Home/AI Observability & LLMOps/Databricks (MLflow)

Databricks (MLflow)

MLOps Extended#7 of 22 in AI Observability & LLMOps
83%
COVERAGE
Created MLflow (most adopted ML lifecycle tool); MLflow 3.0 with GenAI tracing, LLM judges, prompt mgmt; Unity Catalog governance; Inference Tables; Lakehouse Monitoring; 10K+ customers
Tracing
4 full, 0 partial of 4
Prompt/Completion Tracing
Record the complete lifecycle of every LLM request — prompts, completions, tool calls, retrieval steps — with structured parent-child span relationships.
Full
Latency Monitoring
Track response times at each pipeline step with p50/p95/p99 breakdowns and historical trends.
Full
Multi-model Support
Trace across multiple LLM providers and frameworks (LangChain, LlamaIndex, Vercel AI SDK) with auto-instrumentation.
Full
Agentic Observability
Dedicated tracing for multi-step agent workflows — tool call visualization, decision tree inspection, agent-specific metrics, and multi-turn threading.
Full
Cost & Perf
1 full, 2 partial of 3
Cost Tracking
Calculate per-request and aggregate costs. Attribute spend to teams, features, users, or projects.
Partial
Token Analytics
Monitor input/output token counts, context window utilization, and token efficiency.
Partial
Alerting & SLOs
Configure alerts for latency spikes, error thresholds, cost overruns, and quality degradation.
Full
Evaluation
4 full, 1 partial of 5
Built-in Evals
Pre-built evaluators for hallucination, relevance, toxicity, faithfulness, coherence.
Full
Custom Evals
Custom evaluation metrics, LLM-as-a-judge prompts, code-based scorers, domain-specific criteria.
Full
User Feedback
Collect user feedback (thumbs up/down, ratings) linked to specific traces.
Full
RAG-specific Metrics
Specialized metrics for retrieval-augmented generation: context relevance, groundedness, answer faithfulness, retrieval precision.
Partial
Annotation & Labeling
Annotation queues, human-in-the-loop review workflows, SME feedback collection, and golden dataset creation from production traces.
Full
Data & Exp
3 full, 1 partial of 4
Dataset Mgmt
Create, version, and manage evaluation datasets from production traces or manual curation.
Full
A/B Testing
Run experiments comparing prompts, models, or configs against datasets with statistical rigor.
Full
Playground
Interactive environment to test prompts, replay failed traces, and iterate on configurations.
Partial
Prompt Management
Version control, deploy, cache, and collaboratively iterate on prompts as first-class assets. Track which prompt version produced which output.
Full
Operations
1 full, 3 partial of 4
Drift Detection
Detect changes in model behavior, output quality, or input distribution over time.
Full
Self-hosted
Deploy on your own infrastructure for data residency, compliance, and air-gapped environments.
Partial
OpenTelemetry Native
Built on OpenTelemetry standards vs proprietary instrumentation. Prevents vendor lock-in and exports traces to any compatible backend.
Partial
Guardrails Integration
Built-in or pluggable content safety, PII detection, toxicity filtering, and output validation within the observability pipeline.
Partial
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