Infrastructure

Managed Kafka

Managed Kafka

Enterprise-grade managed Apache Kafka service for building real-time streaming data pipelines and event-driven applications.

Overview#

  • 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

Key Features#

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

Supported Versions#

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

Use Cases#

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

Getting Started#

Producer Example#

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Properties props = new Properties();
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props.put("bootstrap.servers", "kafka.company.com:9092");
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props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
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props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
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props.put("security.protocol", "SSL");
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Producer<String, String> producer = new KafkaProducer<>(props);
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producer.send(new ProducerRecord<>("my-topic", "key", "value"));

Consumer Example#

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Properties props = new Properties();
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props.put("bootstrap.servers", "kafka.company.com:9092");
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props.put("group.id", "my-consumer-group");
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props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
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props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
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props.put("security.protocol", "SSL");
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KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
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consumer.subscribe(Arrays.asList("my-topic"));
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while (true) {
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    ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
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    for (ConsumerRecord<String, String> record : records) {
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        System.out.printf("offset = %d, key = %s, value = %s%n",
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            record.offset(), record.key(), record.value());
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    }
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}

Architecture#

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

Management Features#

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

Kafka Connect#

Source Connectors#

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

Sink Connectors#

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

Kafka Streams#

Stream Processing#

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

Schema Registry#

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

Pricing#

Based on:

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

Support#

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

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