// Topics / Observability

Observability

    Testing AI in Production: Shadow Mode, Canaries, Holdouts Offline evals aren't enough. How I test AI features in production with shadow mode, canaries, holdouts, and automatic fallback, with Go code. testing ai production AI Observability: Green Dashboards, Wrong Answers Uptime monitoring won't show an AI service returning confident garbage. The five signals I track instead: traces, quality, cost per outcome, safety, ops. observability ai production LLM Observability: Monitoring Quality, Not Just Uptime Traditional monitoring says the service is up. It won't tell you the model started returning garbage last Tuesday. How to actually observe LLM systems. observability llm ai OpenTelemetry in Late 2021: What's Ready and What's Not OpenTelemetry in late 2021: tracing is ready, metrics are close, logs are not. A Collector-first adoption path with Go code, sampling, and naming rules. observability go Observability-Driven Development: Instrument Before You Ship Observability-driven development without the jargon: structured logs, RED metrics, traces, and SLO alerts that ship with each feature. observability development reliability eBPF for Observability: Interesting, but I'm Not Sold Yet eBPF gives kernel-level observability without kernel modules. Kernel version gaps, patchy BTF support, and scarce expertise make it hard to run today. observability engineering performance Observability for Small Distributed Teams: A Minimal Stack Most observability advice targets 500-engineer orgs. For a small distributed team: structured logs, a request_id, one dashboard per service, few alerts. observability distributed-systems devops SLOs and Error Budgets That Change How Teams Ship Most SLOs are dashboards nobody acts on. Pick indicators that reflect real users, set targets from data, and make error budgets change how your team ships. reliability observability engineering Monitoring vs Observability: Lessons From a Silent Outage After an outage our dashboards couldn't explain, I rebuilt a fintech startup's telemetry around metrics, logs, and traces tied together by request IDs. observability devops distributed-systems Observability vs Monitoring: Why Dashboards Aren't Enough Monitoring answers questions you predicted. After splitting into microservices, we needed structured logs, trace IDs, and tracing to debug what broke. observability devops distributed-systems Production Monitoring: Why We Deleted 42 Grafana Panels We cut 47 Grafana panels to five metrics and three paging alerts. The production metrics that matter for a startup backend, and how to prune the rest. observability devops production Log Aggregation at Scale: ELK vs Alternatives ELK is powerful and a second full-time job. What running it at a mobility startup taught me, and the hosted or simpler options I'd pick instead. observability databases devops