How can Kafka be handled to process up to 100 thousand messages per second?

To ensure Kafka processing of up to 100,000 messages per second, the following approaches can be used:

• Parallelism and scaling: increase the number of partitions in topics and the number of consumers in a group to distribute the load.
• Producer optimization: use asynchronous message sending, batching, and data compression.
• Broker configuration: increase the number of brokers, configure memory and disk subsystem parameters for high throughput.
• Use of efficient clients: in Go, use high-performance libraries such as segmentio/kafka-go or confluent-kafka-go.
• Monitoring and tuning: constantly monitor metrics such as delays, throughput, and errors, and adjust configurations accordingly.

Example of creating multiple consumers for parallel processing:

for i := 0; i < numConsumers; i++ {
    go func(id int) {
        reader := kafka.NewReader(kafka.ReaderConfig{
            Brokers: []string{"localhost:9092"},
            Topic:   "topic",
            GroupID: "group",
        })
        defer reader.Close()

        for {
            m, err := reader.ReadMessage(context.Background())
            if err != nil {
                log.Println(err)
                continue
            }
            processMessage(m)
        }
    }(i)
}