AI tools for “observability”
83 results (tools & skills) · 240 ms · understood as by meaning
MLflow tracing and observability on Databricks. Use when getting started with MLflow, instrumenting GenAI apps and agents, retrieving and analyzing traces, debugging chat sessions, or querying aggregate trace metrics on…
…a new project from scratch — questions about Datadog observability products (logs, metrics, APM, traces, monitors, dashboards), working inside an existing project, deploying, publishing, auth, or…
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT…
…already has. Use when the user asks to add Lens, tracing, observability, or per-turn traces to their agent, or asks why their Lens traces are…
…traces, logs, and metrics to DataRobot for monitoring, observability, and governance. Use when the user says "add tracing/observability/monitoring to my agent", wants to instrument an existing agent project in…
…wiring. Use when the user asks to add tracing, observability, or evaluation to an agent or LLM app running on…
…IoC hunting in logs/spans (dt-sec-ioc-hunting), K8s observability…
…React Native app", "integrate Dynatrace RN", "mobile observability React Native", "react-native-plugin", "dynatrace react native", "add Dynatrace to Expo", "instrument Expo app", "Dynatrace Expo setup", "React…
…Flutter app", "integrate Dynatrace Flutter", "mobile observability Flutter", "dynatrace_flutter_plugin", "Flutter session replay", "dynatrace_flutter_plugin_replay". Do NOT use for: querying Flutter RUM data (use…
…spans into Dynatrace", "onboard this agent app to AI Observability". Do NOT use for analyzing telemetry from an already-instrumented app (use dt-obs-genai) or for languages other than…
LangSmith Observability gives complete visibility into agent behavior with tracing, real-time monitoring, alerting, and high-level insights into usage.
A concise feature matrix for deciding which PlanetScale safety, observability, and automation recommendations apply by engine.
Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user LLM cost, user-level cost drivers, or patterns behind high AI…
…continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces…
…distributions, trace IDs, or span attributes — not AI observability traces or product logs. Uses posthog:apm-service-health, posthog:query-apm-spans, posthog:apm-trace-get, posthog:apm-spans-sparkline,…
Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.
Add PostHog AI Observability to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK…
Investigate AI observability evaluations — `hog` (deterministic code-based), `llm_judge` (LLM-prompt-based), and `sentiment` (user-message sentiment). Find existing evaluations, inspect their configuration, run them…
Set up and troubleshoot Pydantic Logfire frontend observability and session replays in JavaScript/TypeScript browser applications. Use for browser errors, RUM, Web Vitals, replay recording, privacy controls, or reducing…
…Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly,…