api_changes.md

PLEASE NOTE: This document applies to the HEAD of the source tree

If you are using a released version of Kubernetes, you should refer to the docs that go with that version.

The latest 1.0.x release of this document can be found [here](http://releases.k8s.io/release-1.0/docs/devel/api_changes.md).

Documentation for other releases can be found at releases.k8s.io.

So you want to change the API?

The Kubernetes API has two major components - the internal structures and the versioned APIs. The versioned APIs are intended to be stable, while the internal structures are implemented to best reflect the needs of the Kubernetes code itself.

What this means for API changes is that you have to be somewhat thoughtful in how you approach changes, and that you have to touch a number of pieces to make a complete change. This document aims to guide you through the process, though not all API changes will need all of these steps.

Operational overview

It is important to have a high level understanding of the API system used in Kubernetes in order to navigate the rest of this document.

As mentioned above, the internal representation of an API object is decoupled from any one API version. This provides a lot of freedom to evolve the code, but it requires robust infrastructure to convert between representations. There are multiple steps in processing an API operation - even something as simple as a GET involves a great deal of machinery.

The conversion process is logically a "star" with the internal form at the center. Every versioned API can be converted to the internal form (and vice-versa), but versioned APIs do not convert to other versioned APIs directly. This sounds like a heavy process, but in reality we do not intend to keep more than a small number of versions alive at once. While all of the Kubernetes code operates on the internal structures, they are always converted to a versioned form before being written to storage (disk or etcd) or being sent over a wire. Clients should consume and operate on the versioned APIs exclusively.

To demonstrate the general process, here is a (hypothetical) example:

1. A user POSTs a Pod object to /api/v7beta1/...
2. The JSON is unmarshalled into a v7beta1.Pod structure
3. Default values are applied to the v7beta1.Pod
4. The v7beta1.Pod is converted to an api.Pod structure
5. The api.Pod is validated, and any errors are returned to the user
6. The api.Pod is converted to a v6.Pod (because v6 is the latest stable version)
7. The v6.Pod is marshalled into JSON and written to etcd

Now that we have the Pod object stored, a user can GET that object in any supported api version. For example:

1. A user GETs the Pod from /api/v5/...
2. The JSON is read from etcd and unmarshalled into a v6.Pod structure
3. Default values are applied to the v6.Pod
4. The v6.Pod is converted to an api.Pod structure
5. The api.Pod is converted to a v5.Pod structure
6. The v5.Pod is marshalled into JSON and sent to the user

The implication of this process is that API changes must be done carefully and backward-compatibly.

On compatibility

Before talking about how to make API changes, it is worthwhile to clarify what we mean by API compatibility. An API change is considered backward-compatible if it:

• adds new functionality that is not required for correct behavior
• does not change existing semantics
• does not change existing defaults

Put another way:

1. Any API call (e.g. a structure POSTed to a REST endpoint) that worked before your change must work the same after your change.
2. Any API call that uses your change must not cause problems (e.g. crash or degrade behavior) when issued against servers that do not include your change.
3. It must be possible to round-trip your change (convert to different API versions and back) with no loss of information.

If your change does not meet these criteria, it is not considered strictly compatible. There are times when this might be OK, but mostly we want changes that meet this definition. If you think you need to break compatibility, you should talk to the Kubernetes team first.

Let's consider some examples. In a hypothetical API (assume we're at version v6), the Frobber struct looks something like this:

// API v6.
type Frobber struct {
	Height int    `json:"height"`
	Param  string `json:"param"`
}

You want to add a new Width field. It is generally safe to add new fields without changing the API version, so you can simply change it to:

// Still API v6.
type Frobber struct {
	Height int    `json:"height"`
	Width  int    `json:"width"`
	Param  string `json:"param"`
}

The onus is on you to define a sane default value for Width such that rule #1 above is true - API calls and stored objects that used to work must continue to work.

