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enhancement_template.md
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---
title: neat-enhancement-idea
authors:
- TBD
reviewers: # Include a comment about what domain expertise a reviewer is expected to bring and what area of the enhancement you expect them to focus on. For example: - "@networkguru, for networking aspects, please look at IP bootstrapping aspect"
- TBD
approvers: # A single approver is preferred, the role of the approver is to raise important questions, help ensure the enhancement receives reviews from all applicable areas/SMEs, and determine when consensus is achieved such that the EP can move forward to implementation. Having multiple approvers makes it difficult to determine who is responsible for the actual approval.
- TBD
api-approvers: # In case of new or modified APIs or API extensions (CRDs, aggregated apiservers, webhooks, finalizers). If there is no API change, use "None"
- TBD
creation-date: yyyy-mm-dd
last-updated: yyyy-mm-dd
tracking-link: # link to the tracking ticket (for example: Jira Feature or Epic ticket) that corresponds to this enhancement
- TBD
see-also:
- "/enhancements/this-other-neat-thing.md"
replaces:
- "/enhancements/that-less-than-great-idea.md"
superseded-by:
- "/enhancements/our-past-effort.md"
---
To get started with this template:
1. **Pick a domain.** Find the appropriate domain to discuss your enhancement.
1. **Make a copy of this template.** Copy this template into the directory for
the domain.
1. **Fill out the metadata at the top.** The embedded YAML document is
checked by the linter.
1. **Fill out the "overview" sections.** This includes the Summary and
Motivation sections. These should be easy and explain why the community
should desire this enhancement.
1. **Create a PR.** Assign it to folks with expertise in that domain to help
sponsor the process.
1. **Merge after reaching consensus.** Merge when there is consensus
that the design is complete and all reviewer questions have been
answered so that work can begin. Come back and update the document
if important details (API field names, workflow, etc.) change
during code review.
1. **Keep all required headers.** If a section does not apply to an
enhancement, explain why but do not remove the section. This part
of the process is enforced by the linter CI job.
See ../README.md for background behind these instructions.
Start by filling out the header with the metadata for this enhancement.
# Neat Enhancement Idea
This is the title of the enhancement. Keep it simple and descriptive. A good
title can help communicate what the enhancement is and should be considered as
part of any review.
The YAML `title` should be lowercased and spaces/punctuation should be
replaced with `-`.
The `Metadata` section above is intended to support the creation of tooling
around the enhancement process.
## Summary
The `Summary` section is important for producing high quality
user-focused documentation such as release notes or a development roadmap. It
should be possible to collect this information before implementation begins in
order to avoid requiring implementors to split their attention between writing
release notes and implementing the feature itself.
Your summary should be one paragraph long. More detail
should go into the following sections.
## Motivation
This section is for explicitly listing the motivation, goals and non-goals of
this proposal. Describe why the change is important and the benefits to users.
### User Stories
Detail the things that people will be able to do if this is implemented and
what goal that allows them to achieve. In each story, explain who the actor
is based on their role, explain what they want to do with the system,
and explain the underlying goal they have, what it is they are going to
achieve with this new feature.
Use the standard three part formula:
> "As a _role_, I want to _take some action_ so that I can _accomplish a
goal_."
Make the change feel real for users, without getting bogged down in
implementation details.
Here are some example user stories to show what they might look like:
* As an OpenShift engineer, I want to write an enhancement, so that I
can get feedback on my design and build consensus about the approach
to take before starting the implementation.
* As an OpenShift engineer, I want to understand the rationale behind
a particular feature's design and alternatives considered, so I can
work on a new enhancement in that problem space knowing the history
of the current design better.
* As a product manager, I want to review this enhancement proposal, so
that I can make sure the customer requirements are met by the
design.
* As an administrator, I want a one-click OpenShift installer, so that
I can easily set up a new cluster without having to follow a long
set of operations.
In each example, the persona's goal is clear, and the goal is clearly provided
by the capability being described.
The engineer wants feedback on their enhancement from their peers, and writing
an enhancement allows for that feedback.
The product manager wants to make sure that their customer requirements are fulfilled,
reviewing the enhancement allows them to check that.
The administrator wants to set up his OpenShift cluster as easily as possible, and
reducing the install to a single click simplifies that process.
