Hi Habib,
Thank you for the reminder. I'll update the KIP this week and address the
feedback from you and Gokul.
Regards,
Sean
On Tue, Jan 14, 2020 at 9:06 AM Habib Nahas <ha...@hbnet.io> wrote:
> Any chance of an update on the KIP? We are interested in seeing this move
> forward.
>
> Thanks,
> Habib
> Sr SDE, AWS
>
> On Wed, Dec 18, 2019, at 3:27 PM, Habib Nahas wrote:
> > Thanks Sean. Look forward to the updated KIP.
> >
> > Regards,
> > Habib
> >
> > On Fri, Dec 13, 2019, at 6:22 AM, Sean Glover wrote:
> > > Hi,
> > >
> > > After my last reply I had a nagging feeling something wasn't right,
> and I
> > > remembered that epoch time is UTC. This makes the discussion about
> > > timezone irrelevant, since we're always using UTC. This makes the need
> for
> > > the LatencyTime interface that I proposed in the design irrelevant as
> well,
> > > since I can no longer think about how that might be useful. I'll update
> > > the KIP. I'll also review KIP-32 to understand message timestamps
> better
> > > so I can explain the different types of latency results that could be
> > > reported with this metric.
> > >
> > > Regards,
> > > Sean
> > >
> > > On Thu, Dec 12, 2019 at 6:25 PM Sean Glover <sean.glo...@lightbend.com
> >
> > > wrote:
> > >
> > > > Hi Habib,
> > > >
> > > > Thanks for question! If the consumer is in a different timezone than
> the
> > > > timezone used to produce messages to a partition then you can use an
> > > > implementation of LatencyTime to return the current time of that
> timezone.
> > > > The current design assumes that messages produced to a partition
> must all
> > > > be produced from the same timezone. If timezone metadata were
> encoded into
> > > > each message then it would be possible to automatically determine the
> > > > source timezone and calculate latency, however the current design
> will not
> > > > pass individual messages into LatencyTime to retrieve message
> metadata.
> > > > Instead, the LatencyTime.getWallClockTime method is only called once
> per
> > > > fetch request response per partition and then the metric is recorded
> once
> > > > the latency calculation is complete. This follows the same design as
> the
> > > > current consumer lag metric which calculates offset lag based on the
> last
> > > > message of the fetch request response for a partition. Since the
> metric is
> > > > just an aggregate (max/mean) over some time window we only need to
> > > > occasionally calculate latency, which will have negligible impact on
> the
> > > > performance of consumer polling.
> > > >
> > > > A simple implementation of LatencyTime that returns wall clock time
> for
> > > > the Asia/Singapore timezone for all partitions:
> > > >
> > > > import java.time.*;
> > > >
> > > > class SingaporeTime implements LatencyTime {
> > > > ZoneId zoneSingapore = ZoneId.of("Asia/Singapore");
> > > > Clock clockSingapore = Clock.system(zoneSingapore);
> > > >
> > > > @Override
> > > > public long getWallClockTime(TopicPartition tp) {
> > > > return clockSingapore.instant.getEpochSecond();
> > > > }
> > > >
> > > > ...
> > > > }
> > > >
> > > > Regards,
> > > > Sean
> > > >
> > > >
> > > > On Thu, Dec 12, 2019 at 6:18 AM Habib Nahas <ha...@hbnet.io> wrote:
> > > >
> > > >> Hi Sean,
> > > >>
> > > >> Thanks for the KIP.
> > > >>
> > > >> As I understand it users are free to set their own timestamp on
> > > >> ProducerRecord. What is the recommendation for the proposed metric
> in a
> > > >> scenario where the user sets this timestamp in timezone A and
> consumes the
> > > >> record in timezone B. Its not clear to me if a custom
> implementation of
> > > >> LatencyTime will help here.
> > > >>
> > > >> Thanks,
> > > >> Habib
> > > >>
> > > >> On Wed, Dec 11, 2019, at 4:52 PM, Sean Glover wrote:
> > > >> > Hello again,
> > > >> >
> > > >> > There has been some interest in this KIP recently. I'm bumping the
> > > >> thread
> > > >> > to encourage feedback on the design.
