dt-obs-logs

Name: dt-obs-logs
Availability: InStock
Author: Dynatrace

Query and analyze Dynatrace log data using DQL.

120|26|Updated Mar 31, 2026

Search Tags:#troubleshooting #logs #aggregation #observability #query #log-analysis #dql

Ready to run

npx skills add https://github.com/Dynatrace/dynatrace-for-ai --skill dt-obs-logs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dt-obs-logs
Source: https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-logs
Command: npx skills add https://github.com/Dynatrace/dynatrace-for-ai --skill dt-obs-logs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Query, filter, and analyze Dynatrace log data using DQL for troubleshooting and monitoring.

Core Features & Use Cases

Fetching and filtering logs by severity, content, and entity
Searching log messages using pattern matching
Calculating error rates and statistics
Analyzing log patterns and trends
Grouping and aggregating log data by dimensions

Quick Start

Run a log query for the last hour and filter by ERROR to surface critical issues.

Frequently Asked Questions about dt-obs-logs

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

FAQPage Schema

How do I query Dynatrace logs using DQL to troubleshoot application errors?▼

Use DQL to query Dynatrace logs by filtering on severity, content, and entities to troubleshoot application errors. It fetches real-time and historical log data across services to surface critical issues for monitoring and analysis.

Can I calculate error rates and statistics from Dynatrace log data?▼

Yes, calculate error rates and statistics from Dynatrace log data using DQL aggregation functions. Group and aggregate log data by dimensions to analyze patterns, match content, and identify trends across monitored applications and infrastructure.

What is the best way to search Dynatrace log messages using pattern matching?▼

The best way to search Dynatrace log messages is using DQL pattern matching to filter by specific content and severity. This fetches relevant historical or real-time logs across defined entities to isolate issues quickly during troubleshooting.

Does DQL log analysis support filtering by entity and severity across services?▼

Yes, DQL log analysis supports filtering by entity and severity across services. You can fetch and filter Dynatrace log data to monitor specific applications and infrastructure components, calculating statistics and analyzing trends for targeted troubleshooting.

How do I analyze log patterns and trends across my infrastructure with DQL?▼

Analyze log patterns and trends across infrastructure using DQL field operations and aggregation. Query historical and real-time Dynatrace logs, group data by dimensions, and calculate statistics to identify recurring issues and monitor system behavior.