LLM observability dashboard examples

Here are some LLM observability dashboard examples you can use as inspiration, organized by what teams typically want to monitor.

1) Model performance dashboard

Tracks whether the model is doing its job well.

Typical charts/KPIs

• Request volume over time
• Average latency / p95 / p99 latency
• Error rate
• Token usage per request
• Cost per request / per user / per endpoint
• Success rate by model version
• Output quality score
• Human feedback score

Example widgets

• Line chart: p95 latency by hour
• Stacked bar: requests by model
• Table: top failing prompts
• KPI cards: avg cost, error rate, throughput

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2) Prompt observability dashboard

Useful for debugging prompt behavior and regressions.

Typical charts/KPIs

• Prompt template version usage
• Prompt length distribution
• Completion length distribution
• Prompt category / route
• Regression rate after prompt changes
• Frequency of prompt failures
• Top prompt variants by quality score

Example widgets

• Heatmap: prompt version vs quality
• Table: prompt, output, feedback, latency
• Trend line: quality before/after prompt update

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3) Retrieval-Augmented Generation (RAG) dashboard

For systems using search/vector retrieval.

Typical charts/KPIs

• Retrieval hit rate
• Context utilization
• Relevant document rate
• Top-k retrieval scores
• Citation accuracy
• Hallucination rate
• Query-to-document match quality
• Chunk size vs answer quality

Example widgets

• Funnel: query -> retrieved docs -> grounded answer
• Bar chart: documents cited most often
• Table: queries with no relevant retrieval
• Line chart: grounded answer rate over time

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4) Safety and policy dashboard

Monitors harmful or non-compliant outputs.

Typical charts/KPIs

• Toxicity rate
• PII leakage incidents
• Policy violation rate
• Jailbreak attempts
• Refusal rate
• Unsafe content categories
• Moderation false positives/negatives

Example widgets

• Pie chart: violation types
• Trend line: jailbreak attempts per day
• Table: flagged conversations
• KPI: PII leakage = 0

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5) Cost and usage dashboard

Important for finance, ops, and capacity planning.

Typical charts/KPIs

• Daily/monthly token consumption
• Cost by team / app / endpoint
• Cost by model
• Average tokens per conversation
• Peak usage windows
• Rate limit events
• Cache hit rate

Example widgets

• Area chart: daily spend
• Bar chart: cost by model
• Table: top expensive requests
• KPI cards: monthly burn, cache savings

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6) User experience dashboard

Focuses on product outcomes.

Typical charts/KPIs

• Conversation success rate
• User retention after AI interaction
• Time to first useful response
• User satisfaction score
• Escalation to human rate
• Re-ask / retry rate
• Abandonment rate

Example widgets

• Funnel: opened chat -> asked question -> accepted answer
• Cohort chart: retention by week
• Trend line: abandonment rate

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Sample dashboard layout

A practical LLM observability dashboard often has:

Top row: key health metrics

• Requests
• Errors
• Latency p95
• Cost
• Satisfaction
• Safety violations

Middle row: trends

• Traffic over time
• Latency over time
• Cost over time
• Quality score over time

Bottom row: debugging tables

• Slowest requests
• Most expensive requests
• Failed prompts
• Flagged outputs
• Low-score conversations

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Example “single pane of glass” dashboard sections

If you want a concise dashboard structure:

1. Overview

   • Traffic, latency, cost, quality, safety

2. Quality

   • Human feedback, eval scores, hallucination rate

3. RAG

   • Retrieval quality, citations, grounding

4. Safety

   • Toxicity, PII, policy issues

5. Debugging

   • Request traces, prompt/completion logs, errors

6. Cost

   • Token usage, spend by model/app/team

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Example metrics to include in traces

For each request span, capture:

• Request ID
• User/session ID
• Prompt template/version
• Model name/version
• Input tokens
• Output tokens
• Latency
• Temperature/top_p
• Retrieved documents
• Safety flags
• Feedback score
• Final outcome

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Example tools commonly used

Popular observability stacks for LLMs include:

• Langfuse
• Arize Phoenix
• Weights & Biases
• Datadog
• OpenTelemetry
• Helicone
• WhyLabs
• Grafana + Prometheus + Loki
• TruLens
• Honeycomb

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If you want, I can also give you:

1. a wireframe/mockup of an LLM dashboard,
2. a Grafana-style metric layout, or
3. a dashboard example for RAG / agents / chatbots.