> > > >> >
> > > >> > Regards,
> > > >> > Sean
> > > >> >
> > > >> > On Mon, Jul 15, 2019 at 9:01 AM Sean Glover <
> sean.glo...@lightbend.com>
> > > >> > wrote:
> > > >> >
> > > >> > > To hopefully spark some discussion I've copied the motivation
> section
> > > >> from
> > > >> > > the KIP:
> > > >> > >
> > > >> > > Consumer lag is a useful metric to monitor how many records are
> > > >> queued to
> > > >> > > be processed. We can look at individual lag per partition or we
> may
> > > >> > > aggregate metrics. For example, we may want to monitor what the
> > > >> maximum lag
> > > >> > > of any particular partition in our consumer subscription so we
> can
> > > >> identify
> > > >> > > hot partitions, caused by an insufficient producing partitioning
> > > >> strategy.
> > > >> > > We may want to monitor a sum of lag across all partitions so we
> have a
> > > >> > > sense as to our total backlog of messages to consume. Lag in
> offsets
> > > >> is
> > > >> > > useful when you have a good understanding of your messages and
> > > >> processing
> > > >> > > characteristics, but it doesn’t tell us how far behind *in
> time* we
> > > >> are.
> > > >> > > This is known as wait time in queueing theory, or more
> informally it’s
> > > >> > > referred to as latency.
> > > >> > >
> > > >> > > The latency of a message can be defined as the difference
> between when
> > > >> > > that message was first produced to when the message is received
> by a
> > > >> > > consumer. The latency of records in a partition correlates with
> lag,
> > > >> but a
> > > >> > > larger lag doesn’t necessarily mean a larger latency. For
> example, a
> > > >> topic
> > > >> > > consumed by two separate application consumer groups A and B
> may have
> > > >> > > similar lag, but different latency per partition. Application A
> is a
> > > >> > > consumer which performs CPU intensive business logic on each
> message
> > > >> it
> > > >> > > receives. It’s distributed across many consumer group members to
> > > >> handle the
> > > >> > > load quickly enough, but since its processing time is slower,
> it takes
> > > >> > > longer to process each message per partition. Meanwhile,
> Application
> > > >> B is
> > > >> > > a consumer which performs a simple ETL operation to land
> streaming
> > > >> data in
> > > >> > > another system, such as HDFS. It may have similar lag to
> Application
> > > >> A, but
> > > >> > > because it has a faster processing time its latency per
> partition is
> > > >> > > significantly less.
> > > >> > >
> > > >> > > If the Kafka Consumer reported a latency metric it would be
> easier to
> > > >> > > build Service Level Agreements (SLAs) based on non-functional
> > > >> requirements
> > > >> > > of the streaming system. For example, the system must never
> have a
> > > >> latency
> > > >> > > of greater than 10 minutes. This SLA could be used in monitoring
> > > >> alerts or
> > > >> > > as input to automatic scaling solutions.
> > > >> > >
> > > >> > > On Thu, Jul 11, 2019 at 12:36 PM Sean Glover <
> > > >> sean.glo...@lightbend.com>
> > > >> > > wrote:
> > > >> > >
> > > >> > >> Hi kafka-dev,
> > > >> > >>
> > > >> > >> I've created KIP-489 as a proposal for adding latency metrics
> to the
> > > >> > >> Kafka Consumer in a similar way as record-lag metrics are
> > > >> implemented.
> > > >> > >>
> > > >> > >>
> > > >> > >>
> > > >>
> https://cwiki.apache.org/confluence/display/KAFKA/489%3A+Kafka+Consumer+Record+Latency+Metric
> > > >> > >>
> > > >> > >> Regards,
> > > >> > >> Sean
> > > >> > >>
> > > >> > >> --
> > > >> > >> Principal Engineer, Lightbend, Inc.
> > > >> > >>
> > > >> > >> <http://lightbend.com>
> > > >> > >>
> > > >> > >> @seg1o <https://twitter.com/seg1o>, in/seanaglover
> > > >> > >> <https://www.linkedin.com/in/seanaglover/>
> > > >> > >>
> > > >> > >
> > > >> > >
> > > >> > > --
> > > >> > > Principal Engineer, Lightbend, Inc.
> > > >> > >
> > > >> > > <http://lightbend.com>
> > > >> > >
> > > >> > > @seg1o <https://twitter.com/seg1o>, in/seanaglover
> > > >> > > <https://www.linkedin.com/in/seanaglover/>
> > > >> > >
> > > >> >
> > > >>
> > > >
> > > >
> > >
> > > --
> > > Sean Glover
> > > Principal Engineer, Alpakka, Lightbend, Inc. <https://lightbend.com>
> > > @seg1o <https://twitter.com/seg1o>, in/seanaglover
> > > <https://www.linkedin.com/in/seanaglover/>
> > >
> >
