Yes. At the time of writing (June, 2017) the following companies have confirmed they are using Sarama: Shopify, IBM, Heroku, VividCortex, Atomx, keda.sh.

I understand that there are other major companies using it in production too. If you work for such a company and file a ticket to let me know, I'll list it here.

Use Client.GetOffset().

Starting in Sarama v1.11.0, this method will automatically use Kafka's new precise timestamp lookup if your Kafka version (as provided by Config.Version) is at least 0.10.1. Otherwise, the method will fall back to the old API which returns only a very approximate value.

No. Kafka Streams is a separate library for stream processing backed by Kafka. It is not a feature of Kafka proper and not something that Sarama intends to support. If somebody wanted to implement streams on top of Sarama, it should live in a separate package.

SSL is supported. There are a couple of potential causes for SSL connection problems, but if everything else is working (you can connect on the non-SSL port, and other SSL clients can establish a connection) then chances are you have a cipher problem. When creating the keystore on the server, you need to pass the -keyalg RSA argument or else the Kafka broker will operate using an extremely limited set of ciphers, none of which are supported by Golang. See #643 for more details.

Yes, sarama supports consumer groups as of v1.19.0.

Sarama will never put a nil message on the channel. If you are getting nils then the channel has been closed (a receive from a closed channel returns the zero value for that type, which is nil for pointers).

The channel will normally be closed only when the PartitionConsumer has been shut down, either by calling Close or AsyncClose on it. However, the PartitionConsumer may sometimes shut itself down when it encounters an unrecoverable error; in this case you will get an appropriate error on the Errors channel, and it will also log a message to sarama.Logger that looks something like: consumer/TOPIC/PARTITION shutting down because REASON.

You don't. Kafka doesn't have the concept of a topic or partition "ending"; it was designed for systems where new messages are constantly arriving and so the question is meaningless. There are, however, a few ways to approximate this, both with some obvious drawbacks:

• Wait for the configured Consumer.MaxWaitTime time to pass, and if no messages have arrived within that time then assume you're done.
• Use Client.GetOffset to get the last offset when you start, and consume up until that offset is reached.

It's not. First, Go uses a garbage-collector, so most memory will be automatically reclaimed unless there's a reference to it hanging around somewhere by accident. Second, the structure of the consumer is remarkably simple and there's basically nowhere for an incorrect reference to sneak in.

Common explanations for what looks like a leak in the consumer but isn't:

• Go's garbage collector returns memory to the Operating System very rarely, preferring to reuse it internally first. This means that external memory measurements may not go down immediately even when the memory is no longer used.
• If you have a lot of memory to spare, Go will use it aggressively for performance. Just because your program is currently using many GiB of memory, doesn't mean it won't run just fine on a more constrained system.
• The consumer does use a lot of goroutines, but not an unbounded number. Expect a goroutine for every partition you are consuming plus a few on top; this can be thousands for a process consuming many topics each with many partitions.
• The leak is in your code instead: if you have code that permanently stores a reference to the ConsumerMessages coming out of the consumer, that memory will effectively leak and the profiler will point to the location in Sarama where it was allocated.

If you're going to file a ticket claiming there's a leak in the consumer, please provide a detailed profile and analysis of exactly where/how the leak is occurring.

Pretty fast, although it depends heavily on your specific configuration, network, hardware, etc. This benchmark is a few years old now but claims to have been able to produce nearly 100k messages per second. If you need a more concrete guarantee for a given scenario, you'll have to run your own benchmark.

Yes. Like Kafka, Sarama guarantees message order consistency only within a given partition. Order is preserved even when there are network hiccups and certain messages have to be retried.

No. If five messages (1,2,3,4,5) are fed to the producer in sequence, it is possible (though rare) that the Kafka cluster will end up with messages 1, 2, 4, and 5 in order, but not message 3. In this case you will receive an error for message 3 on the Errors() channel.

Yes it is, and even encouraged in order to get higher throughput.