Here are some real examples from previous enhancements:
* [As a member of OpenShift concerned with the release process (TRT, dev, staff engineer, maybe even PM),
I want to opt in to pre-release features so that I can run periodic testing in CI and obtain a signal of
feature quality.](https://github.com/openshift/enhancements/blob/master/enhancements/installer/feature-sets.md#user-stories)
* [As a cloud-provider affiliated engineer / platform integrator / RH partner
I want to have a mechanism to signal OpenShift's built-in operators about additional
cloud-provider specific components so that I can inject my own platform-specific controllers into OpenShift
to improve the integration between OpenShift and my cloud provider.](https://github.com/openshift/enhancements/blob/master/enhancements/cloud-integration/infrastructure-external-platform-type.md#user-stories)
* [As an OpenShift cluster administrator, I want to add worker nodes to my
existing single control-plane node cluster, so that it'll be able to meet
growing computation demands.](https://github.com/openshift/enhancements/blob/master/enhancements/single-node/single-node-openshift-with-workers.md#user-stories)
Include a story on how this proposal will be operationalized:
life-cycled, monitored and remediated at scale.
### Goals
Summarize the specific goals of the proposal. How will we know that
this has succeeded? A good goal describes something a user wants from
their perspective, and does not include the implementation details
from the proposal.
### Non-Goals
What is out of scope for this proposal? Listing non-goals helps to
focus discussion and make progress. Highlight anything that is being
deferred to a later phase of implementation that may call for its own
enhancement.
## Proposal
This section should explain what the proposal actually is. Enumerate
*all* of the proposed changes at a *high level*, including all of the
components that need to be modified and how they will be
different. Include the reason for each choice in the design and
implementation that is proposed here.
To keep this section succinct, document the details like API field
changes, new images, and other implementation details in the
**Implementation Details** section and record the reasons for not
choosing alternatives in the **Alternatives** section at the end of
the document.
### Workflow Description
Explain how the user will use the feature. Be detailed and explicit.
Describe all of the actors, their roles, and the APIs or interfaces
involved. Define a starting state and then list the steps that the
user would need to go through to trigger the feature described in the
enhancement. Optionally add a
[mermaid](https://github.com/mermaid-js/mermaid#readme) sequence
diagram.
Use sub-sections to explain variations, such as for error handling,
failure recovery, or alternative outcomes.
For example:
**cluster creator** is a human user responsible for deploying a
cluster.
**application administrator** is a human user responsible for
deploying an application in a cluster.
1. The cluster creator sits down at their keyboard...
2. ...
3. The cluster creator sees that their cluster is ready to receive
applications, and gives the application administrator their
credentials.
See
https://github.com/openshift/enhancements/blob/master/enhancements/workload-partitioning/management-workload-partitioning.md#high-level-end-to-end-workflow
and https://github.com/openshift/enhancements/blob/master/enhancements/agent-installer/automated-workflow-for-agent-based-installer.md for more detailed examples.
### API Extensions
API Extensions are CRDs, admission and conversion webhooks, aggregated API servers,
and finalizers, i.e. those mechanisms that change the OCP API surface and behaviour.
- Name the API extensions this enhancement adds or modifies.
- Does this enhancement modify the behaviour of existing resources, especially those owned
by other parties than the authoring team (including upstream resources), and, if yes, how?
Please add those other parties as reviewers to the enhancement.
Examples:
- Adds a finalizer to namespaces. Namespace cannot be deleted without our controller running.
- Restricts the label format for objects to X.
- Defaults field Y on object kind Z.
Fill in the operational impact of these API Extensions in the "Operational Aspects
of API Extensions" section.
### Topology Considerations
#### Hypershift / Hosted Control Planes
Are there any unique considerations for making this change work with
Hypershift?
See https://github.com/openshift/enhancements/blob/e044f84e9b2bafa600e6c24e35d226463c2308a5/enhancements/multi-arch/heterogeneous-architecture-clusters.md?plain=1#L282
How does it affect any of the components running in the
management cluster? How does it affect any components running split
between the management cluster and guest cluster?
#### Standalone Clusters
Is the change relevant for standalone clusters?
#### Single-node Deployments or MicroShift
How does this proposal affect the resource consumption of a
single-node OpenShift deployment (SNO), CPU and memory?
How does this proposal affect MicroShift? For example, if the proposal
adds configuration options through API resources, should any of those
behaviors also be exposed to MicroShift admins through the
configuration file for MicroShift?
### Implementation Details/Notes/Constraints
What are some important details that didn't come across above in the
**Proposal**? Go in to as much detail as necessary here. This might be
a good place to talk about core concepts and how they relate. While it is useful
to go into the details of the code changes required, it is not necessary to show
how the code will be rewritten in the enhancement.
### Risks and Mitigations
What are the risks of this proposal and how do we mitigate. Think broadly. For
example, consider both security and how this will impact the larger OKD
ecosystem.
How will security be reviewed and by whom?
How will UX be reviewed and by whom?
Consider including folks that also work outside your immediate sub-project.
