Posted by elffjs 8 hours ago
My bigger concern would be their increasing grip on a lot of the market, and eventually becoming a monopoly (or part of the big tech "duopoly")
At this point this has already effectively happened. The average person doesn't realize the extent of it, because the products Cloudflare builds are inherently transparent to the average consumer.
The question is less about "vibe coding" the product, and more about how their acquired teams function. For most products they have released so far, they are backed by a company they acqui-hired. They will usually rebrand the product and absorb the team.
You would not be surprised if this release was from a product for a startup company rather than a large enterprise company.
Cloudflare hired a bunch of folks for sure, but they also fired a lot of folks. What they are doing these days is building products by buying out entire companies, giving them nearly independent authority to build a product like they would build a company.
There was just more news about it than with other companies ( I think they let go about 2 k. People a year ago).
( Not saying it's good, just a little perception balance)
We went with a simpler and more user friendly consume API, that also allows much higher levels of read parallelism (particularly important if you're using something like Workers, which parallelize well but aren't very powerful individually).
But we know many companies are invested in the Kafka ecosystem, and we want to provide an easy on (and if necessary, off) ramp for them.
Compared to self-hosted or cloud-hosted Kafka (e.g., Amazon MSK or Confluent), K2 is much cheaper, and fully serverless. There are no clusters to manage or scale, and consistent performance even as you vastly increase the amount of data.
The main downside is produce (and end to end) latency is higher (around 1s p99) than systems that rely on local disk replication, like Kafka.
So it's great if you're trying to move a huge amount of data around, or for use cases where cost is more important than latency.
In our case BLOB and large document transfers were handled in parallel, merging them together through object storage is a highly appealing package. Great work!
You need... | Use
-------------------------------------------------------|-------
“Make sure this job gets done” | Queue
retries / dead-letter handling | Queue
delayed jobs | Queue
distribute jobs among workers | Queue
“Record that this event happened” | K2
multiple independent systems reading the same events | K2
replay old events | K2
ordered event streams | K2
Kafka-like architecture | K2