Datadog Reviews

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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.

We run the agent in AWS. 

It has empowered all our platform engineers with a very powerful and easy to use monitoring system. Most of our platform organization is now involved in monitoring. Previously, only a handful of platform engineers were involved, because Graphite and Sensu were so cumbersome to use.

It is incredibly easy to do common monitoring actions:

• Excellent autocomplete for everything in the UI.
• Using tags is very intuitive (in contrast to the cumbersome regex-like based querying in Graphite).
• Going from viewing a metric to creating a monitor alerting on a metric is very easy. This is very important as the easier it is to create monitors, the more monitors will be created by people. With Graphite and Sensu, the effort required to create and test a monitor was so great that we had only a handful of monitors. We now have over 300 monitors.

• It would be nice to be able to graph metrics by excluding certain tags (like you can do in monitors). 
• It would also be nice if we had more insight into our own usage of Datadog (agents and custom metrics). They provide a usage page which does help, but it is not in real-time. 
• It would be great if usage metrics were automatically created and we could create custom metrics, instead we ended up building some of our own stuff to track and alert on our own usage.

One to three years.

Very rarely. Maybe only once or twice that we noticed. It is very reliable. 

No.

It is excellent. The web app has a real-time support chat window in which a support engineer is chatting with you within a minute. That is the "right" way to do support. 

We previously ran Graphite and Sensu ourselves. By moving to Datadog, we did not need to manage our own monitoring infrastructure anymore. Graphite was somewhat complex to run.

Initial setup is easy. Install the agent and send it metrics. There are StatsD/Datadog libraries available for most languages.

Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure. It is hard to say without looking at all of this.

We looked at several competitors at the time (Summer 2016). There did not seem to be any compelling alternatives. Once we did the PoC with Datadog, we loved it and decided to move forward.

Try it out and see if you like it.

We can build dashboards as fast we roll out new systems, which can be fast.

We use standard and custom metrics for every new system we roll out for 360 degree visibility into our systems.

The most valuable features have been: Sharable dashboards, TimeBoards, dogstatsd API, Slack Integration, Event logging API. CloudTrail Events, Tags, alerts, and anomaly detection. EBS Volume Snapshot Age, which they added upon request. We used PagerDuty integration for a while as well.

More granular control over dashboard sharing. Timeboard sharing.

There are infrequent hiccups, which have been decreasing over the time we have used it.

No.

Customer Service:

Never seen better. Questions answered usually almost immediately, even on weekends. An in-stream with your event stream.

Technical Support:

High.

Overall they have always had an amazing team, and quality has been maintained as the company has grown.

Complementary to other tools we used.

Setup is generally easy. They provide an large number of integrations, some are more complex than others, which is to be expected.

In house implementation.

We didn’t calculate explicitly, but as we used the product to track down underutilized instances, it more than paid for itself in the first month.

Pricing overall in this segment has standardized in the last several years.

A few, including Zabbix and Icinga.

One of the fastest and most flexible tools we have used in this area..

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.

We are providing managed services to our customers across multiple industries. Datadog is key to delivering these services by bringing the observability, monitoring, and alerting capabilities we need to operate at scale. 

We operate custom cloud native workloads as well as ISV products such as Atlassian Jira or Confluence. 

Integrating Synthetics, infrastructure, and application performance monitoring, as well as piping all logs through Datadog allows us to operate more with less with good alerting right in time.

We are providing managed services to our customers across multiple industries. 

Datadog is key to delivering these services. It brings in observability, monitoring, and alerting capabilities - all of which we need to operate at scale. 

We operate custom cloud native workloads as well as ISV products such as Atlassian Jira or Confluence. 

Integrating Synthetics, infrastructure, and application performance monitoring, as well as piping all logs through Datadog, help with getting alerts in real-time.

We are providing managed services to our customers across multiple industries. 

Datadog delivers observability, monitoring, and alerting capabilities we need to operate at scale. 

Operating custom cloud native workloads as well as ISV products such as Atlassian Jira or Confluence is also something we do. Integrating Synthetics, infrastructure, and application performance monitoring, as well as piping all logs through Datadog allows us to operate while grabbing alerts in real-time.

The current way accounts are billed could be vastly improved - especially when involving multiple organizations across multiple accounts in combination with reserved commitments. 

Being able to have an automatic materialized report on certain dashboards that could be exported as PDF to be shared with non-Datadog users could help a lot. 

Other than that, we are more than happy with the features we use regularly.

We have been using Datadog since 2015.

We use Datadog incident management for our incident tooling. Whenever we run into an incident, we try to use it. It allows us to create a separate Slack channel for it.

Keeping track of incidents makes it possible to share learnings and follow-up. It is also required for SOC2 compliance.

It is great that creating an incident is possible from Slack while having all the relevant data in Datadog. It allows us to not think too much about organizing incidents, which is a highly stressful situation.

I would like the tooling to have better integration in Slack, specifically sending out reminders to the relevant people to take breaks, do a retrospective, and specify with emojis which messages to log.

Learning about the tooling could also be improved. It is a bit clunky to use, especially in an incident. It could definitely be more streamlined.

I've used the solution for about a year.

We're moving towards the cloud yet still have several active data center contracts. As we move to the cloud, we are interested in knowing more about our services, and DataDog APM/logs should give us this perspective. 

We currently use the infrastructure monitoring part of DataDog. Still, I've really seen the advantage of moving more data into the cloud for comparison and being able to have one place where we can view all related pieces of information regarding a possible incident or potential issue.

We've been able to glean from the monitors what servers are down, and can alert the team in Slack. Knowing what we need to do next is what we would like to move to, so seeing the power of Notebooks is key. We also have several other services that we are underutilizing (logging, error tracking, etc.) that would be better housed in DataDog since it gives us more visibility into linking all of the things together into one cohesive picture.

Monitoring has been invaluable, and as we start to look to other products, bringing in logs and APM traces will create a full picture of what we need to do to resolve incidents. We're also interested in our users' perspectives and when things are slowing down for them.

Additionally, we are interested in the workflows announced today as an actionable decision tree that will allow our teams to see what is wrong and know what to do based on the connected runbook/notebook. I feel that this is the final piece that will make DataDog so much more valuable than its competition.

I have talked to vendors that mention that DataDog is drawing attention to an issue. However, you'll still need to take action on your own. The more tools that they can build that allow you to run AWX playbooks, or other similar fixes, would benefit clients greatly.

We've used the solution for two years.

Hybrid Cloud