Ewen, you gave a nice talk at Kafka Summit where you warned about the danger of SMTs that slow down the data pipe. If we don't provide the time metrics, how will users know when their SMTs are causing performance issues?
Gwen On Mon, Sep 11, 2017 at 7:50 PM Ewen Cheslack-Postava <e...@confluent.io> wrote: > re: questions about additional metrics, I think we'll undoubtedly find more > that people want in practice, but as I mentioned earlier I think it's > better to add the ones we know we need and then fill out the rest as we > figure it out. So, e.g., batch size metrics sound like they could be > useful, but I'd probably wait until we have a clear use case. It seems > likely that it could be useful in diagnosing slow connectors (e.g. the > implementation just does something inefficient), but I'm not really sure > about that yet. > > -Ewen > > On Mon, Sep 11, 2017 at 7:11 PM, Randall Hauch <rha...@gmail.com> wrote: > > > Based on Roger and Ewen's feedback, I removed the aggregate metrics as > they > > would be difficult to make use of without extra work. This simplified > > things a great deal, and I took the opportunity to reorganize the groups > of > > metrics. Also, based upon Ewen's concerns regarding measuring > > times/durations, I removed all time-related metrics except for the offset > > commits and rebalances, which are infrequent enough to warrant the > capture > > of percentiles. Roger asked about capturing batch size metrics for source > > and sink tasks, and offset lag metrics for sink tasks. Finally, Ewen > > pointed out that all count/total metrics are only valid since the most > > recent rebalance and are therefore less meaningful, and were removed. > > > > On Mon, Sep 11, 2017 at 6:50 PM, Randall Hauch <rha...@gmail.com> wrote: > > > > > Thanks, Ewen. Comments inline below. > > > > > > On Mon, Sep 11, 2017 at 5:46 PM, Ewen Cheslack-Postava < > > e...@confluent.io> > > > wrote: > > > > > >> Randall, > > >> > > >> A couple of questions: > > >> > > >> * Some metrics don't seem to have unique names? e.g. > > >> source-record-produce-rate and source-record-produce-total seem like > > they > > >> are duplicated. Looks like maybe just an oversight that the second > ones > > >> should be changed from "produce" to "write". > > >> > > > > > > Nice catch. You are correct - should be "write" instead of "produce". I > > > will correct. > > > > > > > > >> * I think there's a stray extra character in a couple of > > >> places: kafka.connect:type=source-task-metrics,name=source-record- > > >> produce-total,worker=([-.\w]+)l,connector=([-.\w]+),task=([\d]+) > > >> has an extra char after the worker name. > > >> > > > > > > Thanks. Removed in 2 places. > > > > > > > > >> * Are the produce totals actually useful given rebalancing would > cancel > > >> them out anyway? Doesn't seem like you could do much with them. > > >> > > > > > > Yes, the totals would be since the last rebalance. Maybe that isn't > that > > > useful. Might be better to capture the offsets and lag as Roger was > > > suggestion. Thoughts? > > > > > > > > >> * Why do transformations get their own metric but not converters? And > > are > > >> we concerned at all about the performance impact of getting such fine > > >> grained info? Getting current time isn't free and we've seen before > that > > >> we > > >> ended up w/ accidental performance regressions as we tried to check it > > too > > >> frequently to enforce timeouts fine grained in the producer (iirc). > > >> Batching helps w/ this, but on the consumer side, a max.poll.records=1 > > >> setting could put you in a bad place, especially since transforms > might > > be > > >> very lightweight (or nothing) and converters are expected to be > > relatively > > >> cheap as well. > > >> > > > > > > We could remove the read, transform, and put time-based metrics for > sink > > > tasks, and poll, transform, and write time-based metrics. Can/should > they > > > be replaced with anything else? > > > > > > > > >> * If we include the worker id everywhere and don't have metrics > without > > >> that included, isn't that a pain for users that dump this data into > some > > >> other system? They have to know which worker the connector/task is > > >> currently on *or* need to do extra work to merge the metrics from > across > > >> machines. Including versions with the worker ID can make sense for > > >> completeness and accuracy (e.g. technically there are still very slim > > >> risks > > >> of having a task running twice due to zombies), but it seems like bad > > >> usability for the common case. > > >> > > > > > > Part of the reason was also to help identify where each of the metrics > > > came from, but per the next comment this may not be as useful, either. > > > So remove the worker ID in all the task and connector metric names? > What > > > about the worker metrics? > > > > > > > > >> * Is aggregating things like source record rate at the (worker, > > connector) > > >> level really useful since you're just going to need to do additional > > >> aggregation anyway once you've collected metrics across all workers? > I'd > > >> rather add a smaller number of metrics w/ clear use cases than just > try > > to > > >> be exhaustive and then have to maintain stuff that nobody actually > uses. > > >> > > > > > > Yes, the connector aggregate metrics are maybe not as useful if you > also > > > have to aggregate them from different workers. Removing them probably > > also > > > reduces the risk of them being misinterpretted. > > > > > > > > >> * You have status for connectors but not for tasks. Any reason why? > > Seems > > >> like it'd make sense to expose both, especially since users generally > > care > > >> about task status more than connector status (not many connectors > > actually > > >> run a monitoring thread.) > > >> > > > > > > Ack. > > > > > > > > >> * Is number of tasks for each connector a useful metric? Not sure > > whether > > >> someone would find this useful or not. Probably not for alerts, but > > might > > >> be useful to be able to check it via your metrics dashboard. > > >> > > > > > > Seems like it might be useful, at least in terms of tracking the number > > of > > > tasks over time. Might not be as useful for connectors that have > > relatively > > > static tasks, but it would be more interesting/useful for connectors > that > > > create tasks dynamically and periodically request task > reconfigurations. > > > > > > > > >> * Same questions re: granularity of sink tasks/connectors timing and > > >> whether the connectors need all the roll-ups of individual (worker, > > task) > > >> values to (worker, connector) level. > > >> > > > > > > I'm fine with taking out the aggregates to keep things simple and > prevent > > > misunderstanding. > > > > > > > > >> * If we expose the who the worker currently thinks is leader, it might > > >> also > > >> make sense to expose the underlying epoch. Not actually sure if we > > expose > > >> that for the consumer today, but it's an indicator of who is properly > up > > >> to > > >> date. > > >> > > > > > > Ack. > > > > > > > > >> * Why worker-level offset commit stats? It's not clear to me that > these > > >> are > > >> useful without considering the specific connector. > > >> > > > > > > So would they make more sense on the tasks? Again, on the worker > they're > > > aggregates. > > > > > > > > >> > > >> -Ewen > > >> > > >> > > >> On Mon, Sep 11, 2017 at 9:43 AM, Randall Hauch <rha...@gmail.com> > > wrote: > > >> > > >> > Thanks for reviewing. Responses inline below. > > >> > > > >> > On Mon, Sep 11, 2017 at 11:22 AM, Roger Hoover < > > roger.hoo...@gmail.com> > > >> > wrote: > > >> > > > >> > > Randall, > > >> > > > > >> > > Thank you for the KIP. This should improve visibility greatly. I > > >> had a > > >> > > few questions/ideas for more metrics. > > >> > > > > >> > > > > >> > > 1. What's the relationship between the worker state and the > > >> connector > > >> > > status? Does the 'paused' status at the Connector level > include > > >> the > > >> > > time > > >> > > that worker is 'rebalancing'? > > >> > > > > >> > > > >> > The worker state metric simply reports whether the worker is running > > or > > >> > rebalancing. This state is independent of how many connectors are > > >> > deployed/running/paused. During a rebalance, the connectors are > being > > >> > stopped and restarted but are effectively not running. > > >> > > > >> > > > >> > > 2. Are the "Source Connector" metrics like record rate an > > >> aggregation > > >> > of > > >> > > the "Source Task" metrics? > > >> > > > > >> > > > >> > Yes. > > >> > > > >> > > > >> > > - How much value is there is monitoring at the "Source > > >> Connector" > > >> > > level (other than status) if the number of constituent tasks > > may > > >> > > change > > >> > > over time? > > >> > > > > >> > > > >> > The task metrics allow you to know whether the tasks are evenly > loaded > > >> and > > >> > each making progress. The aggregate connector metrics tell you how > > much > > >> > work has been performed by all the tasks in that worker. Both are > > useful > > >> > IMO. > > >> > > > >> > > > >> > > - I'm imagining that it's most useful to collect metrics at > > the > > >> > task > > >> > > level as the task-level metrics should be stable regardless > of > > >> > tasks > > >> > > shifting to different workers > > >> > > > > >> > > > >> > Correct, this is where the most value is because it is the most fine > > >> > grained. > > >> > > > >> > > > >> > > - If so, can we duplicate the Connector Status down at the > > task > > >> > level > > >> > > so that all important metrics can be tracked by task? > > >> > > > > >> > > > >> > Possibly. The challenge is that the threads running the tasks are > > >> blocked > > >> > when a connector is paused. > > >> > > > >> > > > >> > > 3. For the Sink Task metrics > > >> > > - Can we add offset lag and timestamp lag on commit? > > >> > > - After records are flushed/committed > > >> > > - what is the diff between the record timestamps and > > >> commit > > >> > > time (histogram)? this is a measure of end-to-end > > >> pipeline > > >> > > latency > > >> > > - what is the diff between record offsets and latest > > >> offset > > >> > of > > >> > > their partition at commit time (histogram)? this is a > > >> > > measure of whether > > >> > > this particular task is keeping up > > >> > > > > >> > > > >> > Yeah, possibly. Will have to compare with the consumer metrics to > see > > >> what > > >> > we can get. > > >> > > > >> > > > >> > > - How about flush error rate? Assuming the sink > connectors > > >> are > > >> > > using retries, it would be helpful to know how many errors > > >> they're > > >> > > seeing > > >> > > > > >> > > > >> > We could add a metric to track how many times the framework > receives a > > >> > retry exception and then retries, but the connectors may also do > this > > on > > >> > their own. > > >> > > > >> > > > >> > > - Can we tell at the framework level how many records were > > >> inserted > > >> > > vs updated vs deleted? > > >> > > > > >> > > > >> > No, there's no distinction in the Connect framework. > > >> > > > >> > > > >> > > - Batching stats > > >> > > - Histogram of flush batch size > > >> > > - Counts of flush trigger method (time vs max batch size) > > >> > > > > >> > > > >> > Should be able to add these. > > >> > > > >> > > > >> > > > > >> > > Cheers, > > >> > > > > >> > > Roger > > >> > > > > >> > > On Sun, Sep 10, 2017 at 8:45 AM, Randall Hauch <rha...@gmail.com> > > >> wrote: > > >> > > > > >> > > > Thanks, Gwen. > > >> > > > > > >> > > > That's a great idea, so I've changed the KIP to add those > metrics. > > >> I've > > >> > > > also made a few other changes: > > >> > > > > > >> > > > > > >> > > > 1. The context of all metrics is limited to the activity > within > > >> the > > >> > > > worker. This wasn't clear before, so I changed the motivation > > and > > >> > > metric > > >> > > > descriptions to explicitly state this. > > >> > > > 2. Added the worker ID to all MBean attributes. In addition > to > > >> > > hopefully > > >> > > > making this same scope obvious from within JMX or other > metric > > >> > > reporting > > >> > > > system. This is also similar to how the Kafka producer and > > >> consumer > > >> > > > metrics > > >> > > > include the client ID in their MBean attributes. Hopefully > this > > >> does > > >> > > not > > >> > > > negatively impact or complicate how external reporting > systems' > > >> > > > aggregate > > >> > > > metrics from multiple workers. > > >> > > > 3. Stated explicitly that aggregating metrics across workers > > was > > >> out > > >> > > of > > >> > > > scope of this KIP. > > >> > > > 4. Added metrics to report the connector class and version > for > > >> both > > >> > > sink > > >> > > > and source connectors. > > >> > > > > > >> > > > Check this KIP's history for details of these changes. > > >> > > > > > >> > > > Please let me know if you have any other suggestions. I hope to > > >> start > > >> > the > > >> > > > voting soon! > > >> > > > > > >> > > > Best regards, > > >> > > > > > >> > > > Randall > > >> > > > > > >> > > > On Thu, Sep 7, 2017 at 9:35 PM, Gwen Shapira <g...@confluent.io > > > > >> > wrote: > > >> > > > > > >> > > > > Thanks for the KIP, Randall. Those are badly needed! > > >> > > > > > > >> > > > > Can we have two metrics with record rate per task? One before > > SMT > > >> and > > >> > > one > > >> > > > > after? > > >> > > > > We can have cases where we read 5000 rows from JDBC but write > 5 > > to > > >> > > Kafka, > > >> > > > > or read 5000 records from Kafka and write 5 due to filtering. > I > > >> think > > >> > > its > > >> > > > > important to know both numbers. > > >> > > > > > > >> > > > > > > >> > > > > Gwen > > >> > > > > > > >> > > > > On Thu, Sep 7, 2017 at 7:50 PM, Randall Hauch < > rha...@gmail.com > > > > > >> > > wrote: > > >> > > > > > > >> > > > > > Hi everyone. > > >> > > > > > > > >> > > > > > I've created a new KIP to add metrics to the Kafka Connect > > >> > framework: > > >> > > > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP- > > >> > > > > > 196%3A+Add+metrics+to+Kafka+Connect+framework > > >> > > > > > > > >> > > > > > The KIP approval deadline is looming, so if you're > interested > > in > > >> > > Kafka > > >> > > > > > Connect metrics please review and provide feedback as soon > as > > >> > > possible. > > >> > > > > I'm > > >> > > > > > interested not only in whether the metrics are sufficient > and > > >> > > > > appropriate, > > >> > > > > > but also in whether the MBean naming conventions are okay. > > >> > > > > > > > >> > > > > > Best regards, > > >> > > > > > > > >> > > > > > Randall > > >> > > > > > > > >> > > > > > > >> > > > > > > >> > > > > > > >> > > > > -- > > >> > > > > *Gwen Shapira* > > >> > > > > Product Manager | Confluent > > >> > > > > 650.450.2760 <(650)%20450-2760> | @gwenshap > > >> > > > > Follow us: Twitter <https://twitter.com/ConfluentInc> | blog > > >> > > > > <http://www.confluent.io/blog> > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > > > > > > > >
