small example in my local set up, and is working. Heres the sample schema file. These look good. The yaml parser can handle the syntax erorrs, and one of these libraries can validate the data structures. Pydantic has not been mentioned. I wrapped some existing json-related python libraries aiming for being able to use them with yaml as well.

What you don't get out of the box yet, is validating against external schemas that are in yaml format as well. I'm not aware of a python solution. But there is a ruby schema validator for YAML called kwalify. You should be able to access it using subprocess if you don't come across a python library.