Thanks for the votes so far! Due to recent discussions, I've removed the high-level REST API from the KIP.
On Thu, Dec 20, 2018 at 12:42 PM Paul Davidson <pdavid...@salesforce.com> wrote: > +1 > > Would be great to see the community build on the basic approach we took > with Mirus. Thanks Ryanne. > > On Thu, Dec 20, 2018 at 9:01 AM Andrew Psaltis <psaltis.and...@gmail.com> > wrote: > > > +1 > > > > Really looking forward to this and to helping in any way I can. Thanks > for > > kicking this off Ryanne. > > > > On Thu, Dec 20, 2018 at 10:18 PM Andrew Otto <o...@wikimedia.org> wrote: > > > > > +1 > > > > > > This looks like a huge project! Wikimedia would be very excited to have > > > this. Thanks! > > > > > > On Thu, Dec 20, 2018 at 9:52 AM Ryanne Dolan <ryannedo...@gmail.com> > > > wrote: > > > > > > > Hey y'all, please vote to adopt KIP-382 by replying +1 to this > thread. > > > > > > > > For your reference, here are the highlights of the proposal: > > > > > > > > - Leverages the Kafka Connect framework and ecosystem. > > > > - Includes both source and sink connectors. > > > > - Includes a high-level driver that manages connectors in a dedicated > > > > cluster. > > > > - High-level REST API abstracts over connectors between multiple > Kafka > > > > clusters. > > > > - Detects new topics, partitions. > > > > - Automatically syncs topic configuration between clusters. > > > > - Manages downstream topic ACL. > > > > - Supports "active/active" cluster pairs, as well as any number of > > active > > > > clusters. > > > > - Supports cross-data center replication, aggregation, and other > > complex > > > > topologies. > > > > - Provides new metrics including end-to-end replication latency > across > > > > multiple data centers/clusters. > > > > - Emits offsets required to migrate consumers between clusters. > > > > - Tooling for offset translation. > > > > - MirrorMaker-compatible legacy mode. > > > > > > > > Thanks, and happy holidays! > > > > Ryanne > > > > > > > > > > > > -- > Paul Davidson > Principal Engineer, Ajna Team > Big Data & Monitoring >
