magnum/specs/bay-drivers.rst

Container Orchestration Engine drivers

Launchpad blueprint:

https://blueprints.launchpad.net/magnum/+spec/bay-drivers

Container Orchestration Engines (COEs) are different systems for managing containerized applications in a clustered environment, each having their own conventions and ecosystems. Three of the most common, which also happen to be supported in Magnum, are: Docker Swarm, Kubernetes, and Mesos. In order to successfully serve developers, Magnum needs to be able to provision and manage access to the latest COEs through its API in an effective and scalable way.

Problem description

Magnum currently supports the three most popular COEs, but as more emerge and existing ones change, it needs an effective and scalable way of managing them over time.

One of the problems with the current implementation is that COE-specific logic, such as Kubernetes replication controllers and services, is situated in the core Magnum library and made available to users through the main API. Placing COE-specific logic in a core API introduces tight coupling and forces operators to work with an inflexible design.

By formalising a more modular and extensible architecture, Magnum will be in a much better position to help operators and consumers satisfy custom use-cases.

Use cases

1. Extensibility. Contributors and maintainers need a suitable architecture to house current and future COE implementations. Moving to a more extensible architecture, where core classes delegate to drivers, provides a more effective and elegant model for handling COE differences without the need for tightly coupled and monkey-patched logic.

   One of the key use cases is allowing operators to customise their orchestration logic, such as modifying Heat templates or even using their own tooling like Ansible. Moreover, operators will often expect to use a custom distro image with lots of software pre-installed and many special security requirements that is extremely difficult or impossible to do with the current upstream templates. COE drivers solves these problems.

2. Maintainability. Moving to a modular architecture will be easier to manage in the long-run because the responsibility of maintaining non-standard implementations is shifted into the operator's domain. Maintaining the default drivers which are packaged with Magnum will also be easier and cleaner since logic is now demarcated from core codebase directories.

3. COE & Distro choice. In the community there has been a lot of discussion about which distro and COE combination to support with the templates. Having COE drivers allows for people or organizations to maintain distro-specific implementations (e.g CentOS+Kubernetes).

4. Addresses dependency concerns. One of the direct results of introducing a driver model is the ability to give operators more freedom about choosing how Magnum integrates with the rest of their OpenStack platform. For example, drivers would remove the necessity for users to adopt Barbican for secret management.

5. Driver versioning. The new driver model allows operators to modify existing drivers or creating custom ones, release new bay types based on the newer version, and subsequently launch news bays running the updated functionality. Existing bays which are based on older driver versions would be unaffected in this process and would still be able to have lifecycle operations performed on them. If one were to list their details from the API, it would reference the old driver version. An operator can see which driver version a bay type is based on through its driver value, which is exposed through the API.

Proposed change

1. The creation of new directory at the project root: ./magnum/drivers. Each driver will house its own logic inside its own directory. Each distro will house its own logic inside that driver directory. For example, the Fedora Atomic distro using Swarm will have the following directory structure:

   drivers/
     swarm_atomic_v1/
         image/
           ...
         templates/
           ...
         api.py
         driver.py
         monitor.py
         scale.py
         template_def.py
         version.py

   The directory name should be a string which uniquely identifies the driver and provides a descriptive reference. The driver version number and name are provided in the manifest file and will be included in the bay metadata at cluster build time.

   There are two workflows for rolling out driver updates:

   • if the change is relatively minor, they modify the files in the existing driver directory and update the version number in the manifest file.
   • if the change is significant, they create a new directory (either from scratch or by forking).

   Further explanation of the three top-level files:

   • an image directory is optional and should contain documentation which tells users how to build the image and register it to glance. This directory can also hold artifacts for building the image, for instance diskimagebuilder elements, scripts, etc.

   • a templates directory is required and will (for the forseeable future) store Heat template YAML files. In the future drivers will allow operators to use their own orchestration tools like Ansible.

   • api.py is optional, and should contain the API controller which handles custom API operations like Kubernetes RCs or Pods. It will be this class which accepts HTTP requests and delegates to the Conductor. It should contain a uniquely named class, such as SwarmAtomicXYZ, which extends from the core controller class. The COE class would have the opportunity of overriding base methods if necessary.

