skills.rest
Blackkadder
BlackkadderCOMMUNITY
Explore all skills by this author →
GitHub

retrieving-mlflow-traces

Retrieve MLflow traces by ID or filtered criteria via CLI or Python API.

Updated Mar 19, 2026
Search Tags:#debugging#cli#filters#traces#mlflow#python-api
One-click install
npx skills add https://github.com/Blackkadder/databricks-apps-and-agents-workshop --skill retrieving-mlflow-traces-blackkadder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retrieving-mlflow-traces
Source: https://github.com/Blackkadder/databricks-apps-and-agents-workshop/tree/main/.claude/skills/retrieving-mlflow-traces
Command: npx skills add https://github.com/Blackkadder/databricks-apps-and-agents-workshop --skill retrieving-mlflow-traces-blackkadder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Retrieves MLflow traces using CLI or Python API. Use when the user asks to get a trace by ID, find traces, filter traces by status/tags/metadata/execution time, query traces, or debug failed traces. Triggers on "get trace", "search traces", "find failed traces", "filter traces by", "traces slower than", "query MLflow traces".

Core Features & Use Cases

  • Single fetch by trace ID with mlflow traces get
  • Search traces by run ID, session, user, status, time range, etc., using mlflow traces search
  • Retrieve structured trace data including TraceInfo and Spans, with filters and sorting
  • Use Case: Debug MLflow experiments by locating and inspecting relevant traces to diagnose performance issues or errors

Quick Start

Fetch a specific trace by ID with mlflow traces get --trace-id <trace_id>.

Frequently Asked Questions about retrieving-mlflow-traces

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve MLflow traces by trace ID?▼

To retrieve MLflow traces by trace ID, use the mlflow traces get CLI command with the --trace-id flag. This provides direct access to structured trace data including TraceInfo and Spans for debugging or auditing runs.

Can I search MLflow traces by status, tags, or execution time?▼

Yes, you can search MLflow traces by status, tags, metadata, execution time, run ID, session, user, or time range using the mlflow traces search command, enabling multi-criteria filtering across experiments.

What is the best way to debug failed MLflow traces across multiple experiments?▼

The best way to debug failed MLflow traces is to search and filter traces by error status across runs and experiments using the CLI or Python API, then inspect the TraceInfo and Spans to diagnose errors or performance issues.

Does this MLflow traces retrieval skill work with the Python API as well as the CLI?▼

Yes, MLflow traces retrieval works with both the CLI and Python API interfaces. Both methods expose structured trace data including TraceInfo and Spans, allowing you to locate and query traces programmatically or via command line.

How do I find MLflow traces slower than a specific execution time?▼

To find MLflow traces slower than a specific execution time, use the mlflow traces search command with time-bound filters. This allows you to query and audit trace performance by applying execution time criteria across runs.

Related Skills

Explore More Data & Analytics Skills→
mirakuimirakui

querying-mlflow-metrics

Fetch aggregated trace metrics from MLflow tracking servers.

Community
Intermediate
TencentBlueKingTencentBlueKing
862

apm-trace-analysis

Analyze APM trace data to diagnose application issues and bottlenecks.

Official
Intermediate
dominodatalabdominodatalab
6

domino-experiment-tracking

Track MLflow experiments in Domino Data Lab with auto-logging.

Official
Intermediate
alessandro9110alessandro9110
4

retrieving-mlflow-traces

Retrieve MLflow traces by ID or filter by run, session, and time.

Community
Intermediate