Gemini API × Sentry: A Production Pipeline for LLM Error Tracking and Prompt Failure Observability
Pair Sentry's error tracking with Gemini-specific failure modes so you can catch safety filter blocks, recitation rejections, empty completions, and quiet latency drift in production.
Tracing Gemini API in Production with OpenTelemetry: See Every Step of a Single Request
After three months of running Gemini API in production, plain logs stop telling you why latency, cost, or failures spike. This guide walks through wrapping Gemini in OpenTelemetry — Python and Node.js code, GenAI semantic conventions, sampling, and Grafana/Datadog wiring — so you can see the full anatomy of every request.
Gemini API × Langfuse — A Production Playbook for LLM Observability
A practical, production-grade guide to wiring Gemini API into Langfuse — tracing architecture, cost attribution, LLM-as-Judge on live traffic, PII masking, and sampling — with runnable code.
to Production Architecture for Gemini API 2026— Design Patterns for Building Scalable, Reliable AI Systems
A comprehensive guide to production-grade design patterns for Gemini API. Covers resilient API clients, multi-layer caching, multi-tenant design, observability, and cost control with complete code examples.
Gemini API × Spring Boot Enterprise Production Guide: Spring AI, Multi-Tenancy, Security & Observability
A complete guide to running Gemini API in production with Spring Boot. Covers Spring AI framework integration, multi-tenant architecture, API key management, async processing, observability with Micrometer/OpenTelemetry, and enterprise testing strategies.
Gemini API Observability in Production — Logging, Monitoring, and Cost Tracking Patterns
Learn how to build a robust observability stack for production Gemini API deployments. Covers structured logging, token usage tracking, latency monitoring, and cost optimization dashboards with full implementation code.