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dt-obs-problems

Correlate Dynatrace AI-detected problems with logs and metrics for root cause analysis.

2|1|Updated Apr 15, 2026
Search Tags:#analytics#logs#root-cause#correlation#incident-analysis#problems#davis
One-click install
npx skills add https://github.com/israel-salgado/dt-mcp-server --skill dt-obs-problems-israel-salgado
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dt-obs-problems
Source: https://github.com/israel-salgado/dt-mcp-server/tree/main/.agents/skills/dt-obs-problems
Command: npx skills add https://github.com/israel-salgado/dt-mcp-server --skill dt-obs-problems-israel-salgado

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Analyze Dynatrace AI-detected problems including root cause identification, impact assessment, and correlation with logs and metrics.

Core Features & Use Cases

  • RCA and root cause analysis across problems
  • Impact assessment of affected users and services
  • Correlation of problems with logs, metrics, and events to drive investigations
  • Pattern detection and problem trending references for proactive monitoring

Quick Start

Ask the assistant to query current and historical DAVIS problems to identify root causes and impacted entities.

Frequently Asked Questions about dt-obs-problems

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

FAQPage Schema
How do I identify the root cause of Dynatrace Davis problems using logs and metrics?▼

Root-cause analysis for Dynatrace Davis problems is performed by correlating detected incidents with logs and metrics. The Skill evaluates active and historical problems across services, infrastructure, and user sessions to pinpoint underlying causes.

Can I assess the impact of active problems on affected users and services?▼

Impact assessment of affected users and services is supported by evaluating problem data fields like event start and end times. This allows you to measure the scope and severity of incidents across your environment.

What data fields are required to correlate incidents with logs and metrics for root-cause analysis?▼

Accurate problem data fields such as event.start, event.end, dt.davis.event_ids, and Smartscape data are required. These fields enable the correlation of problems with logs, metrics, and events to drive investigations.

How do I analyze historical problems across services and infrastructure for pattern detection?▼

Historical problems across services and infrastructure are analyzed by querying past Davis AI-detected events. This supports pattern detection and problem trending references for proactive monitoring and cross-domain correlation workflows.

Does this approach to incident analysis work for cross-domain correlation workflows?▼

Cross-domain correlation workflows are supported by linking problems across services, infrastructure, and user sessions. This enables comprehensive investigations by querying and connecting problems with relevant logs and deployments.

What is the best way to perform RCA on Dynatrace AI-detected problems?▼

The best way to perform RCA on Dynatrace AI-detected problems is by correlating incident events with Smartscape data and logs. This identifies root causes and assesses impact across active and historical problem sets.

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