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From Greenhorn Techie <greenhorntec...@gmail.com>
Subject Re: Query on MirrorMaker Replication - Bi-directional/Failover replication
Date Tue, 17 Jan 2017 00:28:37 GMT
Thanks Ewen for the detailed response. This is quite helpful and cleared
some of my doubts. However, I do have some follow-up queries. Can you
please let me know your thoughts on the same?

[Query] Is non-compacted topics a pre-requisite to have this mechanism work
as expected? What are the challenges that need to be looked for in case of
compacted-topics?
1. Use MM normally to replicate your data. Be *very* sure you construct
your setup to ensure *everything* is mirrored (proper # of partitions,
replication factor, topic level configs, etc). (Note that this is something
the Confluent replication solution is addressing that's a significant
gap in MM.)
[Query] Here we are planning to use MirrorMaker to do the job for us and
hence topic creation etc is expected to be created by MirrorMaker (by
setting auto.create.topics.enable=true) Will this work? or will
setting auto.create.topics.enable=true
create the topic with default settings?
2. During replication, be sure to record offset deltas for every
topic partition. These are needed to reverse the direction of
replication correctly. Make sure to store them in the backup DC and
somewhere very reliable.
[Query] Is there any recommended approach to do this? As I am new to Kafka,
wondering if there is a good way of doing this
4. Decide to do failover. Ensure replication has actually stopped (via
your own tooling, or probably better, by using ACLs to ensure no new data
can be
produced from original DC to backup DC)
[Query] Does stopping replication mean killing the MirrorMaker process? Or
is there more needed here? Using ACLs probably, we can ensure the mirror
maker service account doesn't have read access on the source cluster and
write access on the DR cluster. Is there anything else to be done here?
5. Record all the high watermarks for every topic partition so you
know which data was replicated from the original DC (vs which is new
after failover).
[Query] Is there any best practice around this? In the presentation Jun Rao
talks about time-stamp based offset recording. As I understand, that would
probably help our case, where we can probably produce messages to the DR
cluster, from the point of failover
7. Once the original DC is back alive, you want to reverse replication
and make it the backup. Lookup the offset deltas, use them to
initialize offsets for the consumer group you'll use to do replication.
[Query]In order to lookup the offset deltas before initiating the consumers
on the original cluster, is there any recommended mechanism/tooling that
can be leveraged?

Best Regards

On Fri, 6 Jan 2017 at 03:31 Ewen Cheslack-Postava <ewen@confluent.io> wrote:

> On Thu, Jan 5, 2017 at 3:07 AM, Greenhorn Techie <
> greenhorntechie@gmail.com>
> wrote:
>
> > Hi,
> >
> > We are planning to setup MirrorMaker based Kafka replication for DR
> > purposes. The base requirement is to have a DR replication from primary
> > (site1) to DR site  (site2)using MirrorMaker,
> >
> > However, we need the solution to work in case of failover as well i.e.
> > where in the event of the site1 kafka cluster failing, site2 kafka
> cluster
> > would be made primary. Later when site1 cluster eventually comes back-up
> > online, direction of replication would be from site2 to site1.
> >
> > But as I understand, the offsets on each of the clusters are different,
> so
> > wondering how to design the solution given this constraint and
> > requirements.
> >
>
> It turns out this is tricky. And once you start digging in you'll find it's
> way more complicated than you might originally think.
>
> Before going down the rabbit hole, I'd suggest taking a look at this great
> talk by Jun Rao (one of the original authors of Kafka) about multi-DC Kafka
> setups: https://www.youtube.com/watch?v=Dvk0cwqGgws
>
> Additionally, I want to mention that while it is tempting to want to treat
> multi-DC DR cases in a way that we get really convenient, strongly
> consistent, highly available behavior because that makes it easier to
> reason about and avoids pushing much of the burden down to applications,
> that's not realistic or practical. And honestly, it's rarely even
> necessary. DR cases really are DR. Usually it is possible to make some
> tradeoffs you might not make under normal circumstances (the most important
> one being the tradeoff between possibly seeing duplicates vs exactly once).
> The tension here is often that one team is responsible for maintain the
> infrastructure and handling this DR failover scenario, and others are
> responsible for the behavior of the applications. The infrastructure team
> is responsible for figuring out the DR failover story but if they don't
> solve it at the infrastructure layer then they get stuck having to
> understand all the current (and future) applications built on that
> infrastructure.
>
> That said, here are the details I think you're looking for:
>
> The short answer right now is that doing DR failover like that is not going
> to be easy with MM. Confluent is building additional tools to deal with
> multi-DC setups because of a bunch of these challenges:
> https://www.confluent.io/product/multi-datacenter/
>
> For your specific concern about reversing the direction of replication,
> you'd need to build additional tooling to support this. The basic list of
> steps would be something like this (assuming non-compacted topics):
>
> 1. Use MM normally to replicate your data. Be *very* sure you construct
> your setup to ensure *everything* is mirrored (proper # of partitions,
> replication factor, topic level configs, etc). (Note that this is something
> the Confluent replication solution is addressing that's a significant gap
> in MM.)
> 2. During replication, be sure to record offset deltas for every topic
> partition. These are needed to reverse the direction of replication
> correctly. Make sure to store them in the backup DC and somewhere very
> reliable.
> 3. Observe DC failure.
> 4. Decide to do failover. Ensure replication has actually stopped (via your
> own tooling, or probably better, by using ACLs to ensure no new data can be
> produced from original DC to backup DC)
> 5. Record all the high watermarks for every topic partition so you know
> which data was replicated from the original DC (vs which is new after
> failover).
> 6. Allow failover to proceed. Make the backup DC primary.
> 7. Once the original DC is back alive, you want to reverse replication and
> make it the backup. Lookup the offset deltas, use them to initialize
> offsets for the consumer group you'll use to do replication.
> 8. Go back to the original DC and make sure there isn't any "extra" data,
> i.e. stuff that didn't get replicated but was successfully written to the
> original DC's cluster. For topic partitions where there is data beyond the
> expected offsets, you currently would need to just delete the entire set of
> data, or at least to before the offset we expect to start at. (A truncate
> operation might be a nice way to avoid having to dump *all* the data, but
> doesn't currently exist.)
> 9. Once you've got the two clusters back in a reasonably synced state with
> appropriate starting offsets committed, start up MM again in the reverse
> direction.
>
> If this sounds tricky, it turns out that when you add compacted topics,
> things get quite a bit messier....
>
> -Ewen
>
>
> >
> > Thanks
> >
>

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