Scope of the Nova project¶
Nova is focusing on doing an awesome job of its core mission. This document aims to clarify that core mission.
This is a living document to help record where we agree about what Nova should and should not be doing, and why. Please treat this as a discussion of interesting, and hopefully useful, examples. It is not intended to be an exhaustive policy statement.
Our mission statement starts with:
To implement services and associated libraries to provide massively scalable, on demand, self service access to compute resources.
Our official mission statement also includes the following examples of compute resources: bare metal, virtual machines, and containers. For the full official mission statement see: https://governance.openstack.org/tc/reference/projects/nova.html#mission
This document aims to help clarify what the mission statement means.
Nova is all about access to compute resources. This section looks at the types of compute resource Nova works with.
Nova was originally focused purely on providing access to virtual servers running on a variety of different hypervisors. The majority of users use Nova only to provide access to virtual servers from a single hypervisor, however, its possible to have a Nova deployment include multiple different types of hypervisors, while at the same time offering containers and bare metal servers.
The Nova API is not a good fit for a lot of container use cases. The Magnum project intends to deliver a good container experience built on top of Nova.
Nova allows you to use containers in a similar way to how you would use on demand virtual machines. We want to maintain this distinction, so we maintain the integrity and usefulness of the existing Nova API.
For example, Nova is not designed to spin up new containers for every apache request, nor do we plan to control what goes on inside containers. They get the same metadata provided to them as virtual machines, to do with as they see fit.
Bare Metal Servers¶
Ironic project has been pioneering the idea of treating physical machines in a similar way to on demand virtual machines.
Nova’s driver is able to allow a multi-tenant cloud style use of Ironic controlled resources.
While currently there are operations that are a fundamental part of our virtual machine abstraction that are not currently available in ironic, such as attaching iSCSI volumes, it does not fundamentally change the semantics of our API, and as such is a suitable Nova driver. Moreover, it is expected that gap with shrink over time.
Our goal for the Nova API is to provide a consistent abstraction to access on demand compute resources. We are not aiming to expose all features of all hypervisors. Where the details of the underlying hypervisor leak through our APIs, we have failed in this goal, and we must work towards better abstractions that are more interoperable. This is one reason why we put so much emphasis on the use of Tempest in third party CI systems.
The key tenet of driver parity is that if a feature is supported in a driver, it must feel the same to users, as if they where using any of the other drivers that also support that feature. The exception is that, if possible for widely different performance characteristics, but the effect of that API call must be identical.
Following on from that, should a feature only be added to one of the drivers, we must make every effort to ensure another driver could be implemented to match that behavior.
It is important that drivers support enough features, so the API actually provides a consistent abstraction. For example, being unable to create a server or delete a server would severely undermine that goal. In fact, Nova only ever manages resources it creates.
Nova is widely used in production. As such we need to respect the needs of our existing users. At the same time we need evolve the current code base, including both adding and removing features.
This section outlines how we expect people to upgrade, and what we do to help existing users that upgrade in the way we expect.
Our upgrade plan is to concentrate on upgrades from N-1 to the Nth release. So for someone running juno, they would have to upgrade to kilo before upgrading to liberty. This is designed to balance the need for a smooth upgrade, against having to keep maintaining the compatibility code to make that upgrade possible. We talk about this approach as users consuming the stable branch.
In addition, we also support users upgrading from the master branch, technically, between any two commits within the same release cycle. In certain cases, when crossing release boundaries, you must upgrade to the stable branch, before upgrading to the tip of master. This is to support those that are doing some level of “Continuous Deployment” from the tip of master into production. Many of the public cloud provides running OpenStack use this approach so they are able to get access to bug fixes and features they work on into production sooner.
This becomes important when you consider reverting a commit that turns out to have been bad idea. We have to assume any public API change may have already been deployed into production, and as such cannot be reverted. In a similar way, a database migration may have been deployed.
Any commit that will affect an upgrade gets the UpgradeImpact tag added to the commit message, so there is no requirement to wait for release notes.
Don’t break existing users¶
As a community we are aiming towards a smooth upgrade process, where users must be unaware you have just upgraded your deployment, except that there might be additional feature available and improved stability and performance of some existing features.
We don’t ever want to remove features our users rely on. Sometimes we need to migrate users to a new implementation of that feature, which may require extra steps by the deployer, but the end users must be unaffected by such changes. However there are times when some features become a problem to maintain, and fall into disrepair. We aim to be honest with our users and highlight the issues we have, so we are in a position to find help to fix that situation. Ideally we are able to rework the feature so it can be maintained, but in some rare cases, the feature no longer works, is not tested, and no one is stepping forward to maintain that feature, the best option can be to remove that feature.
