Datadog Reviews

Sometimes it's more user friendly for development teams. There are some parts of Datadog that are more understandable for development teams. For example, the APM in Datadog works more manually and works like the tools in New Relic or Grafana or Elastic. It is easier to understand for software development teams. 

It could use some additional features when working with metrics like Grafana or like New Relic has. Datadog does not use library technologies like Dynatrace does. Datadog has machine learning too, but it does not have this option in all layers of monitoring like infrastructure service process in applications. 

I've used Datadog for about one month. 

Datadog is a great tool, but it does not cover 100% of all libraries and technologies, like Dynatrace does.

I give Datadog an eight out of ten. 

We use this solution to monitor our Kubernetes clusters, nodes, deployments, daemon sets, replica sets, and pods.

I've been using this solution for a few months at my current company as a member of the Kubernetes team we use Datadog to provide monitoring and telemetry for our team and our customers.

This solution has improved our organization by giving us deeper insight into what's running in our clusters and their performance of it.

I have found the logging and tracing features the most valuable.

The documentation could be improved regarding setting up the agent properly and debugging.

I've been using this solution for a few months at my current company.

Private Cloud

Amazon Web Services (AWS)

We use it to store editorial content.

We started out on the on-premise version, then moved to the AWS version.

I don't have to worry about upgrades with the AWS version.

The on-premise version is very difficult to upgrade.

More than five years.

The fact that its hosted so you don't have to rely on infrastructure to do the work is a very valuable feature.

At other places I've worked, we had to rely on different types of infrastructure -- Datadog does all that. Its very time saving. Datadog has alerting events and metrics all in one place; This was a huge plus, other solutions were trying to treat monitoring as a multi-faceted problem. Datadog treated it as one problem. Also, We no longer use Nagios for alerting, we use Datadog’s alarms, and then we push the data into PagerDuty.

The performance, especially when were drilling into metrics we've been running for a year and a half. When you're launching old data it can get slow.

We have been using the solution for the last year and a half.

No issues with deployment.

No serious issues with stability -- has been pretty great.

We pushed them sometimes, meaning when we would do something their platform didn't support. But they were always very cooperative and proactive.

Customer Service: Very good customer service.Technical Support: Hit or miss, always very proactive and friendly but could be faster sometimes. Almost always have the right answer, but sometimes could be a bit quicker.

At this job I've only used Datadog. Past jobs I've used New Relic, and assortment of others.

Very straightforward. We got Datadog running in a couple of hours, and deployed it across our production environment, We just installed StatsD, started sending metrics, and it just worked. Deployment was super easy and their setup and integration made us feel like it wasn't a vendor lock-in.

Initial cost was a couple of days of work, day to day nothing really.

Yes, we evaluated a bunch of option, including New Relic, as well as toying with the idea of hosting our own, a couple of others as well. We didn't want to manage our own, our corporate culture is to let other companies be the experts when possible. In the case of Datadog, the product exists -- made sense to let them be the experts.

I'm an advocate of Datadog -- go for it.