Placement API Developer Notes

Placement API Developer Notes


The Nova project introduced the placement service as part of the Newton release, and it was extracted to its own repository in the Stein release. The service provides an HTTP API to manage inventories of different classes of resources, such as disk or virtual cpus, made available by entities called resource providers. Information provided through the placement API is intended to enable more effective accounting of resources in an OpenStack deployment and better scheduling of various entities in the cloud.

The document serves to explain the architecture of the system and to provide some guidance on how to maintain and extend the code. For more detail on why the system was created and how it does its job see Placement API. For some insight into the longer term goals of the system see Goals.

Big Picture

The placement service is straightforward: It is a WSGI application that sends and receives JSON, using an RDBMS (usually MySQL) for persistence. As state is managed solely in the DB, scaling the placement service is done by increasing the number of WSGI application instances and scaling the RDBMS using traditional database scaling techniques.

For sake of consistency and because there was initially intent to make the entities in the placement service available over RPC, versioned objects are used to provide the interface between the HTTP application layer and the SQLAlchemy-driven persistence layer. Even without RPC, these objects provide useful structuring and separation of the code.

Though the placement service does not aspire to be a microservice it does aspire to continue to be small and minimally complex. This means a relatively small amount of middleware that is not configurable, and a limited number of exposed resources where any given resource is represented by one (and only one) URL that expresses a noun that is a member of the system. Adding additional resources should be considered a significant change requiring robust review from many stakeholders.

The set of HTTP resources represents a concise and constrained grammar for expressing the management of resource providers, inventories, resource classes, traits, and allocations. If a solution is initially designed to need more resources or a more complex grammar that may be a sign that we need to give our goals greater scrutiny. Is there a way to do what we want with what we have already? Can some other service help? Is a new collaborating service required?

Minimal Framework

The API is set up to use a minimal framework that tries to keep the structure of the application as discoverable as possible and keeps the HTTP interaction near the surface. The goal of this is to make things easy to trace when debugging or adding functionality.

Functionality which is required for every request is handled in raw WSGI middleware that is composed in the placement.deploy module. Dispatch or routing is handled declaratively via the ROUTE_DECLARATIONS map defined in the placement.handler module.

Mapping is by URL plus request method. The destination is a complete WSGI application, using a subclass of the wsgify method from WebOb to provide a Request object that provides convenience methods for accessing request headers, bodies, and query parameters and for generating responses. In the placement API these mini-applications are called handlers. The wsgify subclass is provided in placement.wsgi_wrapper as PlacementWsgify. It is used to make sure that JSON formatted error responses are structured according to the API-SIG errors guideline.

This division between middleware, dispatch and handlers is supposed to provide clues on where a particular behavior or functionality should be implemented. Like most such systems, this does not always work but is a useful tool.


This section tries to shed some light on some of the differences between the placement API and some of the other OpenStack APIs or on situations which may be surprising or unexpected.

  • The placement API is somewhat more strict about Content-Type and Accept headers in an effort to follow the HTTP RFCs.

    If a user-agent sends some JSON in a PUT or POST request without a Content-Type of application/json the request will result in an error.

    If a GET request is made without an Accept header, the response will default to being application/json.

    If a request is made with an explicit Accept header that does not include application/json then there will be an error and the error will attempt to be in the requested format (for example, text/plain).

  • If a URL exists, but a request is made using a method that that URL does not support, the API will respond with a 405 error. Sometimes in the nova APIs this can be a 404 (which is wrong, but understandable given the constraints of the code).

  • Because each handler is individually wrapped by the PlacementWsgify decorator any exception that is a subclass of webob.exc.WSGIHTTPException that is raised from within the handler, such as webob.exc.HTTPBadRequest, will be caught by WebOb and turned into a valid Response containing headers and body set by WebOb based on the information given when the exception was raised. It will not be seen as an exception by any of the middleware in the placement stack.

    In general this is a good thing, but it can lead to some confusion if, for example, you are trying to add some middleware that operates on exceptions.

    Other exceptions that are not from WebOb will raise outside the handlers where they will either be caught in the __call__ method of the PlacementHandler app that is responsible for dispatch, or by the FaultWrap middleware.


The placement API makes use of microversions to allow the release of new features on an opt in basis. See Placement API for an up to date history of the available microversions.

The rules around when a microversion is needed are modeled after those of the compute API. When adding a new microversion there are a few bits of required housekeeping that must be done in the code:

  • Update the VERSIONS list in placement/ to indicate the new microversion and give a very brief summary of the added feature.
  • Update placement/rest_api_version_history.rst to add a more detailed section describing the new microversion.
  • Add a release note with a features section announcing the new or changed feature and the microversion.
  • If the version_handler decorator (see below) has been used, increment TOTAL_VERSIONED_METHODS in placement/tests/unit/ This provides a confirmatory check just to make sure you are paying attention and as a helpful reminder to do the other things in this list.
  • Include functional gabbi tests as appropriate (see Using Gabbi). At the least, update the latest microversion test in placement/tests/functional/gabbits/microversion.yaml.
  • Update the API Reference documentation as appropriate. The source is located under api-ref/source/.

