• High Throughput: Process millions of events per second
• Durability: Replicated, fault-tolerant message storage
• Scalability: Horizontal scaling with automatic rebalancing
• Real-Time: Sub-second message delivery
• Integration: Connect with 100+ data sources and sinks

Streaming Platform

• Publish/subscribe messaging
• Message persistence
• Stream processing
• Event sourcing
• Log aggregation

High Availability

• Multi-broker clusters
• Automatic replication
• Leader election
• Partition redundancy
• 99.99% uptime SLA

Performance

• High throughput (millions msg/sec)
• Low latency (< 10ms)
• Horizontal scalability
• Batch processing
• Compression support

Data Durability

• Configurable replication
• Message retention policies
• Log compaction
• Backup and recovery
• Cross-region replication

Security

• TLS encryption
• SASL authentication
• ACL authorization
• Audit logging
• VPC isolation

• Apache Kafka 3.6
• Apache Kafka 3.5
• Apache Kafka 3.4
• Apache Kafka 3.3

Event Streaming

• Real-time analytics
• Activity tracking
• Operational metrics
• System monitoring
• IoT data ingestion

Data Integration

• CDC (Change Data Capture)
• ETL pipelines
• Data lake ingestion
• Microservices communication
• Database replication

Log Aggregation

• Application logs
• System logs
• Audit trails
• Security events
• Performance metrics

Stream Processing

• Real-time transformations
• Aggregations
• Filtering
• Enrichment
• Complex event processing

Producer Example

Properties props = new Properties();
props.put("bootstrap.servers", "kafka.company.com:9092");
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("security.protocol", "SSL");

Producer<String, String> producer = new KafkaProducer<>(props);
producer.send(new ProducerRecord<>("my-topic", "key", "value"));

Consumer Example

Properties props = new Properties();
props.put("bootstrap.servers", "kafka.company.com:9092");
props.put("group.id", "my-consumer-group");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("security.protocol", "SSL");

KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("my-topic"));

while (true) {
    ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
    for (ConsumerRecord<String, String> record : records) {
        System.out.printf("offset = %d, key = %s, value = %s%n",
            record.offset(), record.key(), record.value());
    }
}

Components

• Brokers: Message storage and serving
• Topics: Message categories
• Partitions: Parallel processing units
• Producers: Message publishers
• Consumers: Message subscribers
• ZooKeeper/KRaft: Cluster coordination

Deployment Options

• Multi-broker clusters
• Multi-AZ deployment
• Cross-region replication
• Dedicated clusters
• Shared clusters

Automated Operations

• Cluster provisioning
• Automatic scaling
• Version upgrades
• Maintenance windows
• Health monitoring

Monitoring

• Throughput metrics
• Latency tracking
• Consumer lag
• Partition distribution
• Broker health

Scaling

• Add/remove brokers
• Partition rebalancing
• Storage expansion
• Throughput tuning

Source Connectors

• Database CDC
• File systems
• Message queues
• Cloud storage
• APIs

Sink Connectors

• Databases
• Data warehouses
• Search engines
• Cloud storage
• Analytics platforms

Stream Processing

• Stateless transformations
• Stateful operations
• Windowing
• Joins
• Aggregations

• Schema management
• Schema evolution
• Compatibility checking
• Avro, JSON, Protobuf support
• Version control

Based on:

• Cluster size (brokers)
• Storage capacity
• Throughput
• Data retention
• Support level

• 24/7 technical support
• Architecture consultation
• Performance tuning
• Migration assistance

Need real-time data streaming? Contact us to get started.