Dennis-Mircea commented on code in PR #877: URL: https://github.com/apache/flink-web/pull/877#discussion_r3850678342
########## docs/content/posts/2026-08-06-release-kubernetes-operator-1.16.0.md: ########## @@ -0,0 +1,131 @@ +--- +title: "Apache Flink Kubernetes Operator 1.16.0 Release Announcement" +date: "2026-08-06T08:00:00.000Z" +authors: +- gyfora: + name: "Gyula Fora" +aliases: +- /news/2026/08/06/release-kubernetes-operator-1.16.0.html +--- + +The Apache Flink community is excited to announce the release of Flink Kubernetes Operator 1.16.0! + +This release centers on **extensibility and documentation**: a completely restructured documentation site, a new default for autoscaler parallelism alignment, a trio of pluggable autoscaler SPIs (custom evaluators, scaling executors, and alignment modes), Kubernetes-native pod `ResourceRequirements`, and a range of Blue/Green, session job, and savepoint reliability fixes. + +We encourage you to [download the release](https://flink.apache.org/downloads.html) and share your experience with the community through the Flink [mailing lists](https://flink.apache.org/community.html#mailing-lists) or [JIRA](https://issues.apache.org/jira/browse/flink)! We're looking forward to your feedback! + +## Highlights + +### Restructured Documentation + +The operator documentation has been comprehensively reorganized and expanded for better navigability and coverage. The site is now grouped into clear top-level areas: **Concepts** (architecture, autoscaling, lifecycle management, and a glossary), **Deployment** (installation, configuration, compatibility, security, leader election, and Helm topics such as cert-manager and RBAC), a consolidated **Custom Resource** reference, **Operations**, and a brand new **Internals** section that documents how the operator actually works under the hood, covering the controller flow, the autoscaler, the admission webhook, and operator startup. + +Beyond moving pages around, large parts of the content were rewritten and gaps were filled, so users and contributors now have a single, coherent map of the operator, from first install through to its internal design. + +### New Default for Autoscaler Parallelism Alignment + +The way the autoscaler aligns a computed target parallelism to the number of key groups or source partitions has a new default. Alignment is now driven by `job.autoscaler.scaling.parallelism-alignment.mode`, which defaults to `BALANCED`, replacing the previous `job.autoscaler.scaling.key-group.partitions.adjust.mode` default of `EVENLY_SPREAD`. + +Two differences are visible in day-to-day scaling: + +- **A scale is no longer blocked.** The previous default kept the vertex at its current parallelism and emitted a `ScalingLimited` event whenever no aligned parallelism preserved the scaling direction. `BALANCED` falls back to the computed target instead, so a scaling decision is applied rather than vetoed. +- **Mild skew is tolerated to avoid over-provisioning.** `EVENLY_SPREAD` snaps to an exact divisor of the key group or partition count, while `BALANCED` takes the first parallelism that reduces per-subtask load. With 128 key groups and a computed target of 24, the old default moved to 32 where the new one settles at 26. + +The previous behavior is still available. The deprecated `scaling.key-group.partitions.adjust.mode` key continues to select the original blocking modes unchanged, `EVENLY_SPREAD` is also offered as a built-in mode under the new key, and `OFF` disables alignment entirely. + +### Autoscaler Extensibility: Pluggable Evaluators, Scaling Executors, and Alignment Modes + +The autoscaler becomes extensible through three new plugin SPIs, all discovered via the standard plugin mechanism and each configurable per named instance. Together they let you customize the autoscaler without forking it: + +- **Custom Evaluator plugin ([FLIP-514](https://cwiki.apache.org/confluence/display/FLINK/FLIP-514)):** inject custom scaling-metric evaluation logic into the evaluation pipeline, augmenting or overriding how the autoscaler interprets the collected metrics before a scaling decision is made. Review Comment: Good catch, I don't know from where I copied them. I've fixed them now. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
