1. The Three Pillars of Observability
Distributed Tracing: Visualizing request flow across 20 microservices with unique Trace IDs and Span IDs. OpenTelemetry (OTel) provides vendor-neutral instrumentation.
Metrics: High-cardinality time-series data (Prometheus / Datadog) tracking throughput, error rates, and CPU utilization.
Structured Logs: JSON formatted log streams aggregated in Elasticsearch / ClickHouse with correlated Trace IDs.
2. The RED and USE Metrics Frameworks
RED Method (for Request-Driven Services): Rate (requests per second), Errors (failed requests), Duration (latency distribution).
USE Method (for Resources: CPU, Memory, Disk): Utilization (time resource was busy), Saturation (queued work waiting for resource), Errors (error count).
3. SLI, SLO and Error Budgets
Define realistic Service Level Indicators (SLIs) and Service Level Objectives (SLOs). For example: '99.9% of payment authorizations complete in <500ms over a 30-day window.' The remaining 0.1% is the team's Error Budget for shipping features quickly.
Model this architecture on the HLDForge Canvas
Turn static box diagrams into living, collaborative systems. Drag and drop microservices, Kafka clusters, and cache tiers. Run automated SPOF detection and STRIDE threat modeling in real time.
Written by HLDForge Architecture Team
Staff Observability Architect
The HLDForge Architecture Team publishes practical engineering guides, real-world case studies, and high-concurrency blueprints to help engineers build scalable and fault-tolerant software.