What problem does it solve? Teams often add monitoring after code is written, leaving them without baselines, verification queries, or measurable rollback criteria when deploying changes. This Skill designs observability before implementation by grounding every decision in live Dynatrace runtime data. ## Core Features & Use Cases - Baseline Discovery: Runs DQL queries against live data to capture latency percentiles, error rates, throughput, and infrastructure saturation for a target service. - Blast Radius Mapping: Uses topology and trace data to identify upstream consumers, downstream dependencies, shared infrastructure, and active problems a change could affect. - Verification & Rollback Design: Produces ready-to-run post-deployment DQL queries, SLO recommendations, and rollback thresholds derived from actual baseline values. - Use Case: Before modifying a checkout service, a team uses Dynatrace Assist to resolve the service entity, collect its p90 latency and error-rate baseline, map its five upstream consumers, and export a Markdown observability plan with regression checks and rollback triggers for the development team. ## Quick Start Ask Dynatrace Assist to build an observability plan for the service you are planning to change, starting with baseline collection and blast-radius mapping.
