Scaling Observability: Designing a High-Volume Telemetry Pipeline Series

A scalable pipeline architecture consists of data collection, processing, storage, and querying stages, with key design principles including horizontal scaling, stateless processing, and backpressure management.

Part 2 covers scaling telemetry: use downsampling for metrics, head/tail-based sampling for traces, and schema-aware parsing for logs.

Part 3 explores building scalable telemetry pipelines with agents, batching, Kafka buffering, and backpressure control for resilient observability.

Part 4 explores horizontally scaling telemetry pipelines, ensuring high availability, managing costs, and applying lessons from production deployments.