Datadog Reviews

We use the solution for logs from all our applications. In Datadog, for monitoring logs, our team creates an automation for implementing massive logging in all our systems. Now, we are deploying it in our core systems.

We are using it to indicate issues and alert our operations team. With this, we better monitoring of our applications and logs.

However, the main difficulty is implementing the solutions in our Kubernetes cluster, separated just as logs to the specific namespace as the volume of logs is tremendous.

The solution is useful for monitoring logs. 

We can create an automation for implementing across all our systems. Right now, we are deploying it in our core systems.

The greatest value is integrated monitoring as it is able to quickly detect issues and improve our time to market.

Our main challenge is implementing the solutions in our Kubernetes cluster, separated just as logs to the specific namespace since the volume of logs is tremendous.

I've used the solution for one year. 

Our company is transitioning to using the solution for monitoring and analytic services we provide to customers. Once fully rolled out, there will be 80-100 users companywide. 

The solution's SaaS model is easy to manage and works well in single- or multi-cloud environments. 

The Saas format can handle heterogeneous or multi-language applications much better than using a combination of tools. 

Graph filters for logs need to be set manually which works well for JSON but not for unstructured logs. 

Making structured logs for high-performance applications is over our heads so we had to dump some technical streams for our logs. 

I recently started using the solution. 

The solution is stable and passed an our internal assessment.

The solution is scalable. 

We received product support through the sales department and they were helpful. 

The solution is better than what we previously used. 

The initial setup is straightforward which is impressive.

I rate setup an eight out of ten. 

We implemented the solution in-house and are continuing to roll it out. 

Licensing is based on the retention period of logs and metrics. 

I rate the solution an eight out of ten. 

The application performance monitoring is pretty good. 

The Log Explorer could be better. I don't think it has log manipulation as Splunk does.

I've only been using Datadog for the past one or two months. 

Datadog is stable. 

The initial setup is pretty easy. It's a kind of agent-based application monitoring. It's similar to Splunk and Elastic Stack.

Although I don't have that much experience with it, overall, on a scale from one to ten, I would give Datadog a rating of eight. 

We use it to monitor our infrastructure, particularly our different EC2 instances, and our containers. We also use it to capture our logs.

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.

We want to reduce having to go to different screens to obtain all the information. However, they are moving in the right direction from what we have noticed.

Stability has never been an issue. We throw all of our servers and containers at it. We have now started to throw our on-premise logs at it too.

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.

It pretty much vacuums up any information that we throw at it. So, stability hasn't been an issue.

It scales depending on the time of year. Right now, we have about 25 to 50 instances, and in each instance there are probably five different containers, not including logging for all those containers.

We used their technical support, especially during rollout. They were really good. We worked hand in hand to try to figure out how to configure everything.

For the monitoring of different EC2 instances, you install them into Datadog. 

We use Chef to install Datadog's package, then that calls out all the information from the instance.

We did evaluate other vendors.

We chose Datadog because we were looking for an all-in-one package. They also do log caching and integrate with other systems well.

Take advantage of Datadog's trial period, and really beat it up, then give them a call.

We use the web service for this product.

The solution is primarily used for better understanding the health of applications, modern environments, and many other solutions, which are the main focus of Datadog and many other monitoring tools.

With Datadog specifically, I can look at the health of the technology stack and services, and also integrate multiple metric sources, security, business data, and much more. This makes it a real software solution for centralizing data and unifying monitoring silos in one place. Datadog is like a hub - not just a monitoring software.

The solution primarily has helped the organization by helping us better understand the health of applications, modern environments, et cetera. 

We can see the health of the technology stack and services. We can also integrate multiple metric sources, security, business data, and much more. It centralizes data and unifies monitoring in one place. It's Helping reduce costs with other solutions, and also reduces costs with teams that might waste time with manual troubleshooting.

Understanding better the health of applications, modern environments, and many other solutions, is the main focus of Datadog and many other monitoring tools.

