Results for “model-observability”

Projeta métricas, logs, traces, dashboards, alertas e SLO com Prometheus, Grafana, Loki, Tempo, Mimir, Zabbix e Alertmanager, incluindo consultas PromQL e boas práticas de alertas.

Self-hosted observability platform for LLM applications, providing tracing, evaluation, datasets, experiments, and real-time monitoring to debug and improve AI systems.

Trace, evaluate, and monitor LLM applications with an open-source observability platform.

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Implements a complete observability stack with Prometheus metrics, Grafana dashboards, Jaeger distributed tracing, and structured logging, including heartbeat-based absence detection for scheduled jobs on Google Cloud.

Adds logging, metrics, tracing, and alerting to make production behavior visible and diagnosable.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Debug, evaluate, and monitor LLM applications with tracing, datasets, and built-in evaluators.

Design production-ready observability strategies combining metrics, logs, and traces, including SLI/SLO design, golden-signals monitoring, and alert optimization.