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Explore the key features that make Dynatrace powerful for deployment & hosting workflows.
Dynatrace uses consumption-based pricing across multiple SKUs, including Full-Stack Monitoring (starting around $0.04/hour per 8 GiB host), Infrastructure Monitoring (around $0.01/hour per host), Log Management & Analytics (priced per GiB ingested and queried), Application Security, and Digital Experience Monitoring. While there is a 15-day free trial and self-service signup, the platform's commercial model and feature depth are clearly aimed at mid-market and enterprise buyers. Smaller teams typically find the total cost of ownership higher than lighter SaaS APM alternatives, especially once log ingestion and retention are factored in.
Davis AI is Dynatrace's deterministic causal AI engine that uses the real-time Smartscape topology to trace cause-and-effect relationships rather than relying purely on statistical correlation. This means when an incident occurs, Davis identifies the actual root-cause component (a failing pod, a slow database, a third-party API) along with all impacted entities, instead of surfacing dozens of correlated alerts. Dynatrace has expanded Davis with predictive AI for capacity forecasting and a generative AI copilot (Davis CoPilot) that lets engineers ask natural-language questions and auto-generate DQL queries, dashboards, and workflows.
Compared to the other major observability tools in our directory, Dynatrace is generally seen as the most automated and AI-driven of the three, with the strongest auto-discovery via OneAgent and the most mature causal root-cause analysis. Datadog typically wins on breadth of integrations (700+) and dashboard flexibility, while New Relic is often more cost-predictable thanks to its per-user pricing model. Dynatrace tends to be the preferred choice for large enterprises with complex Kubernetes, mainframe, or SAP environments where automation reduces operational toil, while Datadog and New Relic are often picked by faster-moving teams that prioritize developer ergonomics or budget predictability.
Dynatrace supports a very wide range of environments including AWS, Azure, Google Cloud, IBM Cloud, OpenShift, Kubernetes, VMware, on-premises servers, mainframes (z/OS), and SAP systems. The OneAgent supports major languages including Java, .NET, Node.js, Python, Go, PHP, and Ruby, and integrates with OpenTelemetry for vendor-neutral instrumentation. It also offers prebuilt content for hundreds of technologies through Dynatrace Hub, including databases, message queues, CI/CD platforms, and ITSM tools like ServiceNow, Jira, and PagerDuty.
Yes — Dynatrace Application Security adds runtime vulnerability analytics, runtime application protection, and attack detection on top of the same OneAgent used for observability. Because it observes applications at runtime, it can prioritize CVEs based on whether the vulnerable library is actually loaded and exposed to the public internet, dramatically reducing false positives compared to static SAST tools. Combined with AutomationEngine workflows, security teams can automate remediation tasks like ticket creation, deployment blocks, or runtime mitigations, making Dynatrace a credible DevSecOps platform alongside its observability function.
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Tutorial updated March 2026