Review Summary
Users appreciate Dynatrace for its comprehensive monitoring capabilities, intuitive interface, and strong customer s ...
Users appreciate Dynatrace for its comprehensive monitoring capabilities, intuitive interface, and strong customer s ...
Dynatrace is the AI-powered observability platform. We empower today’s AI-enabled digital enterprises to understand their systems and data so they can analyze, automate, and innovate faster. With Dynatrace, you can transform complexity into your greatest asset and drive your business forward.
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I love the OpenPipeline implementation that allows us to modify retention on logs, metrics, and traces. I love the power of DQL centralizing all of the data on Dynatrace into a single query language that can be cross-correlated with trace headers and correlation ID's. I love the simplicity of the Dynatrace Operator and how it instruments entire namespaces with code-level visibility just with a couple of helm commands and some simple yaml configuration.
DQL - unifying data with the ability to pull in a large amount of context has been extremely helpful.
What I like most about Dynatrace is how it takes the guesswork out of troubleshooting. The Davis AI engine automatically pinpoints root causes without you having to dig through endless logs. One Agent deployment is seamless - one install auto discovers your entire stack with no manual configuration. Smartscape topology gives you a live map of how every service and component connects, making it incredibly easy to understand blast radius during incidents. Finally, having full-stack observability - infrastructure, APM, logs, and Real User Monitoring - all in a single pane of glass eliminates the need to jump between multiple tools.
BizEvent logs are segregated from the rest of the platform data, meaning we can't easily correlate business events to traces and logs, even if the W3C trace context headers are present in the bizevent table. Dynatrace makes it hard to rollout to a large group or company since I can't easily validate user permissions and scopes by spoofing a specific user to ensure they only have the access they need. Instrumenting .NET 8 Azure Functions with OpenTelemetry running in isolated workloads proved impossible for our company, and we found the documentation lacking in regards to doing so. This was such an issue that we had to pivot entirely to utilizing ASP.NET Core API instead of Azure Functions SDK for our application to be properly monitored by Dynatrace.
There was virtually no guidance on best practices. It felt like when asked about how to best do things, we were either given very specific answers (like which buttons to click to do a thing) or a general you're doing great, whatever way you are doing it is right!. Things like critical features like segregating data via buckets to ensure faster query response time with reduced cost was never highlighted until we explicitly asked about it. This was AFTER asking for best practices guidance.
What I dislike about dynatrace is the steep learning curve - DQL queries and advanced configuration takes significant time to master. Pricing escalates quickly with data injection volume, making it hard to predict monthly costs. The frequent UI re-designs constantly break familiar workflows, forcing re-learning. Lastly, alert noise requires heavy tuning up front otherwise DavisAI floods you with notifications