Datadog Reviews

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.

I'm a senior cloud security engineer and we are customers of Datadog. 

In terms of the public cloud provider integration of AWS, I would say it's very easy and straightforward to integrate. We can automate that way as well, because it also provides the cloud formation template and is a way to have a central place to monitor and visualize metrics in a multi-account structure. It's something we really need because the company has many AWS accounts. Rather than jumping from one account to another, Datadog gives us the functionality of having everything on one platform, in one place.

I believe there is room for improvement with this solution. It wasn't easy for me to get a quick understanding of what this tool offers us as opposed to the added tools of AWS. By that, I mean in regards to finding a better way to apply some filters or to create some alarms. I don't get more advanced features in comparison to AWS but at least I get a centralized way of doing things, which can be done on the AWS side as well. It's more complicated because you have to configure some other services to stream their logs from multi accounts to one account. It could be more user friendly and include advanced examples in the documentation showing some use cases or customer case studies, so you can get a clear idea that this functionality provides something extra. 

I've been using this solution for about a month. 

This is a stable solution. 

It's an SaaS solution, so it should be scalable although I don't know the architecture of it.

We have support from a technical engineer during the POC, which is still ongoing. It's amazing. Their customization and support during the POC include weekly meetings, with a follow up of any issues through email and Slack. 

The initial setup in regards to integration with AWS was very simple.

I would recommend this solution even though I don't have much experience with it yet. The company is currently using New Relic and we are now investigating Datadog for two reasons; the cost and also the integration with microservices and Kubernetes. I feel like this is a good solution. 

There is some room for improvement, so I would rate this solution an eight out of 10. 

We are a solution provider and Datadog is one of the products that I was working on with one of my clients. They are currently evaluating it for use in cloud monitoring.

Specifically, Datadog is used for monitoring cloud applications in terms of performance. The logs come into this solution from AWS and it provides dashboards for various environments.

The most valuable features are the graphs, dashboards, metrics, and the interface.

Additional metrics should be included.

Better integration with other solutions is needed.

I used Datadog in a project that lasted between one and two years. 

In terms of stability, I have not seen any issues and don't have any complaints.

Datadog is easy to scale.

We have not contacted technical support.

The initial setup was okay. I was not part of the implementation team but from my understanding, it was not complex.

Our in-house team handled the deployment.

My client is currently evaluating several monitoring tools including Datadog, Dynatrace, and AppDynamics. Compared to Dynatrace, Datadog has some room for improvement.

This is definitely a good product and I would consider them one of the leaders within the application monitoring and cloud monitoring space. My advice to anybody who is researching this solution is to consider it within the top three. That said, there are some features and metrics that are available in other products, such as Dynatrace, that are not available in Datadog.

I would rate this solution an eight out of ten.

We use it for notifications, alerting, and capturing most of the information from Amazon, such as EC2 instances.

It has enhanced the performance of my team.

The product could do better with its notifications. 

I want more technical support than conferences because technical support helps with setting up the product much easier.

So far, it has been pretty stable. After we stand up and configure it, it works well.

We have managed to get up to 350 hosts in one of the clusters, and it works fine.

Datadog's support is pretty good.

The integration and configuration of the product in our AWS environment was easy. This was one of the many things that I liked about Datadog.

I have not seen ROI out.

We chose Datadog over the other products that we evaluated because it had better features: notifications, alerting, and metric capture. Also, Datadog had the skill sets that we wanted at the time.

Try out some of the other products in comparison. This is a good product if you are looking for notifications and custom metrics.

We have always used the cloud version of this product.

This product also integrates with Slack and PagerDuty.

We are using the infrastructure and app monitoring side, such as process monitoring. We are using it in a very traditional way. We are not using the APM capabilities. When it comes to something like containers, we will generally use it on the host but not inside the container itself. 

We are using it with our customers and in-house day-to-day.

It provides more cloud data. They tend to just get the way a service would be designed on the cloud. Datadog can handle a server disappearing and account for it, but they will kick somebody out. 

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. This can't be done with a lot of the other platforms. This has made things considerably easier. Where we used to get "What's my performance?" Here, have access. Go nuts. Tell us if you need it. Now, our customers no longer ask us for all that, as they want to go do it themselves. This has made our lives infinitely easier.

The only thing that they were missing that has throw us from the beginning (they are still missing it) is consistency in the APIs. There are a couple of guys on the automation side who complain rightfully over how hard it is because every new feature which comes out has a new way of interfacing with the API. This was our big, red flag in the beginning, but given the price and other features, it wasn't enough for us to discount. We said "That we would live with this one red flag", but it is still a red flag.

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

It does not have the best interface.

We haven't noticed any issues in the primary use case for which we are using it. 

The reason we're not using or looking at the APM space right now is due to platform availability. Datadog doesn't support enough platforms, which they know. Every customer that we have is running PHP, and we cannot use APM with any of our customers because of that. Even if they are 95 percent running Java, if Datadog doesn't have PHP, we can't use it because it won't integrate.

Scalability has not been a concern at all. We have had customers with steady state loads: low and high. Our smallest customer is a friends and family startup which has about three instances. We have steady state loads which are more than 500. Then, we have customers with two instances all summer, but do seasonal work in the winter and can scale to more than 1000 instances. 

We have never noticed a hiccup on Datadog with any of our scaling. It has always grown to meet our program.

We have used technical support for certain integrations. We use a lot of Ansible and Chef, and we have had a lot of problems with both of these automating components. Technical support was helpful within their limitations.

We switched when we started getting heavy into the cloud. We used to use ScienceLogic, New Relic, AppDynamics, Zabbix, etc. It was hodgepodge. 