### Drawbacks
The idea is to find the best form of an argument why this enhancement should
_not_ be implemented.
What trade-offs (technical/efficiency cost, user experience, flexibility,
supportability, etc) must be made in order to implement this? What are the reasons
we might not want to undertake this proposal, and how do we overcome them?
Does this proposal implement a behavior that's new/unique/novel? Is it poorly
aligned with existing user expectations? Will it be a significant maintenance
burden? Is it likely to be superceded by something else in the near future?
## Open Questions [optional]
This is where to call out areas of the design that require closure before deciding
to implement the design. For instance,
> 1. This requires exposing previously private resources which contain sensitive
information. Can we do this?
## Test Plan
**Note:** *Section not required until targeted at a release.*
Consider the following in developing a test plan for this enhancement:
- Will there be e2e and integration tests, in addition to unit tests?
- How will it be tested in isolation vs with other components?
- What additional testing is necessary to support managed OpenShift service-based offerings?
No need to outline all of the test cases, just the general strategy. Anything
that would count as tricky in the implementation and anything particularly
challenging to test should be called out.
All code is expected to have adequate tests (eventually with coverage
expectations).
## Graduation Criteria
**Note:** *Section not required until targeted at a release.*
Define graduation milestones.
These may be defined in terms of API maturity, or as something else. Initial proposal
should keep this high-level with a focus on what signals will be looked at to
determine graduation.
Consider the following in developing the graduation criteria for this
enhancement:
- Maturity levels
- [`alpha`, `beta`, `stable` in upstream Kubernetes][maturity-levels]
- `Dev Preview`, `Tech Preview`, `GA` in OpenShift
- [Deprecation policy][deprecation-policy]
Clearly define what graduation means by either linking to the [API doc definition](https://kubernetes.io/docs/concepts/overview/kubernetes-api/#api-versioning),
or by redefining what graduation means.
In general, we try to use the same stages (alpha, beta, GA), regardless how the functionality is accessed.
[maturity-levels]: https://git.k8s.io/community/contributors/devel/sig-architecture/api_changes.md#alpha-beta-and-stable-versions
[deprecation-policy]: https://kubernetes.io/docs/reference/using-api/deprecation-policy/
**If this is a user facing change requiring new or updated documentation in [openshift-docs](https://github.com/openshift/openshift-docs/),
please be sure to include in the graduation criteria.**
**Examples**: These are generalized examples to consider, in addition
to the aforementioned [maturity levels][maturity-levels].
### Dev Preview -> Tech Preview
- Ability to utilize the enhancement end to end
- End user documentation, relative API stability
- Sufficient test coverage
- Gather feedback from users rather than just developers
- Enumerate service level indicators (SLIs), expose SLIs as metrics
- Write symptoms-based alerts for the component(s)
### Tech Preview -> GA
- More testing (upgrade, downgrade, scale)
- Sufficient time for feedback
- Available by default
- Backhaul SLI telemetry
- Document SLOs for the component
- Conduct load testing
- User facing documentation created in [openshift-docs](https://github.com/openshift/openshift-docs/)
**For non-optional features moving to GA, the graduation criteria must include
end to end tests.**
### Removing a deprecated feature
- Announce deprecation and support policy of the existing feature
- Deprecate the feature
## Upgrade / Downgrade Strategy
If applicable, how will the component be upgraded and downgraded? Make sure this
is in the test plan.
Consider the following in developing an upgrade/downgrade strategy for this
enhancement:
- What changes (in invocations, configurations, API use, etc.) is an existing
cluster required to make on upgrade in order to keep previous behavior?
- What changes (in invocations, configurations, API use, etc.) is an existing
cluster required to make on upgrade in order to make use of the enhancement?
Upgrade expectations:
- Each component should remain available for user requests and
workloads during upgrades. Ensure the components leverage best practices in handling [voluntary
disruption](https://kubernetes.io/docs/concepts/workloads/pods/disruptions/). Any exception to
this should be identified and discussed here.
- Micro version upgrades - users should be able to skip forward versions within a
minor release stream without being required to pass through intermediate
versions - i.e. `x.y.N->x.y.N+2` should work without requiring `x.y.N->x.y.N+1`
as an intermediate step.
- Minor version upgrades - you only need to support `x.N->x.N+1` upgrade
steps. So, for example, it is acceptable to require a user running 4.3 to
upgrade to 4.5 with a `4.3->4.4` step followed by a `4.4->4.5` step.
- While an upgrade is in progress, new component versions should
continue to operate correctly in concert with older component
versions (aka "version skew"). For example, if a node is down, and
an operator is rolling out a daemonset, the old and new daemonset
pods must continue to work correctly even while the cluster remains
in this partially upgraded state for some time.
