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+# SIG Scalability Charter
+
+## Mission
+The SIG Scalability helps to define scalability goals for Kubernetes, ensures
+that they all play well together and ensures that every Kubernetes release meets
+them by measuring performance and scalability indicators and publishing the
+results.
+
+We also coordinate and contribute to general system-wide scalability and
+performance improvements (that don’t fall into the charter of another individual
+SIG) as well as provide consultations about any scalability and performance
+related aspects of Kubernetes.
+
+## What can we do/require from other SIGs
+Scalability and performance are horizontal aspects of the system - changes in a
+single place of Kubernetes may affect the whole system. As a result, to
+effectively ensure Kubernetes scales, we need a special cross-SIG privileges.
+
+- We can rollback any merged PR if it has been identified as a cause of an SLO
+ regression. The offending PR should only be merged again after proving to pass
+ tests at scale.
+- We can pause the merge queue in case of a regression observed until a particular
+ PR has been identified as cause of the regression and regression has been
+ mitigated. The “Rules of engagement” of pausing merge-queue and rationale for
+ necessity of its introduce are explained in a separate doc.
+ TODO(wojtek-t, shyamjvs): Write it down and link here.
+- We require significant changes (in terms of impact, such as: update of etcd,
+ update of Go version, major architectural changes, etc.) may only be merged:
+ - with an explicit approval from a SIG-scalability approver and
+ - after having passed performance testing on biggest supported clusters (unless
+ found unnecessary by scalability approver)
+- We can block a feature from transitioning to Beta status if (when turned on) it
+ causes a significant degradation of overall Kubernetes scalability/performance.
+ (Ideally it would be “SLI degradation of more than X%” or “breaking SLO”, but
+ initially it may also be SIG-scalability decision based on public test results).
+- We can block a feature from transitioning to GA status if it cannot be used at
+ scale.
+- We can require a SIG to introduce a regression-catching benchmark test for a
+ scalability-critical functionality.
+
+For the record, by regression above we mean a regression identified by the set
+of release-blocking scalability/performance tests (as defined by
+sig-release-master-blocking group of test suites).
+
+## SIG Values
+
+- We are NOT firefighters, we are fire-prevention specialists.
+- We promote deep technical understanding of the Kubernetes system and our tools.
+- We strive to eliminate toil.
+- We work towards building a scalable Kubernetes even in face of superlinear growth
+ of number of contributors.
+
+## Scope and subprojects
+The scope of SIG Scalability covers all aspects of Kubernetes scalability and
+performance. However, all issues that fully fall under a single SIG are implicitly
+delegated to that SIG.
+
+SIG scalability subprojects are as follows.
+
+
Subproject | +Description | +Example Artifacts | +
Kubernetes scalability | +Defining what does it mean that “Kubernetes scales”. This includes defining + (or approving) individual performance SLIs/SLOs, ensuring they are all oriented + on user experience and consistent with each other. | +API-machinery performance SLIs/SLOs | +
Kubernetes performance validation | +Ensuring that each official Kubernetes release satisfies all scalability and + performance related requirements, as state in “Kubernetes scalability” + definition. | +1.9 validation report | +
Scalability testing frameworks | +Designing and creating frameworks to make scalability and performance testing + of Kubernetes easy and available for all contributors. Different frameworks may + help in different aspect of scalability testing enabling making conscious tradeoffs, + e.g. cost of accuracy or real life vs more generalized benchmarking scenarios. | +Cluster loader | +
Scalability and performanc tests | +Ensuring that all tests necessary to validate Kubernetes scalability and + performance exist (ideally by providing easy-to-use framework and working with SIGs + to provide them) have the environment and resources to run on and are being + executed according to calendar enabling release validation. | +Scalability e2e tests | +
Scalability governance | +Establishing and documenting best practises on how to design and/or implement + Kubernetes features in scalable and performant way. Educating contributors and + ensuring those are widely used. | +Regressions case study | +