For your next change you want to allow multiple Param values. You can not simply change Param string to Params []string (without creating a whole new API version) - that fails rules #1 and #2. You can instead do something like:

// Still API v6, but kind of clumsy.
type Frobber struct {
	Height int           `json:"height"`
	Width  int           `json:"width"`
	Param  string        `json:"param"`  // the first param
	ExtraParams []string `json:"params"` // additional params
}

Now you can satisfy the rules: API calls that provide the old style Param will still work, while servers that don't understand ExtraParams can ignore it. This is somewhat unsatisfying as an API, but it is strictly compatible.

Part of the reason for versioning APIs and for using internal structs that are distinct from any one version is to handle growth like this. The internal representation can be implemented as:

// Internal, soon to be v7beta1.
type Frobber struct {
	Height int
	Width  int
	Params []string
}

The code that converts to/from versioned APIs can decode this into the somewhat uglier (but compatible!) structures. Eventually, a new API version, let's call it v7beta1, will be forked and it can use the clean internal structure.

We've seen how to satisfy rules #1 and #2. Rule #3 means that you can not extend one versioned API without also extending the others. For example, an API call might POST an object in API v7beta1 format, which uses the cleaner Params field, but the API server might store that object in trusty old v6 form (since v7beta1 is "beta"). When the user reads the object back in the v7beta1 API it would be unacceptable to have lost all but Params[0]. This means that, even though it is ugly, a compatible change must be made to the v6 API.

As another interesting example, enumerated values provide a unique challenge. Adding a new value to an enumerated set is not a compatible change. Clients which assume they know how to handle all possible values of a given field will not be able to handle the new values. However, removing value from an enumerated set can be a compatible change, if handled properly (treat the removed value as deprecated but allowed).

Changing versioned APIs

For most changes, you will probably find it easiest to change the versioned APIs first. This forces you to think about how to make your change in a compatible way. Rather than doing each step in every version, it's usually easier to do each versioned API one at a time, or to do all of one version before starting "all the rest".

Edit types.go

The struct definitions for each API are in pkg/api/<version>/types.go. Edit those files to reflect the change you want to make. Note that all non-online fields in versioned APIs must have description tags - these are used to generate documentation.

Edit defaults.go

If your change includes new fields for which you will need default values, you need to add cases to pkg/api/<version>/defaults.go. Of course, since you have added code, you have to add a test: pkg/api/<version>/defaults_test.go.

Do use pointers to scalars when you need to distinguish between an unset value and an automatic zero value. For example, PodSpec.TerminationGracePeriodSeconds is defined as *int64 the go type definition. A zero value means 0 seconds, and a nil value asks the system to pick a default.

Don't forget to run the tests!

Edit conversion.go

Given that you have not yet changed the internal structs, this might feel premature, and that's because it is. You don't yet have anything to convert to or from. We will revisit this in the "internal" section. If you're doing this all in a different order (i.e. you started with the internal structs), then you should jump to that topic below. In the very rare case that you are making an incompatible change you might or might not want to do this now, but you will have to do more later. The files you want are pkg/api/<version>/conversion.go and pkg/api/<version>/conversion_test.go.

Changing the internal structures

Now it is time to change the internal structs so your versioned changes can be used.

Edit types.go

Similar to the versioned APIs, the definitions for the internal structs are in pkg/api/types.go. Edit those files to reflect the change you want to make. Keep in mind that the internal structs must be able to express all of the versioned APIs.

Edit validation.go

Most changes made to the internal structs need some form of input validation. Validation is currently done on internal objects in pkg/api/validation/validation.go. This validation is the one of the first opportunities we have to make a great user experience - good error messages and thorough validation help ensure that users are giving you what you expect and, when they don't, that they know why and how to fix it. Think hard about the contents of string fields, the bounds of int fields and the requiredness/optionalness of fields.

Of course, code needs tests - pkg/api/validation/validation_test.go.

Edit version conversions

At this point you have both the versioned API changes and the internal structure changes done. If there are any notable differences - field names, types, structural change in particular - you must add some logic to convert versioned APIs to and from the internal representation. If you see errors from the serialization_test, it may indicate the need for explicit conversions.