   • driver.py is required, and should contain the logic which maps controller actions to COE interfaces. These include: bay_create, bay_update, bay_delete, bay_rebuild, bay_soft_reboot and bay_hard_reboot.

   • version.py is required, and should contain the version number of the bay driver. This is defined by a version attribute and is represented in the 1.0.0 format. It should also include a Driver attribute and should be a descriptive name such as swarm_atomic.

     Due to the varying nature of COEs, it is up to the bay maintainer to implement this in their own way. Since a bay is a combination of a COE and an image, driver.py will also contain information about the os_distro property which is expected to be attributed to Glance image.

   • monitor.py is optional, and should contain the logic which monitors the resource utilization of bays.

   • template_def.py is required and should contain the COE's implementation of how orchestration templates are loaded and matched to Magnum objects. It would probably contain multiple classes, such as class SwarmAtomicXYZTemplateDef(BaseTemplateDefinition).

   • scale.py is optional per bay specification and should contain the logic for scaling operations.

2. Renaming the coe attribute of BayModel to driver. Because this value would determine which driver classes and orchestration templates to load, it would need to correspond to the name of the driver as it is registered with stevedore and setuptools entry points.

   During the lifecycle of an API operation, top-level Magnum classes (such as a Bay conductor) would then delegate to the driver classes which have been dynamically loaded. Validation will need to ensure that whichever value is provided by the user is correct.

   By default, drivers are located under the main project directory and their namespaces are accessible via magnum.drivers.foo. But a use case that needs to be looked at and, if possible, provided for is drivers which are situated outside the project directory, for example in /usr/share/magnum. This will suit operators who want greater separation between customised code and Python libraries.

3. The driver implementations for the 3 current COE and Image combinations: Docker Swarm Fedora, Kubernetes Fedora, Kubernetes CoreOS, and Mesos Ubuntu. Any templates would need to be moved from magnum/templates/{coe_name} to magnum/drivers/{driver_name}/templates.

4. Removal of the following files:

   magnum/magnum/conductor/handlers/
     docker_conductor.py
     k8s_conducter.py

Design Principles

• Minimal, clean API without a high cognitive burden
• Ensure Magnum's priority is to do one thing well, but allow extensibility by external contributors
• Do not force ineffective abstractions that introduce feature divergence
• Formalise a modular and loosely coupled driver architecture that removes COE logic from the core codebase

Alternatives

This alternative relates to #5 of Proposed Change. Instead of having a drivers registered using stevedore and setuptools entry points, an alternative is to use the Magnum config instead.

Data model impact

Since drivers would be implemented for the existing COEs, there would be no loss of functionality for end-users.

REST API impact

Attribute change when creating and updating a BayModel (coe to driver). This would occur before v1 of the API is frozen.

COE-specific endpoints would be removed from the core API.

Security impact

None

Notifications impact

None

Other end user impact

There will be deployer impacts because deployers will need to select which drivers they want to activate.

Performance Impact

None

Other deployer impact

In order to utilize new functionality and bay drivers, operators will need to update their installation and configure bay models to use a driver.

Developer impact

Due to the significant impact on the current codebase, a phased implementation approach will be necessary. This is defined in the Work Items section.

Code will be contributed for COE-specific functionality in a new way, and will need to abide by the new architecture. Documentation and a good first implementation will play an important role in helping developers contribute new functionality.

Implementation

Assignee(s)

Primary assignee: murali-allada

Other contributors: jamiehannaford strigazi

Work Items

1. New drivers directory
2. Change coe attribute to driver
3. COE drivers implementation (swarm-fedora, k8s-fedora, k8s-coreos, mesos-ubuntu). Templates should remain in directory tree until their accompanying driver has been implemented.
4. Delete old conductor files
5. Update client
6. Add documentation
7. Improve user experience for operators of forking/creating new drivers. One way we could do this is by creating new client commands or scripts. This is orthogonal to this spec, and will be considered after its core implementation.

Dependencies

None

Testing

Each commit will be accompanied with unit tests, and Tempest functional tests.

Documentation Impact

A set of documentation for this architecture will be required. We should also provide a developer guide for creating a new bay driver and updating existing ones.

References

Using Stevedore in your Application.