Cross-Region MSK Replication: K2K vs. MirrorMaker2

Cloud data showdown: K2K touted faster, MirrorMaker under fire

TLDR: Lenses claims its K2K replicates cloud data faster and with fewer headaches than MirrorMaker2, while both stayed reliable. Commenters split: some cheer the speed and simplicity, others call it vendor spin and ask for independent tests—because fewer 3am outages is the real win.

The Kafka crowd showed up with popcorn for this one. Lenses dropped a head-to-head test claiming their K2K tool beats the old guard, MirrorMaker2 (the standard for copying data across regions) with lower lag, faster writes, and more throughput—while dodging the messy failover headaches that have haunted ops teams. In simple terms: both tools were reliable, but K2K looked speedier and simpler. Cue the comment drama.

One early voice, andmarios, waved a big “I work at Lenses” flag, which instantly triggered the classic internet split: fans grateful someone’s tackling a long‑running pain (“make the offset nightmares stop”), and skeptics calling this a polished vendor benchmark. Operators who’ve been burned by MirrorMaker2’s “offset translation” chaos (think: markers telling apps where they left off) chimed in with gallows humor—memes about a “MirrorMaker2 support group” and jokes like “EOS means Exactly Once… in my dreams.” EOS stands for “Exactly Once Semantics,” aka avoiding duplicates, and it’s a big deal in these tests.

The biggest debate: even if K2K is faster (14–32% less delay, 51–78% quicker writes), can it really simplify day‑to‑day ops? Some asked for third‑party numbers and pricing; others said they’d switch tomorrow if it means fewer 3am pages. Bottom line: this comparison lit up a community that’s deeply tired of replication drama—and hungry for a tool that just works.

Key Points

  • Cross-region replication tests compared Lenses K2K and Apache Kafka MirrorMaker2 (including AWS MSK Replicator) on Amazon MSK.
  • Both solutions achieved 100% reliability across all scenarios tested.
  • K2K showed 14–32% lower latency (e.g., 143 ms vs 166 ms baseline; 142 ms vs 209 ms EOS).
  • K2K delivered 51–78% faster producer write times and 16% higher throughput (7.81K vs 6.75K rd/s).
  • K2K achieved 5x better batching efficiency with EOS (419 KB vs 85 KB average batch size).

Hottest takes

"Disclaimer: I am part of the Lenses team" — andmarios
Made with <3 by @siedrix and @shesho from CDMX. Powered by Forge&Hive.