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https://issues.apache.org/jira/browse/KAFKA-12472?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17302889#comment-17302889
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A. Sophie Blee-Goldman commented on KAFKA-12472:
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{quote} illegal generation id is usually due to a new member with the same id
replaced an old member and then later the old zombie member tries to talk to
coordinator (though with the new model, this should mostly be for static
members).
{quote}
Makes sense – but just wondering, what are you referring to here by "new model"
{quote}Re. 3: My reasoning is that if a new member joins the group and triggers
the rebalance, then from observability point of view we would like to know it's
due to "NewMember", not "CoordinatorRequested", since the latter is actually
not the "root" cause. This applies to both consumer and streams.
{quote}
The motivation here sounds good, as the "CoordinatorRequested" state doesn't
really tell you why it's rebalancing – but it does seem to potentially violate
the transition rule that "a non-zero status code can only transit to zero or to
a higher code". What if you have a new member join and then some other consumer
in another client triggers a rebalance, causing the new member to get the
RebalanceInProgressException before it's able to complete the first rebalance.
Shouldn't it then transition from *NewMember* --> *CoordinatorRequested* ? But
this transition is disallowed under this rule.
Similarly, it seems like a single StreamThread could go from any of the
Streams-specific states to almost any of the consumer states, eg
*AssignmentProbing -->* *DroppedGroup*. I guess I'm wondering why do we need
this transition rule in the first place?
> Add a Consumer / Streams metric to indicate the current rebalance status
> ------------------------------------------------------------------------
>
> Key: KAFKA-12472
> URL: https://issues.apache.org/jira/browse/KAFKA-12472
> Project: Kafka
> Issue Type: Improvement
> Components: consumer, streams
> Reporter: Guozhang Wang
> Priority: Major
> Labels: needs-kip
>
> Today to trouble shoot a rebalance issue operators need to do a lot of manual
> steps: locating the problematic members, search in the log entries, and look
> for related metrics. It would be great to add a single metric that covers all
> these manual steps and operators would only need to check this single signal
> to check what is the root cause. A concrete idea is to expose two enum gauge
> metrics on consumer and streams, respectively:
> * Consumer level (the order below is by-design, see Streams level for
> details):
> 0. *None* => there is no rebalance on going.
> 1. *CoordinatorRequested* => any of the coordinator response contains a
> RebalanceInProgress error code.
> 2. *NewMember* => when the join group response has a MemberIdRequired error
> code.
> 3. *UnknownMember* => when any of the coordinator response contains an
> UnknownMember error code, indicating this member is already kicked out of the
> group.
> 4. *StaleMember* => when any of the coordinator response contains an
> IllegalGeneration error code.
> 5. *DroppedGroup* => when hb thread decides to call leaveGroup due to hb
> expired.
> 6. *UserRequested* => when leaveGroup upon the shutdown / unsubscribeAll
> API, as well as upon calling the enforceRebalance API.
> 7. *MetadataChanged* => requestRejoin triggered since metadata has changed.
> 8. *SubscriptionChanged* => requestRejoin triggered since subscription has
> changed.
> 9. *RetryOnError* => when join/syncGroup response contains a retriable
> error which would cause the consumer to backoff and retry.
> 10. *RevocationNeeded* => requestRejoin triggered since revoked partitions
> is not empty.
> The transition rule is that a non-zero status code can only transit to zero
> or to a higher code, but not to a lower code (same for streams, see
> rationales below).
> * Streams level: today a streams client can have multiple consumers. We
> introduced some new enum states as well as aggregation rules across
> consumers: if there's no streams-layer events as below that transits its
> status (i.e. streams layer think it is 0), then we aggregate across all the
> embedded consumers and take the largest status code value as the streams
> metric; if there are streams-layer events that determines its status should
> be in 10+, then it ignores all embedded consumer layer status code since it
> should has a higher precedence. In addition, when create aggregated metric
> across streams instance (a.k.a at the app-level, which is usually what we
> would care and alert on), we also follow the same aggregation rule, e.g. if
> there are two streams instance where one instance's status code is 1), and
> the other is 10), then the app's status is 10).
> 10. *RevocationNeeded* => the definition of this is changed to the original
> 10) defined in consumer above, OR leader decides to revoke either
> active/standby tasks and hence schedule follow-ups.
> 11. *AssignmentProbing* => leader decides to schedule follow-ups since the
> current assignment is unstable.
> 12. *VersionProbing* => leader decides to schedule follow-ups due to version
> probing.
> 13. *EndpointUpdate* => anyone decides to schedule follow-ups due to
> endpoint updates.
> The main motivations of the above proposed precedence order are the following:
> 1. When a rebalance is triggered by one member, all other members would only
> know it is due to CoordinatorRequested from coordinator error codes, and
> hence CoordinatorRequested should be overridden by any other status when
> aggregating across clients.
> 2. DroppedGroup could cause unknown/stale members that would fail and retry
> immediately, and hence should take higher precedence.
> 3. Revocation definition is extended in Streams, and hence it needs to take
> the highest precedence among all consumer-only status so that it would not be
> overridden by any of the consumer-only status.
> 4. In general, more rare events get higher precedence.
> This is proposed on top of KAFKA-12352. Any comments on the precedence rules
> / categorization are more than welcomed!
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