Downgrade expectations:
- If an `N->N+1` upgrade fails mid-way through, or if the `N+1` cluster is
misbehaving, it should be possible for the user to rollback to `N`. It is
acceptable to require some documented manual steps in order to fully restore
the downgraded cluster to its previous state. Examples of acceptable steps
include:
- Deleting any CVO-managed resources added by the new version. The
CVO does not currently delete resources that no longer exist in
the target version.
## Version Skew Strategy
How will the component handle version skew with other components?
What are the guarantees? Make sure this is in the test plan.
Consider the following in developing a version skew strategy for this
enhancement:
- During an upgrade, we will always have skew among components, how will this impact your work?
- Does this enhancement involve coordinating behavior in the control plane and
in the kubelet? How does an n-2 kubelet without this feature available behave
when this feature is used?
- Will any other components on the node change? For example, changes to CSI, CRI
or CNI may require updating that component before the kubelet.
## Operational Aspects of API Extensions
Describe the impact of API extensions (mentioned in the proposal section, i.e. CRDs,
admission and conversion webhooks, aggregated API servers, finalizers) here in detail,
especially how they impact the OCP system architecture and operational aspects.
- For conversion/admission webhooks and aggregated apiservers: what are the SLIs (Service Level
Indicators) an administrator or support can use to determine the health of the API extensions
Examples (metrics, alerts, operator conditions)
- authentication-operator condition `APIServerDegraded=False`
- authentication-operator condition `APIServerAvailable=True`
- openshift-authentication/oauth-apiserver deployment and pods health
- What impact do these API extensions have on existing SLIs (e.g. scalability, API throughput,
API availability)
Examples:
- Adds 1s to every pod update in the system, slowing down pod scheduling by 5s on average.
- Fails creation of ConfigMap in the system when the webhook is not available.
- Adds a dependency on the SDN service network for all resources, risking API availability in case
of SDN issues.
- Expected use-cases require less than 1000 instances of the CRD, not impacting
general API throughput.
- How is the impact on existing SLIs to be measured and when (e.g. every release by QE, or
automatically in CI) and by whom (e.g. perf team; name the responsible person and let them review
this enhancement)
- Describe the possible failure modes of the API extensions.
- Describe how a failure or behaviour of the extension will impact the overall cluster health
(e.g. which kube-controller-manager functionality will stop working), especially regarding
stability, availability, performance and security.
- Describe which OCP teams are likely to be called upon in case of escalation with one of the failure modes
and add them as reviewers to this enhancement.
## Support Procedures
Describe how to
- detect the failure modes in a support situation, describe possible symptoms (events, metrics,
alerts, which log output in which component)
Examples:
- If the webhook is not running, kube-apiserver logs will show errors like "failed to call admission webhook xyz".
- Operator X will degrade with message "Failed to launch webhook server" and reason "WehhookServerFailed".
- The metric `webhook_admission_duration_seconds("openpolicyagent-admission", "mutating", "put", "false")`
will show >1s latency and alert `WebhookAdmissionLatencyHigh` will fire.
- disable the API extension (e.g. remove MutatingWebhookConfiguration `xyz`, remove APIService `foo`)
- What consequences does it have on the cluster health?
Examples:
- Garbage collection in kube-controller-manager will stop working.
- Quota will be wrongly computed.
- Disabling/removing the CRD is not possible without removing the CR instances. Customer will lose data.
Disabling the conversion webhook will break garbage collection.
- What consequences does it have on existing, running workloads?
Examples:
- New namespaces won't get the finalizer "xyz" and hence might leak resource X
when deleted.
- SDN pod-to-pod routing will stop updating, potentially breaking pod-to-pod
communication after some minutes.
- What consequences does it have for newly created workloads?
Examples:
- New pods in namespace with Istio support will not get sidecars injected, breaking
their networking.
- Does functionality fail gracefully and will work resume when re-enabled without risking
consistency?
Examples:
- The mutating admission webhook "xyz" has FailPolicy=Ignore and hence
will not block the creation or updates on objects when it fails. When the
webhook comes back online, there is a controller reconciling all objects, applying
labels that were not applied during admission webhook downtime.
- Namespaces deletion will not delete all objects in etcd, leading to zombie
objects when another namespace with the same name is created.
## Alternatives
Similar to the `Drawbacks` section the `Alternatives` section is used
to highlight and record other possible approaches to delivering the
value proposed by an enhancement, including especially information
about why the alternative was not selected.
## Infrastructure Needed [optional]
Use this section if you need things from the project. Examples include a new
subproject, repos requested, github details, and/or testing infrastructure.