PayPay SRE Practices: Chaos Engineering & Resilience

Prerequisite: Familiarity with the concepts introduced in Part 3 — Data Layer Tidb. Review it first if the terminology in this part is unfamiliar. Answer-first: Ensuring 99.99% availability for payment systems demands proactive SRE practices and automated Chaos Engineering. Injecting synthetic latency, pod failures, and network partitions via Chaos Mesh validates microservice circuit breakers before real production incidents occur. Implementing this architecture enforces sub-50ms P99 latency guarantees, strict component isolation, and automated observability pipelines required for production-grade enterprise operations. ...

May 5, 2026 · 10 min · Lê Tuấn Anh

MCP Observability & Tracing: Auditing Control Planes

Prerequisite: Familiarity with the concepts introduced in Part 5 — Security. Review it first if the terminology in this part is unfamiliar. Part 6 — MCP Observability & Tracing: Auditing the Control Plane Answer-first: Operating Model Context Protocol (MCP) servers without telemetry logging creates compliance vulnerabilities (violating OWASP MCP08: Lack of Audit & Telemetry). Instrumenting MCP servers with vendor-agnostic OpenTelemetry (OTel) tracing captures JSON-RPC 2.0 tool execution durations, argument metadata, and error rates in real-time Prometheus dashboards. Architecting this pipeline enforces sub-50ms P99 latency guarantees, OpenTelemetry GenAI semantic conventions, and 2026 Model Context Protocol. ...

June 8, 2026 · 5 min · Lê Tuấn Anh

Production AI Observability: Go LLM Tracing with OTel

Production AI observability harness in Go leveraging OpenTelemetry GenAI Semantic Conventions (v1.42.0+). Features zero-allocation streaming LLM channel tracing with context.WithoutCancel, W3C context propagation, OTTL token cost attribution in OTel Collector, and low-cardinality Prometheus metric conversion.

August 6, 2026 · 19 min · Tuấn Anh

Production AI Observability: Building Zero-Overhead LLM Tracing & Cost Attribution with OpenTelemetry in Go

Production AI Observability: Building Zero-Overhead LLM Tracing & Cost Attribution with OpenTelemetry in Go Answer-first: Production AI observability instruments Go microservices with OpenTelemetry spans to capture LLM API latency, prompt token usage, cost metrics, and error rates in real-time. Implementing this architecture enforces sub-50ms P99 latency guarantees, zero-allocation memory pooling with Go 1.24 unique.Handle, and fault-tolerant Dapr 1.15 component orchestration for resilient production scaling. This design guarantees sub-50ms P99 latency bounds and zero-allocation memory pooling. ...

August 6, 2026 · 18 min · Vesviet Engineering Team