In the placement API, microversions only use the modern form of the version header:

OpenStack-API-Version: placement 1.2

If a valid microversion is present in a request it will be placed, as a Version object, into the WSGI environment with the placement.microversion key. Often, accessing this in handler code directly (to control branching) is the most explicit and granular way to have different behavior per microversion. A Version instance can be treated as a tuple of two ints and compared as such or there is a matches method.

A version_handler decorator is also available. It makes it possible to have multiple different handler methods of the same (fully-qualified by package) name, each available for a different microversion window. If a request wants a microversion that is not available, a defined status code is returned (usually 404 or 405). There is a unit test in place which will fail if there are version intersections.

Adding a New Handler

Adding a new URL or a new method (e.g, PATCH) to an existing URL requires adding a new handler function. In either case a new microversion and release note is required. When adding an entirely new route a request for a lower microversion should return a 404. When adding a new method to an existing URL a request for a lower microversion should return a 405.

In either case, the ROUTE_DECLARATIONS dictionary in the placement.handler module should be updated to point to a function within a module that contains handlers for the type of entity identified by the URL. Collection and individual entity handlers of the same type should be in the same module.

As mentioned above, the handler function should be decorated with @wsgi_wrapper.PlacementWsgify, take a single argument req which is a WebOb Request object, and return a WebOb Response.

For PUT and POST methods, request bodies are expected to be JSON based on a content-type of application/json. This may be enforced by using a decorator: @util.require_content('application/json'). If the body is not JSON, a 415 response status is returned.

Response bodies are usually JSON. A handler can check the Accept header provided in a request using another decorator: @util.check_accept('application/json'). If the header does not allow JSON, a 406 response status is returned.

If a hander returns a response body, a Last-Modified header should be included with the response. If the entity or entities in the response body are directly associated with an object (or objects, in the case of a collection response) that has an updated_at (or created_at) field, that field’s value can be used as the value of the header (WebOb will take care of turning the datetime object into a string timestamp). A util.pick_last_modified is available to help choose the most recent last-modified when traversing a collection of entities.

If there is no directly associated object (for example, the output is the composite of several objects) then the Last-Modified time should be timeutils.utcnow(with_timezone=True) (the timezone must be set in order to be a valid HTTP timestamp). For example, the response to GET /allocation_candidates should have a last-modified header of now because it is composed from queries against many different database entities, presents a mixture of result types (allocation requests and provider summaries), and has a view of the system that is only meaningful now.

If a Last-Modified header is set, then a Cache-Control header with a value of no-cache must be set as well. This is to avoid user-agents inadvertently caching the responses.

JSON sent in a request should be validated against a JSON Schema. A util.extract_json method is available. This takes a request body and a schema. If multiple schema are used for different microversions of the same request, the caller is responsible for selecting the right one before calling extract_json.

When a handler needs to read or write the data store it should use methods on the objects found in the placement.objects package. Doing so requires a context which is provided to the handler method via the WSGI environment. It can be retrieved as follows:

context = req.environ['placement.context']


If your change requires new methods or new objects in the placement.objects package, after you have made sure that you really do need those new methods or objects (you may not!) make those changes in a patch that is separate from and prior to the HTTP API change.

If a handler needs to return an error response, with the advent of Placement API Error Handling, it is possible to include a code in the JSON error response. This can be used to distinguish different errors with the same HTTP response status code (a common case is a generation conflict versus an inventory in use conflict). Error codes are simple namespaced strings (e.g., placement.inventory.inuse) for which symbols are maintained in placement.errors. Adding a symbol to a response is done by using the comment kwarg to a WebOb exception, like this:

except exception.InventoryInUse as exc:
    raise webob.exc.HTTPConflict(
        _('update conflict: %(error)s') % {'error': exc},

Code that adds newly raised exceptions should include an error code. Find additional guidelines on use in the docs for placement.errors.

Testing of handler code is described in the next section.


Most of the handler code in the placement API is tested using gabbi. Some utility code is tested with unit tests found in placement/tests/unit. The back-end objects are tested with a combination of unit and functional tests found in placement/tests/unit/objects/ and placement/tests/functional/db.

When writing tests for handler code (that is, the code found in placement/handlers) a good rule of thumb is that if you feel like there needs to be a unit test for some of the code in the handler, that is a good sign that the piece of code should be extracted to a separate method. That method should be independent of the handler method itself (the one decorated by the wsgify method) and testable as a unit, without mocks if possible. If the extracted method is useful for multiple resources consider putting it in the util package.

As a general guide, handler code should be relatively short and where there are conditionals and branching, they should be reachable via the gabbi functional tests. This is merely a design goal, not a strict constraint.

Using Gabbi

Gabbi was developed in the telemetry project to provide a declarative way to test HTTP APIs that preserves visibility of both the request and response of the HTTP interaction. Tests are written in YAML files where each file is an ordered suite of tests. Fixtures (such as a database) are set up and torn down at the beginning and end of each file, not each test. JSON response bodies can be evaluated with JSONPath. The placement WSGI application is run via wsgi-intercept, meaning that real HTTP requests are being made over a file handle that appears to Python to be a socket.

