Real-Time Systems
11 live exchange feeds. Sub-15ms tick-to-database. 24/7 operation.
WebSocket infrastructure, event-driven pipelines, high-availability architecture, and low-latency processing for systems where stale data is a product failure. We run market data ingest from OKX, Binance, Coinbase, Kraken, and 7 other exchanges simultaneously with sub-50ms tick latency into ClickHouse.
< 50ms
Tick-to-database ingest latency
11
Live exchange feeds in simultaneous operation
24/7
Continuous operation without scheduled downtime
METRICS
By the numbers
< 50ms
Tick-to-database ingest latency
1M+
Events/sec handled per core
100%
Infrastructure code ownership
3 wks
Avg time to production
BUDGET
Latency budget breakdown, tick to database
End-to-end latency is the sum of each hop. We budget every hop and measure each one in production. When a percentile drifts, the alert points at the specific stage, not the whole pipeline.
| Hop | p50 | p95 | p99 | Failure mode |
|---|---|---|---|---|
| Exchange WebSocket | 8ms | 15ms | 32ms | Network jitter or upstream throttle. |
| Tick normalization (Rust) | 0.4ms | 1.2ms | 3.0ms | Memory pressure or allocator contention. |
| Redis Stream XADD | 1.5ms | 4ms | 9ms | Persistence fsync or memory eviction. |
| Consumer group XREAD | 0.8ms | 2ms | 5ms | Consumer lag from slow downstream. |
| ClickHouse INSERT batch | 5ms | 12ms | 28ms | Disk pressure or merge backpressure. |
| End-to-end (tick to ack) | 18ms | 38ms | 70ms | Tail latency dominated by ClickHouse merge. |
CAPABILITIES
What we build
01
WebSocket infrastructure
Persistent connections with reconnect logic, exponential backoff, and per-feed health monitoring. Each exchange feed runs as an isolated Rust process under PM2 supervision. A feed failure restarts in under 5 seconds without impacting the other 10 feeds.
02
Event-driven processing
Redis Streams consumer groups for at-least-once delivery with explicit ACK. Events are processed in the order received within a symbol partition. Consumer lag alerts fire if any consumer group falls more than 5 seconds behind the producer.
03
High availability and graceful degradation
Systems designed to degrade gracefully, not hard-crash. If the primary ClickHouse node is unreachable, the ingest buffers to Redis. When the node recovers, it replays from the Redis buffer and reconciles row counts before resuming normal operation.
04
Low-latency hot paths
Critical processing paths written in Rust: tick normalization, deduplication on composite keys, and signal scoring. Rust hot loops handle 1M+ events per second per core without garbage collection pauses. Slower analytical operations remain in Python where development speed matters more than microseconds.
TECHNOLOGY
Tech stack
APPLICATIONS
Where this applies
- 01Crypto exchange feed aggregation. 11 exchanges, sub-50ms tick processing, 723M+ rows in ClickHouse. Each feed is an independent Rust binary with its own reconnect state, deduplication window, and row-count audit published to a monitoring table every 60 seconds.
- 02Real-time portfolio risk monitor. A fund manager needed live drawdown, VaR, and concentration alerts as trades were booked. We built a streaming aggregation layer that recomputes portfolio-level risk metrics within 200ms of any position change.
- 03IoT sensor data ingestion. A manufacturing client pushed 40,000 sensor readings per second from 200 production line devices. We built a MQTT-to-Redis-to-ClickHouse pipeline that maintained sub-100ms ingest latency at peak load with zero data loss over a 30-day observation window.
- 04Live notification and alerting infrastructure. A SaaS platform needed per-user alerts that triggered on thresholds computed over streaming data. We built a WebSocket fan-out layer with Redis pub/sub that delivers alerts to active browser sessions within 50ms of the threshold crossing.
PROCESS
How we deliver
Every engagement follows the same three phases. No surprises, no scope creep.
Latency Budget + Load Model
We define the end-to-end latency budget, peak event rate, and backpressure strategy before architecture decisions are made. Failure modes are designed in from the start.
Stream Architecture + Backpressure Design
Event pipeline built with bounded queues, consumer groups, and explicit acknowledgment. Load tests verify the system degrades gracefully at 3x expected throughput.
Production Cutover + SRE Handoff
Live switchover with latency percentile dashboards, dead-letter queue alerts, and a lag recovery runbook. Full infrastructure and code ownership transferred.
GET STARTED
Ready to build?
Most projects ship in 2 to 4 weeks. Fixed price. Full IP transfer.