Powerful multi-cloud observability with real cost and usability tradeoffs
January 14, 2026

Powerful multi-cloud observability with real cost and usability tradeoffs

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Datadog

We're a global ad-platform company with hosts across multiple regions on both AWS and GCP. Datadog helps us manage multi-cloud complexity, monitor latency and ad-delivery performance, and ensure high availability at scale.It lets us correlate logs, metrics, and sometimes traces to quickly diagnose issues, reduce mean time to resolution, and prioritize capacity and cost optimizations. Datadog provides a unified view for engineering and SRE teams, drives alerting and incident management, and supports post-incident analysis—covering infrastructure, services, and application performance across the entire pipeline.

Pros

  • Free-form search across logs and fields (`*:query`)
  • Heavy-duty dashboard capabilities, handling a lot of data with relative speed
  • Thorough, solid integration via datadog-agent and the various plugins
  • Exceptionally quick/nice support

Cons

  • Alarms leave a lot to be desired. My team currently struggles with alarm fatigue because we couldn't find way to represent complex/sophisticated failure modes that would auto-recover, so we incur in noise. The composite alarm functionality is not enough.
  • Costs are frequently opaque, and deciding to adopt new features requires talking to our representative to estimate real impact
  • Some recurring, but fundamental issues have to be solved via workarounds, such as tags being delayed by cloud-providers and requiring workarounds at the risk of having gaps on dashboards. The agent should handle that automatically.
  • Shorter MTTD
  • Increased % of support queue fulfilled, given the access to historical data via rehydration
  • Increased systems performance after surfacing pipeline-wide profiling data
Datadog is generally useable, but some useful features are difficult to find; I often had to actively show them to coworkers.
Other features, like log transactions, never worked reliably for me regardless of how carefully I read the documentation.
Lately I've relied more on Datadog support to sort through hiccups - they are very responsive and helpful.
Datadog is significantly more user-friendly than CloudWatch.In terms of capabilities, they're similar.
I would not call either of the best-in-class for any single feature, but Datadog feels more polished and ready to use overall.Multi-cloud monitoring is a clear differentiator in Datadog's favor.

Do you think Datadog delivers good value for the price?

Not sure

Are you happy with Datadog's feature set?

Yes

Did Datadog live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Datadog go as expected?

Yes

Would you buy Datadog again?

Yes

AWS CloudFormation, CDK, Amazon Elastic Compute Cloud (EC2), Amazon S3 (Simple Storage Service)
Datadog shines when correlating logs, metrics, and traces across systems/cloud providers.
The various integrations (either native or via the agent) make it straightforward to get unified views over complex systems.

That said, it can be costly and the pricing is often opaque, which complicates forecasting and optimization. Non-trivial amounts of time are spent seeing what we should emit/index, and many features are outright forbidden given our data volumes. Its breadth is also a double-edged sword: without careful tuning you can very quickly hit alert fatigue.

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