Performance of conversions very heavily influence performance of apiserver. Thus, we are auto-generating conversion functions that are much more efficient than the generic ones (which are based on reflections and thus are highly inefficient).

The conversion code resides with each versioned API. There are two files:

• pkg/api/<version>/conversion.go containing manually written conversion functions
• pkg/api/<version>/conversion_generated.go containing auto-generated conversion functions

Since auto-generated conversion functions are using manually written ones, those manually written should be named with a defined convention, i.e. a function converting type X in pkg a to type Y in pkg b, should be named: convert_a_X_To_b_Y.

Also note that you can (and for efficiency reasons should) use auto-generated conversion functions when writing your conversion functions.

Once all the necessary manually written conversions are added, you need to regenerate auto-generated ones. To regenerate them:

• run

   $ hack/update-generated-conversions.sh

If running the above script is impossible due to compile errors, the easiest workaround is to comment out the code causing errors and let the script to regenerate it. If the auto-generated conversion methods are not used by the manually-written ones, it's fine to just remove the whole file and let the generator to create it from scratch.

Unsurprisingly, adding manually written conversion also requires you to add tests to pkg/api/<version>/conversion_test.go.

Update the fuzzer

Part of our testing regimen for APIs is to "fuzz" (fill with random values) API objects and then convert them to and from the different API versions. This is a great way of exposing places where you lost information or made bad assumptions. If you have added any fields which need very careful formatting (the test does not run validation) or if you have made assumptions such as "this slice will always have at least 1 element", you may get an error or even a panic from the serialization_test. If so, look at the diff it produces (or the backtrace in case of a panic) and figure out what you forgot. Encode that into the fuzzer's custom fuzz functions. Hint: if you added defaults for a field, that field will need to have a custom fuzz function that ensures that the field is fuzzed to a non-empty value.

The fuzzer can be found in pkg/api/testing/fuzzer.go.

Update the semantic comparisons

VERY VERY rarely is this needed, but when it hits, it hurts. In some rare cases we end up with objects (e.g. resource quantities) that have morally equivalent values with different bitwise representations (e.g. value 10 with a base-2 formatter is the same as value 0 with a base-10 formatter). The only way Go knows how to do deep-equality is through field-by-field bitwise comparisons. This is a problem for us.

The first thing you should do is try not to do that. If you really can't avoid this, I'd like to introduce you to our semantic DeepEqual routine. It supports custom overrides for specific types - you can find that in pkg/api/helpers.go.

There's one other time when you might have to touch this: unexported fields. You see, while Go's reflect package is allowed to touch unexported fields, us mere mortals are not - this includes semantic DeepEqual. Fortunately, most of our API objects are "dumb structs" all the way down - all fields are exported (start with a capital letter) and there are no unexported fields. But sometimes you want to include an object in our API that does have unexported fields somewhere in it (for example, time.Time has unexported fields). If this hits you, you may have to touch the semantic DeepEqual customization functions.

Implement your change

Now you have the API all changed - go implement whatever it is that you're doing!

Write end-to-end tests

This is, sadly, still sort of painful. Talk to us and we'll try to help you figure out the best way to make sure your cool feature keeps working forever.

Examples and docs

At last, your change is done, all unit tests pass, e2e passes, you're done, right? Actually, no. You just changed the API. If you are touching an existing facet of the API, you have to try really hard to make sure that all the examples and docs are updated. There's no easy way to do this, due in part to JSON and YAML silently dropping unknown fields. You're clever - you'll figure it out. Put grep or ack to good use.

If you added functionality, you should consider documenting it and/or writing an example to illustrate your change.

Make sure you update the swagger API spec by running:

$ hack/update-swagger-spec.sh

The API spec changes should be in a commit separate from your other changes.

Incompatible API changes

If your change is going to be backward incompatible or might be a breaking change for API consumers, please send an announcement to [email protected] before the change gets in. If you are unsure, ask. Also make sure that the change gets documented in CHANGELOG.md for the next release.

Adding new REST objects

TODO(smarterclayton): write this.