We were very strong in the APM space. We had all of our APMs going through AppDynamics, which suited a lot of our customer use cases in the cloud. However, when our customers started to get more specific, they wanted traditional core monitoring and the other on-premise traditional vendors, like ScienceLogic, weren't cutting it. That is when we started to look at Datadog. We went back and forth for a while between Zabbix and Datadog. In the end, Datadog won out based on feature price and everything together.

The integration with the AWS environment has been pretty seamless. There have been a few services that we don't use that they don't have book support for. However, usually that happens when it is a new service which is really unpopular. Most of the time, our customers shouldn't have been using that service to begin with, since it's a legacy thing that we inherited. I can't think of a single case where we haven't told the customer "You have to get off of that." 

It has saved us a lot of trouble in implementation.

The pricing came up a bit compared to their competitors. It is not that the price has risen, but that the competitors have gone down. They keep adding more features that I would have expected to be baked in at a more nominal price. I have been increasingly dissatisfied with the pricing, but not enough to jump ship. It is still pretty good.

Check the APIs very carefully. Without fail, this is the single biggest complaint for automation and operations. It is not that it can't be done. Just make sure that you have the technical expertise to work around it.

We use a mixture of both AWS and on-premise. There are actually three scenarios: 

1. Some of our customers purchase it for AWS. 
2. Some of them were accounts that we set up directly on Datadog for our customers. 
3. In some cases, customers already have a relationship with Datadog. 

Those are the three scenarios. Some have a mixture of scenarios due to regulatory reasons.

• Monitoring
• Analytics
• Tracing
• APM

It's hosted. We don't have to do it, and they handle a large amount of data with backups and all of the other things that we no longer have to manage. 

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, but overall we are happy with it.

It is incredibly stable.

We have had no issues with scalability.

We have needed technical support because we were dealing with averages of averages.

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. Datadog is a custom StatsD client, and it adds additional functionality, like tags, etc. However, out-of-the-box should work with native StatsD, so it is incredibly easy to drop in replace if you are using StatsD for metrics.

In terms of employee time: While the instructor costs were transferred to Datadog, it freed up our engineers to work on things which were of valuable to our business rather than maintaining a service that we don't make money on.

It costs the same amount it would if we were hosting it ourselves, so we are incredibly happy with the cost.

We did look at several vendors. What it came down to is we did not want to manage the metric services ourselves anymore, and Datadog matched what it cost for us to host it ourselves.

Check out Datadog. It is awesome.

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

We have only used the SaaS offering, but not AWS nor on-premise.

If our app is up and running, we use it to monitor how many credits the app is using up on each node. We also monitor services by how long each call is taking with the help of EC2s off of application.

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 provides us insights on our calls to other services, such as how long each call is taking and what is the whole stack trace.

• It is very easy to use.
• It is easy to configure.
• It has a nice UI.
• Datadog provides everything that we need.

Stability is great. It has not come down. It is always up.

We do not put a lot of stress on it. It use for monitoring our app, and it's a pretty great product.

We have an application in AWS running four nodes. It is not too large. Our user base is about 2000 users.

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. 

Before Datadog, we had APM monitoring, which is something similar, but it wasn't as nice to use or as easy to configure.

It is easy to configure. You load the Datadog agent into the EC2 instance, then you just follow it. 

I did not participate in the evaluation of the other products.

If you are monitoring the metrics and insights in your application, and need help monitoring, then this is a great application to look into. The app is always available. It has a clean UI and provides the metrics that you will need. It is a good product.

Right now, we only using it on this one application.

The primary use case is application monitoring. We also use it set custom metrics and watch our AWS metrics, as well as data.

At my current job, I have only use it a couple months. However, I used it for a few years at a previous company.

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.

Its most valuable feature is the monitoring, such as all the custom metrics that Datadog imports from AWS. In addition, the specific monitoring where you can set up an alert to a bunch of different services. 

Some of their newer solutions are interesting, like their logging, but they are not fleshed out. They could use more metrics or synthetics, which would be really helpful.

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.

It is very stable. Both times that I have worked with Datadog, we haven't had any issues with them going down. Or, if they did, we didn't know, which is good.

At the previous company that I worked at, we threw a lot at them all at once.

Because this is a newer integration, we are putting less stress on the tool. We are still working on integrating it into our platform.

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.

We are a 100 person company with 20 engineers.

The technical support is great. They respond quickly. They know what they are talking about and dig right in. If they don't know the answer, they can get it to us very quickly.

The integration and configuration through AWS was pretty smooth. It was easy to set up and start using. The documentation was clear. So, it worked really well.

We did the integration and configuration through AWS ourselves.

We haven't seen ROI at my current company. The solution is too new. 

At my last company, we did see ROI, specifically around response time. We could get to mission critical things that were down and losing revenue on immediately. So, the product paid itself back.

The pricing and licensing through AWS Marketplace has been good. It would be nice if it was cheaper, but their pricing is reasonable for what it is. Sometimes, for their newer features, they charge as if it's fully fleshed out, even though it is a newer feature and it may have less stuff than their other items. So, if they would scale the pricing appropriately as they add more stuff to it, that would makes sense. The pricing should reflect the abilities of the features.

We looked into self-hosting something, like Prometheus. We also evaluated New Relic.

We chose Datadog for its ease of use in getting set up and what they offered us.

Take the time to explore it and see all the metrics which are available. The metrics make the reporting better. Spend the time and learn the metrics. The things that they can send and give you are good. Learn how to aggregate them and how to write more complex queries, which they do a good job of showing how to do, but I found that newer people don't do this. They just try to use the baseline set of features. Doing the more complex stuff adds significant value.

We have PagerDuty integrated with it, as well as all of AWS. Those are the big ones we have running through it. It integrates well. It essentially replaces CloudWatch, so we can just use Datadog, which is nice. The biggest thing that they provide is putting everything in one spot.

I have just used the AWS version.