Datadog Reviews

We primarily use this product for availability and performance monitoring, log aggregation.

Datadog gave us awesome visibility across all of our applications.

The most valuable features are logging, the extensive set of integrations, and easy jumpstart.

In the past two years, there have been a couple of outages.

We have been using Datadog for two years.

The outages that we have had in the past two years were fixed in a matter of minutes.

So far we did not have any issues with scaling, and everything is working great.

Support is awesome.

We did use NewRelic, but the logging feature was not as good as it is in Datadog.

The initial setup is straightforward and everything is very well documented and easy to start using.

We implemented it in-house.

We evaluated a custom ELK solution, Sumo Logic, and Logentries.

Datadog is already covering much more than we normally need with exceptional quality. This is a great product.

Our primary use of Datadog includes: 

• Keeping a close look into our AWS resources. Monitoring our multiple RDS and ElastiCache instances play a big role in our indicators.
• Kubernetes. We aren't using all of the available Kubernetes integrations but the few of them that work out of the box adds great value to our metrics.
• Monitoring and alerting. We wired our most relevant monitoring and alerts to services like PagerDuty, and for the rest of them, we keep our engineers up to date with constant Slack updates. 
  

Observability is something that a lot of Companies are trying to achieve. Having a clear view, not only of our infrastructure but our apps and services as well, has brought a great added value to our customers.

For a logging solution, we use to have Papertrail. It did the trick but having a single point that manages and indexes all the logs is a BIG improvement. Also, having the option to generate metrics from logs is a game-changer that we're trying to include in our monitoring strategy.

I would like to say the same about APM but the support for PHP seems to be somewhat lacking. It works but I think this service could provide us more information.

With respect to logs, we used to integrate various kinds of tools to achieve very basic tasks and it always felt like a very fragile solution. I think logs are by far the most useful feature and at the same time, the one that we could improve.

APM - This is either a hit or miss, allow me to explain: we use various programming languages, mainly PHP and Ruby, and the traces generated don't always provide all of the information we want. For example, we get a great level of detail for the SQL queries that the app generates but not so much for the PHP side. It's hard to track where exactly where all of the bottlenecks are, so some analysis tools for APM could make a good addition.

Please add PHP profiling; you already have it for other popular programming languages such as Python and Java, which is great because we have a little bit of those, but our main app is powered by PHP and we don't have profiling for this yet. I guess it's only a matter of time for this to be added, so in the meanwhile, you can consider this review as a vote for the PHP profiling support.

The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances.

We have been using Datadog for one year.

It's pretty stable for the main integrations. There was only one time where Datadog was down and that was scary since all of our monitoring is handled by Datadog. There was a lot of uncertainty while the outage was in place.

For everyday use, it's adequate, but for very specific tasks, not so much. There was a time where I had to do a big export and as expected, the API is somewhat limited. Since it was a one-time task, it was not a big deal but if this was a regular task, I wouldn't be happy about it.

For small tasks, I think it's great. For specialized support, it feels like you're under-staffed, having to wait days/weeks for a solution is a big NO-NO.

I've used a few other products such as NewRelic and AppDynamics. The switch is usually affected by two factors: pricing and convenience.

Getting APM metrics out of Kubernetes is always a painful task. We got support to take a look at this and we had to go through various iterations to get it right, and then AGAIN the next year. This was a bad experience.

It was all implemented in-house. The documentation is fairly up to date, for the most part.

Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick.

Unfortunately, it wasn't my call to include Datadog for this Company but sure I'm glad that the Lead Architect took this decision. It brought many improvements in a small span of time.

Please add PHP profiling soon!

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.