Datadog Pros and Cons

Their interface is probably one of the easiest things to use because it lets non-developers and non-engineers quickly get access to metrics and pull business value out of them. We could put together dashboards and give it to people who are non-technical, then they can see the state of the world.

We have been able to set very specific CPU and memory alerts, at the very base level, then we started to pull real business value, like 99th percentile response rates for our API calls.

It has turned into an operational dashboard. If you felt something is going wrong, you can immediately open up Datadog. It has been our go to application because we know the answer will be there.

It provides more cloud data. They tend to just get the way a service would be designed on the cloud.

It has saved us a lot of trouble in implementation.

The ease with which we can filter, use metrics, and give accounts to customers, then let the customer filter, set up metrics, and alerts. This has been a big win for us.

It has scaled great. I haven't run into any problems anywhere that I've used it. They have handled everything that we have needed them to.

It lets us react more quickly to things going wrong. Whereas before, it might have been 30 minutes to an hour before we noticed something going on, we will know within a minute or two if something is off, which will let us essentially get something back up and running faster for our customers, which is revenue.

We have a better grasp of what is occurring during the deployment cycle. If something fails, we have an idea what has failed, where it has failed, and how it failed to better mitigate the situation.

It is a good one stop location where we keep all our data for our infrastructure, and it's also easier to navigate between different things.

The integration and configuration are incredibly simple. The SaaS offering is remarkably easy to set up, especially if you're coming from a Graphite environment or anything that uses a StatsD.

The ingestion points are unlimited and support customization. We haven't had anything yet that we haven't been able to integrate with it.

If we have a large load for users using our basic Datadog, it will immediately fire off an alert notifying us either something's wrong or not.

It has a nice UI.

Using the data, our operation teams works with the dashboards to get their statistics, analytics, etc.

It has enhanced the performance of my team.

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

The way data is represented can be limiting. When I first tried it out a long time ago, you could graph a metric and another metric, and they'd overlay, but you couldn't take the ratio between the two.

When I started using it years ago, it had stability problems. I remember, specifically, we ran everything in Docker containers. There were some problems getting it into a Docker container with very specific memory limits.

It does not have the best interface.

Stability of the product has been a concern for us outside of the primary monitoring agents.

It lacks consistency in the APIs.

I would love to see support for front-end and mobile applications. Right now, it is mostly all back-end stuff. Being able to do some integration with our front-end products would be awesome.

We want to reduce having to go to different screens to obtain all the information.

At the beginning, when we started throwing logs at it, there was a bit of hiccup. However, this was during their beta period, so hiccups were expected.

There are things about it that we would like to be fixed, such as it is taking averages of average. This results in data that we don't expect.

We have asked technical support questions, and sometimes they don't get back to us right away. Or when they do, it is not the right answer.

I would like testing for data in the future.

The product could do better with its notifications.

The on-premise version is very difficult to upgrade.