LLM observability meets application-level visibility.
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Arize Phoenix is an excellent LLM observability framework. 40+ auto-instrumentations, best-in-class evaluation tools, and a strong open-source community. We respect that depth. This page is an honest look at where IAPM takes a different approach, where Phoenix excels, and how the two can work together.
LLM performance in the context of your entire application stack
Best-in-Class LLM Evaluation, Zero Application Context
When your LLM latency spikes, where is the bottleneck?
- 40+ auto-instrumentations covering OpenAI, Anthropic, LangChain, LlamaIndex, and more. Phoenix delivers deep LLM-specific visibility.
- But LLM calls do not execute in a vacuum. They depend on API gateways, vector databases, embedding services, and the application underneath.
- When your RAG pipeline slows down, is it the model, the retrieval layer, the database feeding context, or a noisy neighbor? Phoenix cannot answer that because it only sees the LLM layer.
One spatial view. Full application context. Faster resolution.
See Your LLM Calls in Full System Context
Topology as your primary investigation surface.
- 3D spatial topology: Your LLM services, the APIs that call them, the vector databases they query, and the relationships between all of them.
- When something breaks, you see it in context: which service is affected, what it depends on, where the problem propagates.
- No context switching between your LLM tracing tool and your application monitoring. One environment. Application-level visibility.
Zero proprietary agents. Full OTel ecosystem.
Architecture: How We Differ
Application-level correlation vs LLM-only tracing.
IAPM provides application observability: distributed tracing, metrics, logs, and LLM observability in a single spatial environment. When your LLM latency spikes, IAPM shows you whether the bottleneck is the model provider, your API gateway, the vector database, or an upstream dependency.
Phoenix shows you the LLM call. IAPM shows you the LLM call in the context of the entire request lifecycle and the application dependencies around it.
| Aspect | IAPM | Arize Phoenix |
|---|---|---|
| Scope | Application monitoring (APM) + LLM observability | LLM observability only |
| Instrumentation | Standard OpenTelemetry SDKs (all signals) | OpenTelemetry-based (LLM spans via OpenInference) |
| LLM Auto-Instrumentation | OpenTelemetry GenAI semantic conventions | 40+ auto-instrumentations (OpenInference) |
| Visualization | 3D spatial topology + web dashboards | Trace tree views, evaluation dashboards |
| Service Topology | Auto-discovered 3D service map | No service topology |
| Application Metrics | Application metrics via OTel correlated with traces | No application-level metrics |
| LLM Evaluation | Evaluation via OTel-compatible pipelines | Best-in-class: hallucination, toxicity, relevance, custom evals |
| Cross-Signal Correlation | Traces + metrics + logs unified in spatial view | LLM traces only |
Tessa fixes code. You review it. You own it.
| Capability | Tessa (IAPM) | Arize Phoenix |
|---|---|---|
| AI Diagnosis | Cross-signal anomaly detection with spatial context | No AI diagnosis (manual investigation) |
| Codebase Access | Full workspace: read, search, rename, modify | No codebase access |
| Code Fixes | Fixes code in your workspace. You review, you own it. | No code changes |
| Root Cause Analysis | Application-level: LLM + app + dependencies | LLM layer only |
| Accountability Model | Human on the loop | Manual debugging by engineer |
AI: Tessa vs Manual Investigation
Human on the loop.
Tessa accesses your codebase workspace, diagnoses from 3D topology, and makes the fix. You review, you own it. When your RAG pipeline degrades, Tessa does not just show you the LLM trace. She correlates the latency spike with the vector database query time, checks the application metrics, identifies the root cause, and proposes a code fix.
Phoenix gives you excellent LLM trace visibility to investigate manually. Tessa closes the gap between "I see the problem" and "the fix is ready for review."
One platform for LLM + application monitoring. One price.
Pricing: Application Observability Value
One platform vs LLM tool + APM tool + ops cost.
- One platform, not three: IAPM includes LLM observability, APM, and AI diagnosis. Phoenix covers the LLM layer only.
- No tool sprawl: Avoid managing separate tools for LLM tracing and APM. One bill. One UI. Full correlation.
- Predictable pricing: Nodes x tier price = monthly cost. No per-trace or per-evaluation charges.
- AI included: Tessa is included in every paid tier. No separate AI add-on to budget for.
| Capability | IAPM | Arize Phoenix |
|---|---|---|
| LLM Observability | Included | Free (OSS self-hosted) / AX Pro from $50/mo |
| Application Monitoring (APM) | Included | Not available (requires separate tool) |
| APM / Distributed Tracing | Included | Not available (requires separate tool) |
| AI Assistant | Included (Tessa) | Not available |
| 3D Spatial Topology | Included | Not available |
| Application Observability Total | $45/node/month (Analyze) | Phoenix + APM tool = multiple bills |
IAPM pricing from immersivefusion.com/pricing. Arize Phoenix is open source; Arize platform pricing varies by plan. Verify current pricing at arize.com/pricing. All prices USD.
Keep Phoenix for evals. Add IAPM for application context.
Already Using Phoenix? Add Application Context.
OpenTelemetry makes it simple.
- Keep Phoenix for evals: If you love Phoenix's evaluation framework, keep using it. IAPM adds the application monitoring layer Phoenix does not cover.
- Zero re-instrumentation: Phoenix is built on OpenTelemetry via OpenInference. Your existing OTel instrumentation works with both.
- Run both side by side: Compare the experience. When you see the value of correlating LLM performance with application health, you will understand why application-level context matters.
- Exit guarantee: If IAPM is not right for you, change one endpoint URL. Your instrumentation stays exactly the same.
Dual-Destination Collector Config
exporters:
otlp/iapm:
endpoint: "https://otlp.iapm.app"
headers:
API-Key: "YOUR-API-KEY"
otlp/phoenix:
endpoint: "localhost:4317"
service:
pipelines:
traces:
exporters: [otlp/iapm, otlp/phoenix]
metrics:
exporters: [otlp/iapm]Standard OTel Collector config. LLM traces go to both. Application metrics go to IAPM.
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