Real-time Data Processing

Our real-time processing systems typically achieve sub-50ms end-to-end latency for most use cases. For high-frequency trading and ultra-critical applications, we can achieve sub-10ms latency. The actual latency depends on factors like data complexity, processing requirements, and network topology. We provide detailed latency analysis and optimization recommendations during the design phase.

We implement exactly-once processing semantics using distributed transactions, idempotent operations, and checkpoint mechanisms. Our systems use Apache Kafka's transactional guarantees, Apache Flink's checkpointing, and custom deduplication logic to ensure no data is lost or processed multiple times. We also implement comprehensive monitoring to verify processing guarantees in real-time.

Our systems include automatic failover mechanisms with hot standby replicas that take over within seconds. We implement persistent state management with regular checkpoints, so processing can resume from the last known good state. Circuit breakers prevent cascade failures, and our monitoring systems provide instant alerts. Typical recovery time is under 5 seconds with zero data loss.

Yes, our systems are designed to handle millions of events per second through horizontal scaling and distributed processing. We use partitioning strategies, parallel processing, and load balancing to distribute the workload across multiple nodes. Our largest deployment currently processes over 10 million events per second with consistent sub-50ms latency. We can scale further based on your specific requirements.

We implement complex event processing (CEP) using advanced pattern matching algorithms, time-window operations, and state machines. Our systems can detect complex patterns across multiple event streams, correlate events based on time and content, and trigger actions based on business rules. We support temporal patterns, sequence detection, anomaly identification, and statistical analysis in real-time.

We provide comprehensive real-time monitoring including processing latency, throughput rates, error rates, and business KPIs. Our dashboards show live metrics with customizable alerts for threshold breaches. We monitor system health, resource utilization, and data quality in real-time. Automated alerts are sent via email, SMS, Slack, or webhook integrations. Historical data is retained for trend analysis and capacity planning.