Octavia Style Commandments

This project was ultimately spawned from work done on the Neutron project. As such, we tend to follow Neutron conventions regarding coding style.

Octavia Specific Commandments

  • [O316] Change assertTrue(isinstance(A, B)) by optimal assert like assertIsInstance(A, B).

  • [O318] Change assert(Not)Equal(A, None) or assert(Not)Equal(None, A) by optimal assert like assertIs(Not)None(A).

  • [O319] Validate that debug level logs are not translated.

  • [O321] Validate that jsonutils module is used instead of json

  • [O322] Don’t use author tags

  • [O323] Change assertEqual(True, A) or assertEqual(False, A) to the more specific assertTrue(A) or assertFalse(A)

  • [O324] Method’s default argument shouldn’t be mutable

  • [O338] Change assertEqual(A in B, True), assertEqual(True, A in B), assertEqual(A in B, False) or assertEqual(False, A in B) to the more specific assertIn/NotIn(A, B)

  • [O339] LOG.warn() is not allowed. Use LOG.warning()

  • [O340] Don’t use xrange()

  • [O341] Don’t translate logs.

  • [0342] Exception messages should be translated

  • [O343] Python 3: do not use basestring.

  • [O344] Python 3: do not use dict.iteritems.

  • [O345] Usage of Python eventlet module not allowed

  • [O346] Don’t use backslashes for line continuation.

  • [O347] Taskflow revert methods must have **kwargs.

Creating Unit Tests

For every new feature, unit tests should be created that both test and (implicitly) document the usage of said feature. If submitting a patch for a bug that had no unit test, a new passing unit test should be added. If a submitted bug fix does have a unit test, be sure to add a new one that fails without the patch and passes with the patch.

Everything is python

Although OpenStack apparently allows either python or C++ code, at this time we don’t envision needing anything other than python (and standard, supported open source modules) for anything we intend to do in Octavia.


With as much as is going on inside Octavia, its likely that certain messages and commands will be repeatedly processed. It’s important that this doesn’t break the functionality of the load balancing service. Therefore, as much as possible, algorithms and interfaces should be made as idempotent as possible.

Centralize intelligence, de-centralize workload

This means that tasks which need to be done relatively infrequently but require either additional knowledge about the state of other components in the Octavia system, advanced logic behind decisions, or otherwise a high degree of intelligence should be done by centralized components (ex. controllers) within the Octavia system. Examples of this might include:

  • Generating haproxy configuration files

  • Managing the lifecycle of Octavia amphorae

  • Moving a loadbalancer instance from one Octavia amphora to another.

On the other hand, tasks done extremely often, or which entail a significant load on the system should be pushed as far out to the most horizontally scalable components as possible. Examples of this might include:

  • Serving actual client requests to end-users (ie. running haproxy)

  • Monitoring pool members for failure and sending notifications about this

  • Processing log files

There will often be a balance that needs to be struck between these two design considerations for any given task for which an algorithm needs to be designed. In considering how to strike this balance, always consider the conditions that will be present in a large operator environment.

Also, as a secondary benefit of centralizing intelligence, minor feature additions and bugfixes can often be accomplished in a large operator environment without having to touch every Octavia amphora running in said environment.

All APIs are versioned

This includes “internal” APIs between Octavia components. Experience coding in the Neutron LBaaS project has taught us that in a large project with many heterogeneous parts, throughout the lifecycle of this project, different parts will evolve at different rates. It is important that these components are allowed to do so without hindering or being hindered by parallel development in other components.

It is also likely that in very large deployments, there might be tens- or hundreds-of-thousands of individual instances of a given component deployed (most likely, the Octavia amphorae). It is unreasonable to expect a large operator to update all of these components at once. Therefore it is likely that for a significant amount of time during a roll-out of a new version, both the old and new versions of a given component must be able to be controlled or otherwise interfaced with by the new components.

Both of the above considerations can be allowed for if we use versioning of APIs where components interact with each other.

Octavia must also keep in mind Neutron LBaaS API versions. Octavia must have the ability to support multiple simultaneous Neutron LBaaS API versions in an effort to allow for Neutron LBaaS API deprecation of URIs. The rationale is that Neutron LBaaS API users should have the ability to transition from one version to the next easily.

Scalability and resilience are as important as functionality

Octavia is meant to be an operator scale load balancer. As such, it’s usually not enough just to get something working: It also needs to be scalable. For most components, “scalable” implies horizontally scalable.

In any large operational environment, resilience to failures is a necessity. Practically speaking, this means that all components of the system that make up Octavia should be monitored in one way or another, and that where possible automatic recovery from the most common kinds of failures should become a standard feature. Where automatic recovery is not an option, then some form of notification about the failure should be implemented.

Avoid premature optimization

Understand that being “high performance” is often not the same thing as being “scalable.” First get the thing to work in an intelligent way. Only worry about making it fast if speed becomes an issue.

Don’t repeat yourself

Octavia strives to follow DRY principles. There should be one source of truth, and repetition of code should be avoided.

Security is not an afterthought

The load balancer is often both the most visible public interface to a given user application, but load balancers themselves often have direct access to sensitive components and data within the application environment. Security bugs will happen, but in general we should not approve designs which have known significant security problems, or which could be made more secure by better design.

Octavia should follow industry standards

By “industry standards” we either mean RFCs or well-established best practices. We are generally not interested in defining new standards if a prior open standard already exists. We should also avoid doing things which directly or indirectly contradict established standards.

Use of pre-commit checks

pre-commit is a software tool that allows us to manage pre-commit checks as part of the Git repository’s configuration and to run checks as Git pre-commit hooks (or other types of Git hooks) automatically on developer machines. It helps to catch and fix common issues before they get pushed to the server. After the installation of the tool (e.g. on Fedora via sudo dnf install pre-commit) simply cd to the Git repository and run pre-commit install to let the tool install its Git pre-commit hook. From now on these predefined checks will run on files that you change in new Git commits.