Datadog Reviews

We used Datadog to capture the salvatory of our AWS fleet of around 1,200 servers.

Datadog's ability to group and visualize the servers and the data makes it relatively easy for the root cause analysis.

Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic.

Datadog's price is also high.

I have been using Datadog for about three years.

Stability really wasn't ever an issue. We didn't have any outages specific to Datadog where we couldn't get reports or insights to information. We were more concerned about the stability of our own systems and applications.

There was no issue with scaling as such. It didn't scale well only from the cost perspective.

Fortunately, because of the stability of the solution, we never had reasons to deal with technical support. Most of our interaction was with their product management, which was focused on the feature capability and ultimately pricing.

It didn't scale well from the cost perspective. We had a custom package deal.

We switched from Datadog to New Relic because it offered ET functionality. Datadog was traditionally born out of monitoring infrastructure. Over the years, they have improved their ability to give you insights at the application layer and to be considered under APM. New Relic really started at the application layer and has worked its way down. 

Ultimately, we were able to accept New Relic because coming from an operations team, infrastructure was more important. As our application became more complex, our application developers needed better insight. Because there is a significant overlap in the Venn diagram between Datadog and New Relic, we felt that the needs of the infrastructure team and the applications team could be met with New Relic and its expansion in providing a sort of lightweight security.

Datadog started off at the infrastructure level, and New Relic started off at the application level. Both of them were expanding not only into each other's space but also into the SIM space.

There are a lot of options out there. For folks like me, it becomes a costly proposition because, at the end of the day, we're talking about logs, events that get pushed out. I have to push out some to Datadog and some to the security event manager. Then you start to think why can't you just push them to one place and let a product do that. That's where these products are trying to grow. They're not quite there yet because the SIM space is pretty mature. An enterprise like ours needs something fully focused and dedicated. Startups can live with New Relic that has a security capability or Datadog.

I would advise you to really understand the value that you're trying to go after. Make sure that you're not trying to solve all problems that you have from the observability perspective with Datadog because that will erode the value you get out of this solution.

Make sure that you are going to use Datadog for infrastructure, and it is going to be great. If you start adding other kinds of stuff to it, you'll probably start losing some of that value. Especially, if you want to go for application-level monitoring, you may be a bit disappointed.

I would rate this solution a six out of ten. I'm a very price-conscious kind of purchaser.

Datadog has clear dashboards and good documentation. 

The solution needs to integrate AI tools. 

I avail support from our internal team. 

I rate Datadog a nine out of ten. 

We’re currently using logging, monitoring, metrics, APM, etc.

We've started to use e-SLOs, however, it takes a bit of time to work through those.

RUM has been very useful. I have used this in the past to debug problems in production, which has been g great.

We also want to start using synthetics and tracing more. 

Our application currently runs in many different environments based on our customers' requirements. This allows us to see everything in one place and filter by environment as required, which is extremely useful.

The product has offered increased visibility via logging APM, metrics, RUM, etc. We've gone from almost nothing to something that didn’t take a lot of time to set up. It has been great since we had so little time to spare.

As a startup, we have limited resources, and no one has enough time for anything. The fact that there are so many easy integrations and configurations by YAML makes everything easy to set up without needing a full-time employee. Instead, we're just configuring monitoring solutions which are very desirable.

The product is very useful for tracking down anything that’s gone wrong. I’ve been using it to make sure everything is working correctly after deployment and to make sure we don’t suffer performance degradation. We've found it great for tracking down anything that’s gone wrong in real-time.  

The logs are helpful. They are necessary for any application. Prior to this, our solution would have been to SSH into a machine and tail log files. This, however, is untenable for many reasons, and one of the first things I wanted to change.

The RUM has been great. Seeing real users interacting with our website is quite helpful.

Sometimes it’s difficult to customize certain queries to find specific things, specifically with the logging solution. I’ve used other logging platforms in the past that have extensive and mature query languages. This might not be super friendly to start out with, yet can be very powerful. 

I wish there was more of an emphasis on query languages instead of the UI-based tooling that Datadog provides. Even though it is powerful on its own, the UI-based design lacks the elegance, efficiency, and complexity.

I've been using the solution for six months or so.

I was previously familiar with Splunk.

I don’t handle pricing or licensing aspects. 

I did not evaluate other options. 

Our primary use case would be using the dashboards and getting proper insights based on the dashboards.

The monitoring, SLO, and SLA have been better and easier since we started using the Terraform infrastructure. APM has been easier as we had to enable it through the CronJob directly.

Profiling has been made easier. We are able to get many insights into the code. Profiling provides really good insights right now. 

Logs are the most valuable and the best solution so far. Datadog can help solve any slow queries or database-related errors. 

The primary use case would be using the dashboards and getting proper insights based on the dashboards.

Monitoring has been better and easier since we started using the Terraform infrastructure.

APM has been easier as we had to enable it through the CronJob directly.

Profiling has made it easier in terms of getting many insights into the code.

The logs are the most valuable and the best solution. Datadog can help us to solve any slow queries or database-related errors.

Profiling provides really good insights, and APM has really good tracing visibility. 

The SLA and SLO definitions and the monitoring are also really important and very valuable parts of the product and make great Datadog features. 

Datadog support is also really valuable as they provide support for the product through the chat as well. 

The Datadog premium support has helped us to provide faster outcomes for a problem. 

Also, rather than having an email thread, it would be better to get the support on call and sort out the issue, which is the support we get from Datadog CSM.

Integration should have been easier. It is very tough to go to all the services and enable Datadog integration for each AWS service. 

We can add the AWS services and the services on one page and show only the services that are enabled. A similar approach should be for any other integration.

Lately, chat support has a longer waiting time. We would love to get faster chat support. We also need additional support for sending the flare files

Observability is a key use case, as is security.

With this product, we get more visibility into our K8s clusters and more intelligent alerting.

Datadog dashboards are pretty great.

We need more integration with security tools like Drata.

I've used the solution for three years.

The main use case is observability and reliability as part of a platform/delivery engineering solution. We use the product to assist tenants and clients within the company to get more ramped up on SRE/DevOps.

The solution has provided us with a lot more insight into service-level metrics, which is especially useful with APM/tracing. It gives us all-up dashboards and alerts to assist with incident management.

The most useful aspects of the product are the dashboards and APM/tracing. The tools are powerful and intuitive to set up as well.

Custom-level metrics could be improved.

Billing should be more transparent.

I've used the solution for three to four years at multiple companies.

The solution is very stable.

The scalability is fantastic so far.

Technical support has been great so far.

The initial setup is straightforward. The documentation we use is very clean and concise.

We handled the initial setup in-house.

I would advise others to be cautious around custom metrics and be picky when setting them up.

We primarily use the solution for monitoring and log analysis.

Datadog shows all the logs for the services, and it is very useful for troubleshooting.

The most valuable aspect of the solution is the APM.

The logging capabilities are quite useful. 

The logging could be improved in the future. 

I've used the solution for four years.

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.