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neat-enhancement-idea |
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To get started with this template:
- Pick a domain. Find the appropriate domain to discuss your enhancement.
- Make a copy of this template. Copy this template into the directory for the domain.
- 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.
- Create a PR. Assign it to folks with expertise in that domain to help sponsor the process.
- 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.
- 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.
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.
The Summary
section is incredibly 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.
A good summary is no more than one paragraph in length. More detail should go into the following sections.
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.
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 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.
- 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.
- 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.
Include a story on how this proposal will be operationalized: life-cycled, monitored and remediated at scale.
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.
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.
This is where we get down to the nitty gritty of what the proposal actually is. Describe clearly what will be changed, 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, and expand on reasons for not choosing alternatives in the Alternatives section at the end of the document.
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 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.
- The cluster creator sits down at their keyboard...
- ...
- The cluster creator sees that their cluster is ready to receive applications, and gives the application administrator their credentials.
If the cluster creator uses a standing desk, in step 1 above they can stand instead of sitting down.
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 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.
What are the caveats to the implementation? What are some important details that didn't come across above. Go in to as much detail as necessary here. This might be a good place to talk about core concepts and how they relate.
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.
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?
This is where to call out areas of the design that require closure before deciding to implement the design. For instance,
- This requires exposing previously private resources which contain sensitive information. Can we do this?
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).
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 KubernetesDev Preview
,Tech Preview
,GA
in OpenShift
- Deprecation policy
Clearly define what graduation means by either linking to the API doc definition, or by redefining what graduation means.
In general, we try to use the same stages (alpha, beta, GA), regardless how the functionality is accessed.
If this is a user facing change requiring new or updated documentation in 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.
- 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)
- 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
For non-optional features moving to GA, the graduation criteria must include end to end tests.
- Announce deprecation and support policy of the existing feature
- Deprecate the feature
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. 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 requiringx.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 a4.3->4.4
step followed by a4.4->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 theN+1
cluster is misbehaving, it should be possible for the user to rollback toN
. 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.
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.
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
- authentication-operator condition
-
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.
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 alertWebhookAdmissionLatencyHigh
will fire.
-
disable the API extension (e.g. remove MutatingWebhookConfiguration
xyz
, remove APIServicefoo
)-
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.
Major milestones in the life cycle of a proposal should be tracked in Implementation History
.
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.
Use this section if you need things from the project. Examples include a new subproject, repos requested, github details, and/or testing infrastructure.
Listing these here allows the community to get the process for these resources started right away.