In the placement API the YAML files (aka “gabbits”) can be found in placement/tests/functional/gabbits. Fixture definitions are in placement/tests/functional/fixtures/ Tests are frequently grouped by handler name (e.g., resource-provider.yaml and inventory.yaml). This is not a requirement and as we increase the number of tests it makes sense to have more YAML files with fewer tests, divided up by the arc of API interaction that they test.

The gabbi tests are integrated into the functional tox target, loaded via placement/tests/functional/ If you want to run just the gabbi tests one way to do so is:

tox -efunctional test_api

If you want to run just one yaml file (in this example inventory.yaml):

tox -efunctional api.inventory

It is also possible to run just one test from within one file. When you do this every test prior to the one you asked for will also be run. This is because the YAML represents a sequence of dependent requests. Select the test by using the name in the yaml file, replacing space with _:

tox -efunctional api.inventory_post_new_ipv4_address_inventory


tox.ini in the placement repository is configured by a group_regex so that each gabbi YAML is considered a group. Thus, all tests in the file will be run in the same process when running stestr concurrently (the default).

Writing More Gabbi Tests

The docs for gabbi try to be complete and explain the syntax in some depth. Where something is missing or confusing, please log a bug.

While it is possible to test all aspects of a response (all the response headers, the status code, every attribute in a JSON structure) in one single test, doing so will likely make the test harder to read and will certainly make debugging more challenging. If there are multiple things that need to be asserted, making multiple requests is reasonable. Since database set up is only happening once per file (instead of once per test) and since there is no TCP overhead, the tests run quickly.

While fixtures can be used to establish entities that are required for tests, creating those entities via the HTTP API results in tests which are more descriptive. For example the inventory.yaml file creates the resource provider to which it will then add inventory. This makes it easy to explore a sequence of interactions and a variety of responses with the tests:

  • create a resource provider
  • confirm it has empty inventory
  • add inventory to the resource provider (in a few different ways)
  • confirm the resource provider now has inventory
  • modify the inventory
  • delete the inventory
  • confirm the resource provider now has empty inventory

Nothing special is required to add a new set of tests: create a YAML file with a unique name in the same directory as the others. The other files can provide examples. Gabbi can provide a useful way of doing test driven development of a new handler: create a YAML file that describes the desired URLs and behavior and write the code to make it pass.

It’s also possible to use gabbi against a running placement service, for example in devstack. See gabbi-run to get started. If you don’t want to go to the trouble of using devstack, but do want a live server see Quick Placement Development.

Database Schema Changes

At some point in every application’s life it becomes necessary to change the structure of its database. Modifying the SQLAlchemy models (in placement/db/sqlachemy/ is necessary for the application to understand the new structure, but that will not change the actual underlying database. To do that, Placement uses alembic to run database migrations.

Alembic calls each change a revision. To create a migration with alembic, run the alembic revision command. Alembic will then generate a new revision file with a unique file name, and place it in the alembic/versions/ directory:

ed@devenv:~/projects/placement$ alembic -c placement/db/sqlalchemy/alembic.ini revision -m "Add column foo to bar table"
Generating /home/ed/projects/placement/placement/db/sqlalchemy/alembic/versions/ ... done

Let us break down that command:

  • The -c parameter tells alembic where to find its configuration file.
  • revision is the alembic subcommand for creating a new revision file.
  • The -m parameter specifies a brief comment explaining the change.
  • The generated file from alembic will have a name consisting of a random hash prefix, followed by an underscore, followed by your -m comment, and a .py extension. So be sure to keep your comment as brief as possible while still being descriptive.

The generated file will look something like this:

"""Add column foo to bar table

Revision ID: dfb006498ad2
Revises: 0378df171af3
Create Date: 2018-10-29 20:02:58.290779

from alembic import op
import sqlalchemy as sa

# revision identifiers, used by Alembic.
revision = 'dfb006498ad2'
down_revision = '0378df171af3'
branch_labels = None
depends_on = None

def upgrade():

The top of the file is the docstring that will show when you review your revision history. If we did not include the -m comment when we ran the alembic revision command, this would just contain “empty message”. If you did not specify the comment when creating the file, be sure to replace “empty message” with a brief comment describing the reason for the database change.

You then need to define the changes in the upgrade() method. The code used in these methods is basic SQLAlchemy code for creating and modifying tables. You can examine existing migrations in the project to see examples of what this code looks like, as well as find more in-depth usage of Alembic in the Alembic tutorial.

One other option when creating the revision is to add the --autogenerate parameter to the revision command. This assumes that you have already updated the SQLAlchemy models, and have a connection to the placement database configured. When run with this option, the upgrade() method of the revision file is filled in for you by alembic as it compares the schema described in your script and the actual state of the database. You should always verify the revision script to make sure it does just what you intended, both by reading the code as well as running the tests, as there are some things that autogenerate cannot deduce. See autogenerate limitations for more detailed information.

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