Dynatrace-AWS Observability Build-out

I need a Dynatrace-driven, end-to-end observability framework rolled out across several AWS-hosted microservices. The goal is to move from scattered point checks to a single, actionable view that covers infrastructure, runtimes, and user-facing performance.

Scope
• Instrument every workload that lives on AWS—EC2 instances, container clusters, Lambdas, managed databases, you name it—so that Dynatrace captures golden signals automatically.
• Create service topology maps that make call chains and dependencies obvious at a glance.
• Design production-ready dashboards focused on CPU / memory usage, response times, and error rates; the layout must let engineers trace an issue from high-level SLO status straight down to the offending log line.
• Define practical SLOs and SLIs for each critical service, wire alerting policies, and publish them to both Opsgenie and ServiceNow (SNOW) so incidents open with the right priority and routing.
• Tune alert noise: Davis AI, custom thresholds, maintenance windows, and smart baselining should all be in play.
• Document the whole setup—tagging strategy, management zones, maintenance, and how to extend the framework to future services.

Acceptance criteria
1. All agreed workloads appear in Dynatrace with accurate metadata and no blind spots.
2. Dashboards load in under two seconds and surface CPU / memory, response times, and error rates without manual drill-downs.
3. Each SLO page shows a green / yellow / red status, with alert rules that trigger an Opsgenie incident and a ServiceNow ticket containing clear remediation notes.
4. A hand-off guide (markdown or Confluence-ready) explains how to add a new microservice in under ten minutes.

If you’ve built similar observability stacks and can demonstrate a clean, maintainable approach, let’s lock in the timeline and get started.