With Datadog I can look at the health of the technology stack and services. I can also integrate multiple metric sources, security, business data, and much more. It's great for centralizing data and unifying monitoring silos. 

Datadog is a hub, not just a monitoring software. The biggest value of Datadog is looking at the big picture, not only one part of it.

Datadog could have a better business analysis module. 

Other vendors have specific business collections and analyses. With Datadog, I don't see much of it. It's possible to do this with custom metrics, dashboards, etc. However, none of those are business-focused - and that is what is lacking in Datadog.

I've used the solution for two years. 

We use the SaaS version of the product.

We have a web infrastructure that uses Amazon Web Services containers with everything included, and we use Datadog to monitor them all.

The most valuable feature of Datadog is its logs. We can use the logs to conduct analysis and root cause analysis.

They could look into improving the integration.

I'd like to see better pricing and more integration in the next release.

I have been working with Datadog for approximately one year.

Datadog is a stable solution.

The scalability is good.

Datadog is currently used by 15 people in our organization.

We intend to continue and expand our use of this solution.

We contacted technical support, and they were extremely helpful.

The installation is reasonably straightforward.

We are a small organization. We have one administrator who is responsible to maintain and keep this solution up to date.

Our licensing fees are paid on a monthly basis.

It's quite expensive. They could improve the price by making it affordable.

I would recommend this solution to others.

I would rate Datadog an eight out of ten.

We use it for monitoring and instrumentation of security. We secure our databases and servers. It is typically for the security of apps, services, and systems. We are using its latest version.

It has reduced some challenges, and it has optimized the time spent on monitoring and management activities. It has improved the visualization and the ability to monitor and control.

Datadog increases our visibility. It puts all the data in one log so that we can use that log in a contextual manner. Some operational optimizations definitely have happened with this solution. In general, the user community is happier than before. We are basically asking them every quarter how happy they are on a scale of zero to five. That needle has moved but not significantly. If it was 3 earlier, it is still less than 3.5 now, but the user experience is better than before. 

Because of this monitoring, we are empowered to publish certain dashboards for the business folks as well. We have three to five senior business folks who are looking at their investments and operations optimization. They are basically putting money on the table for this.

Its integration definitely stands out. It provides seamless monitoring of all our systems, services, apps, and whatever else we secure and monitor. 

Visualizations have become simpler with dashboards. We are getting visibility into systems, services, and apps stack through a single pane of glass, which is good. We are able to put logs in context.

It can have an artificial intelligence component. Even though I can seamlessly look at end-to-end security, it would be better to have alerts and notifications powered by an AI engine. I am not sure if they have an AI component. We have not reached out to them or looked at it, but this is something that I keep on talking about within our company in terms of features. Such a feature would be good to have, and it would further optimize my Security Ops team's abilities.

I have been using this solution for almost six months now.

It is stable. There is nothing critical about it. I've not heard of any significant issues in terms of operating this solution in the last six months.

We have only been using it for six months, and we haven't scaled it. Six months are nothing for such a solution.

We do monitoring as a service, and we have a hundred team members in the team. There are between 30 to 50 users who actively use it in some way.

We had Carbon Black. We didn't switch from Carbon Black to Datadog. Datadog was something different because of the visualization capability and bringing everything together. We acquired a couple of companies, and Datadog was being purchased. We just validated the purchase specification, features, and assessments. It was not a one-on-one sort of exchange of Carbon Black with Datadog.

It was easier than what we had been using in the past. It is a SaaS-based solution, and it was supposed to be a straightforward setup.

It is too early for that. I have not yet seen the impact on my budgetary lines or process optimization. I had ten people in my Security Ops team earlier, and I still have ten people. They are definitely happier as users than before, but what does that give to the organization is not yet clear to me. 

I would rate Datadog a seven out of ten. It is too early to say whether we are getting our money's worth, but we have felt the difference in terms of optimization and user experience.

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.