Datadog Reviews

After a security incident, we needed to find and migrate to a different cloud provider, and after evaluating different competitors and the skill set of the team, we decided to move to AWS. AWS also enables the team to have finer control over how our apps are deployed and how security and access are managed. By leveraging AWS's functionality, we have increased our application's security and sped up the deployment process. We've even been able to handle higher workloads due to AWS's auto-scaling functionality.

Elastic container services have improved our organization by allowing us to deploy our application. While this problem was not solved by using the elastic container service since we had a previous solution on a different provider, the ease and flexibility of deploys have greatly benefited the ops team and the overall engineering organization. It is easy to use. However, there are many out-of-the-box features like metrics and seeing task definitions that make life easier.

The most valuable feature I have found is the elastic container service. That is where our apps get deployed. This feature is really important to us since, without it, we would not be able to deploy our apps the way we wanted to and would have to use a different vendor. 

This service is also valuable to our team as we have a lot of familiarity with it and adapting to the services from our previous one was fairly seamless. 

Another feature that is very valuable for our team is the IAM. It allows us to control security.

ECS could be improved by including more tutorials for beginners to reduce the barriers to entry. It would help to ensure understanding and learning in terms of how to use a cloud provider. Besides this, there are not any other areas of improvement needed since the service is very straightforward and there is ample documentation.

I've used the solution for one year.

We are using the solution from a monitoring and management perspective. We use it for alerts.

The solution's real-time user management and session analytics as well as the APM, are the solution's most valuable aspects.

We could easily identify the production box, and we could handle alerts.

The initial setup is very straightforward. 

It's stable. 

They have flag integrations, mail integrations, and other options as well.

We didn't do a deep analysis on this at this moment to identify the disadvantages.

We have noticed that Session Replays are unavailable on the mobile app. We'd like mobile app integrations. They could have better log reporting. That said, almost everything that we require is there. 

We've only used the solution for two months. We just wanted to understand the complexities and the benefits that we might get from this product.

The solution is stable and reliable. The performance is good. There are no bugs or glitches. It doesn't crash or freeze. 

It may be scalable. However, we haven't actually tested anything. 

We have six or seven people on the solution at any given time. They're there to handle fixes or do an analysis of logs or monitor the infrastructure.

I'm not sure if we plan to increase usage. We are not growing very rapidly. We're just preparing our environment for the upcoming year. 

We've dealt with support. They are helpful and responsive. 

Positive

We have used AWS CloudWatch and AWS inbuilt application of the features, however, we thought that it will be good to have a separate application to do all these kinds of monitoring and to have something for handling alerting mechanisms.

We are looking for the best available platforms on the market, which also would give us better flexibility while having everything come from one place. We found that Datadog is good enough for now, and we are still exploring what it can do and our options. We are not completely in with Datadog. We've been exploring it only for four or five months.

It's an easy product to set up. The integration was very smooth and they have multiple options. It was pretty good integration-wise.

The setup itself only took a day or two. It doesn't take long. 

We handled the setup ourselves in-house. We did not need any outside assistance. 

For some features, it was quite expensive. For example, APM and RAM, and Session Replays. We are using it in a very limited way and are not using it for every microservice. We are using it for a minimal budget. As we are at an exploratory phase and are doing pay-as-you-go. Once we feel confident, we will likely get a yearly license. 

We are customers.

We're working on the latest version. I couldn't recall the version number.

I'd rate the solution six out of ten. I need to evaluate the solution further. 

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..

We use actual user monitoring and have set up thresholds for alerts to PagerDuty, Sentry, Slack, and so on. We also have dashboards set up for tracking latency and error rates. 

As an individual contributor, I also try to set up dashboards for the individual feature projects I work on. I'd like to learn more ways to use this, though, especially when it comes to more proactive approaches to issues. A starter pack of common-use types would be nice.

The solution it has improved our organization by expanding the awareness of issues and alerts beyond SRE and really empowering software engineers at a team level to make changes to monitoring and incident responses.

There could still be more training to bring this even further. A lot of the time I get into Datadog and it's already an incident and I am not in the right mindset to learn about the product or set alerts up.

The feature I have found most valuable is when I can reuse existing monitors and alerts for new dashboards. 

It is nice that things are so integrated, and any individual thing I build out can likely be re-used across the suite.

Other features I have found useful include the stack traces, especially when it links back to something specific I can look for in the code base. I also like that you can group similar alerts together to look for trends over time instead of one in isolation and see if there have been regressions.

The biggest improvement would be around educational content and helping new users get started. I've only been using Datadog for a few months, and at first, it was frankly overwhelming in terms of both the UI and the available capabilities. The workshops today have helped with this, however, more could be done.

As a user, I have about six or more months of experience with the solution. As a company, I'm not sure.

I was not in charge of evaluating any other solutions.

We use Datadog to monitor our product on the cloud.

The performance of Datadog is good.

Datadog has a lot of features kind of cramped into one dashboard. It's quite hard to get around what feature does exactly what. There was a steep learning curve, trying to navigate through menus.

The menu navigation could improve. If there was a more straightforward way of adding new functions or features to where each menu is placed that would be an improvement.

I have been using Datadog for approximately six months.

The solution is stable.

The scalability of Datadog is pretty good. However, we haven't arrived at the level that we need to test out the scalability.

We have five people using the solution.

I have not used the support from Datadog.

We have not used other solutions previously.

The initial setup is straightforward, and the process took approximately three days.

We have approximately six people that implement and support the solution.

Sometimes it's very hard to project how much it will cost for the monthly subscription for the next month when you add certain features.  Having better visibility of the cost would give a better experience.

There are not any additional costs for the use of this solution.

I would recommend this solution to others.

My advice to others is to use a few features of the solution before going full scale.

I rate Datadog an eight out of ten.

I am using Datadog for error reporting.

I have found error reporting and log centralization the most valuable features. Overall, Datadog provides a full package solution.

I have been using this solution for approximately three years.

The solution is stable.

I used to process a million requests easily with Datadog, I never had any scalability issue.

I have not needed to contact support.

The initial setup is easy.

Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs.

I rate Datadog a nine 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 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.