Dynatrace provides observability for logs without having to configure any upfront parsing or metric extraction rules. This advancement in log observability was made possible through Grail – the new core platform technology which unifies data while retaining its context to deliver fast, scalable, and cost-effective AI-powered answers and automation. To convert your raw logs into actionable answers Dynatrace also introduced DQL (Dynatrace Query Language) for context-rich log analytics.
Watch this observability clinic with Andreas Grabner @andreas_grabner where Josh Lange @joshua_lange and Michal Franczak @michal_franczak walk us through:
What is the problem that Dynatrace Log Observability solves?
What is Grail and how does it work?
Explore the new Log & Events Viewer
Introduction to Dynatrace Query Language
Tips and Tricks for working with DQL
Here are all the follow-up links we discussed in the tutorial:
Dynatrace Grail: https://dynatr.ac/3FOow2R
Any Analysis, any time: Logs powered by Grail: https://dynatr.ac/3T2Ejhh
Dynatrace Query Language: https://dynatr.ac/3fvhPYK
DQL Guide: https://dynatr.ac/3T3sQ11
Dynatrace Pattern Language: https://dynatr.ac/3FHoF7V
Business Analytics: https://dynatr.ac/3EanKfn
Chapter List:
00:00 – Introduction
01:23 – What you're going to learn today
01:52 – What problem Dynatrace solves
02:22 – What is Grail
03:58 – Dynatrace Query Language (DQL)
08:28 – Introduction Live Demo DQL
32:00 – Advanced Live Demo DQL
38:26 – Classical vs Grail Log Observability
43:46 – What's coming next
47:05 – Wrap-Up & More Resources
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