X-czh commented on code in PR #581:
URL:
https://github.com/apache/flink-kubernetes-operator/pull/581#discussion_r1184861589
##########
flink-kubernetes-operator-autoscaler/src/main/java/org/apache/flink/kubernetes/operator/autoscaler/config/AutoScalerOptions.java:
##########
@@ -98,6 +98,13 @@ private static ConfigOptions.OptionBuilder
autoScalerConfig(String key) {
.withDescription(
"Max scale down factor. 1 means no limit on scale
down, 0.6 means job can only be scaled down with 60% of the original
parallelism.");
+ public static final ConfigOption<Double> MAX_SCALE_UP_FACTOR =
+ autoScalerConfig("scale-up.max-factor")
+ .doubleType()
+ .defaultValue(2.0)
Review Comment:
For example, in my company:
1. Job input usu. has periodic pattern, sometimes spikes but smoothly change
in most cases
2. Underlying resources are not elastic, resource competition between jobs
is not rare
3. Job types are diverse with heavy dependency on various external services,
scaling Flink alone is often ineffective
4. The scale is gigantic (over 40k jobs), we have to carefully limit the
autoscaler's behavior to prevent resonant scaling behaviors from causing
massive failures
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