When we remove features, we need to warn users by first marking those features as deprecated, before we finally remove the feature. The idea is to get feedback on how important the feature is to our user base. Where a feature is important we work with the whole community to find a path forward for those users.
Nova aims to provide a highly interoperable and stable REST API for our users to get self-service access to compute resources.
No more API Proxies¶
Nova API current has some APIs that are now (in kilo) mostly just a proxy to other OpenStack services. If it were possible to remove a public API, these are some we might start with. As such, we don’t want to add any more.
The first example is the API that is a proxy to the Glance v1 API. As Glance moves to deprecate its v1 API, we need to translate calls from the old v1 API we expose, to Glance’s v2 API.
The next API to mention is the networking APIs, in particular the
security groups API. Most of these APIs exist from when
existed and the proxies were added during the transition. However, security
groups has a much richer Neutron API, and if you use both Nova API and Neutron
API, the mismatch can lead to some very unexpected results, in certain cases.
Our intention is to avoid adding to the problems we already have in this area.
No more Orchestration¶
Nova is a low level infrastructure API. It is plumbing upon which richer ideas can be built. Heat and Magnum being great examples of that.
While we have some APIs that could be considered orchestration, and we must continue to maintain those, we do not intend to add any more APIs that do orchestration.
Third Party APIs¶
Nova aims to focus on making a great API that is highly interoperable across all Nova deployments.
We have historically done a very poor job of implementing and maintaining compatibility with third party APIs inside the Nova tree.
As such, all new efforts should instead focus on external projects that provide third party compatibility on top of the Nova API. Where needed, we will work with those projects to extend the Nova API such that its possible to add that functionality on top of the Nova API. However, we do not intend to add API calls for those services to persist third party API specific information in the Nova database. Instead we want to focus on additions that enhance the existing Nova API.
Our mission includes the text “massively scalable”. Lets discuss what that means.
Nova has three main axes of scale: Number of API requests, number of compute nodes and number of active instances. In many cases the number of compute nodes and active instances are so closely related, you rarely need to consider those separately. There are other items, such as the number of tenants, and the number of instances per tenant. But, again, these are very rarely the key scale issue. Its possible to have a small cloud with lots of requests for very short lived VMs, or a large cloud with lots of longer lived VMs. These need to scale out different components of the Nova system to reach their required level of scale.
Ideally all Nova components are either scaled out to match the number of API requests and build requests, or scaled out to match the number of running servers. If we create components that have their load increased relative to both of these items, we can run into inefficiencies or resource contention. Although it is possible to make that work in some cases, this should always be considered.
We intend Nova to be usable for both small and massive deployments. Where small involves 1-10 hypervisors and massive deployments are single regions with greater than 10,000 hypervisors. That should be seen as our current goal, not an upper limit.
There are some features that would not scale well for either the small scale or the very large scale. Ideally we would not accept these features, but if there is a strong case to add such features, we must work hard to ensure you can run without that feature at the scale you are required to run.
IaaS not Batch Processing¶
Currently Nova focuses on providing on-demand compute resources in the style of classic Infrastructure-as-a-service clouds. A large pool of compute resources that people can consume in a self-service way.
Nova is not currently optimized for dealing with a larger number of requests for compute resources compared with the amount of compute resources currently available. We generally assume that a level of spare capacity is maintained for future requests. This is needed for users who want to quickly scale out, and extra capacity becomes available again as users scale in. While spare capacity is also not required, we are not optimizing for a system that aims to run at 100% capacity at all times. As such our quota system is more focused on limiting the current level of resource usage, rather than ensuring a fair balance of resources between all incoming requests. This doesn’t exclude adding features to support making a better use of spare capacity, such as “spot instances”.
There have been discussions around how to change Nova to work better for batch job processing. But the current focus is on how to layer such an abstraction on top of the basic primitives Nova currently provides, possibly adding additional APIs where that makes good sense. Should this turn out to be impractical, we may have to revise our approach.
Deployment and Packaging¶
Nova does not plan on creating its own packaging or deployment systems.
Our CI infrastructure is powered by Devstack. This can also be used by developers to test their work on a full deployment of Nova.
We do not develop any deployment or packaging for production deployments. Being widely adopted by many distributions and commercial products, we instead choose to work with all those parties to ensure they are able to effectively package and deploy Nova.