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 use the solution for monitoring time spent on views and events triggered. For example, for one of our products, we have created a custom dashboard that lets us track all the custom events and multiple entry points in the same part of the application.

Knowing the entry point helps us choose which part of the program should be improved next. It also helps us with collecting important data about the overall usage of each module within our application. 

The solution has helped our organization with custom events to track specific cases.

It's helped with monitoring time spent on views and events triggered. For example, for one of our products, we have created a custom dashboard that lets us track all the custom events as well as multiple entry points into the same part of the application.

Knowing the entry point helps us choose which part of the program should be improved. It's collecting important data about the overall usage of each module within our application. 

The most valuable feature is the custom events to track specific cases.

Monitoring time spent on views and events can be triggered. For example, for one of our products, we have created a custom dashboard that lets us track all the custom events and multiple entry points in the same part of the application.

Knowing the entry point helps us decide on improvements. We can collect important data about the overall usage of each module within our application. 

We look forward to the next features from Datadog. We need to learn more about the session reply feature inside of DD.

I've used the solution for two years.

We primarily use the solution for monitoring and telemetry.

We use lots of log collections, log-based metrics, and dashboard visualization.  The logging, metrics, and APM are vital.  

My team focuses on the backend. Day-to-day monitoring includes observing metrics such as the CPU and memory until it gets too high. This solution provides an alert during the metric collection.  

APM and tracing are super useful. We use it for daily monitoring of CPU and memory. We can get alerts to tail to specific metrics.

We also find the tracing feature useful. We often run into bugs, and when a production issue happens, it is super useful to see the related services and sense where the problem is.

We would like to see smaller or shorter tutorials and video sessions. Also, the ability to provide a custom formula for monitoring is vital. Perhaps there can be more training materials on this. We often need to detect slow-running queries and slow network responses. We also focus a lot on the abuse of request limits. Having some form of rate limit features or metrics would be useful.  

Profiling could also be useful. Some services are CPU-intensive, and others are IO-intensive. Knowing where the bottleneck is, is crucial. 

We mostly use it to handle log aggregation, monitor our web application, and alert us on data pipeline failures. 

Our system is fully on AWS, and so we pipe in all of our Cloudwatch logs into Datadog to have a central place to index and search logs. 

Our web app is built on an Elastic Beanstalk backend, and we use the Datadog agent to keep track of all of the requests that hit our backend and all of their components. 

We also use the prebuilt AWS pipeline dashboards to monitor our batch jobs and lambdas.

Datadog has made it much easier to have a central place for people to look for logs and made it much easier to notify them of any elevated error rates or failures. 

It is also easier to get high-level views of platform health, whereas looking directly at AWS tends to provide very specific insight into particular surface areas or products. 

By having the whole team onboard onto Datadog, we also have a single source of truth that everyone can use when triaging and resolving incidents that occur across any surface area.

The ease of setting up metrics and alerting and integrating with Slack has significantly reduced the friction of keeping the team up to date on the platform's health. Before creating custom Cloudwatch metrics was never very intuitive, and also it was non-trivial to set up integrations with other services we use, especially Slack. 

It also provides a good way to gain the context needed when trying to fix issues, as it's a central place to look through logs, requests, AWS metrics, and more - overall contributing to the health of our platform.

The product is quite complex, and there are so many features that I either didn't know about or wasn't sure how to use.

One thing that could be improved is somehow surfacing interesting or relevant products that might be applicable given our infrastructure. 

Additionally, the billing can sometimes be confusing and opaque, especially around not making it obvious what the implications can be if you add different AWS integrations. This has caused some unexpected costs in the past due to engineers not understanding how Datadog pricing works.

We've used the solution for around two years.

This was the first solution we tried.

It is quite expensive, especially if you don't know how the pricing works.

We implement these solutions for our clients. We have implemented Datadog as an SIEM solution.

Because of our client focus, it is easy for us to sell. This is because it is easy to use and easy to set up.

While I like the ease of use, when compared with Tenable Nessus they could still improve their usability. They are okay, but there is room to be better.

They could have more integration.

They could be more intuitive as well. For example, the intuitivity of the user interfaces, and how long it takes for users to learn how to use Datadog.

It is not impossible to use, or impossible to do the administration with it but when you put these two next to each other, meaning Nessus and Datadog, Nessus comes out as the winner.

I have been using Datadog for two years.

We are not using the latest version, we have missed at least one update.

We have no issues with the stability of Datadog.

Datadog is a scalable product.

We have two customers who are using this solution.

Technical support runs 24/7. The technical support is absolutely fine.

We are also using Nessus. My experience using Tenable Nessus is better.

It is easier to install than to use it.

I was not the one doing the handling the installation. I'm a senior consultant, and I was coordinating, planning, and interacting with clients. But the actual installation, I was not involved with. 

The installation could be done in an hour or so.

It is not complex, two professionals are enough to complete the installation and maintenance of Datadog.

With Datadog, it's a monthly fee. They prefer monthly subscriptions.

I would recommend this solution for medium enterprises with 100 to 1,000 employees. 

Small business is too small for the way that Datadog operates. It is not the best for very large enterprises for a company with more than 1,000 employees.

I would rate DataDog an eight out of ten.

Our clients use it for monitoring applications. Its deployment depends on our customer's use case. 

It is 100% cloud. We have got a multi-tenant environment, so we segment it out.

It helps us to be more proactive. We can help customers with their e-commerce applications for any networking issues. We can also help them in any area from a development standpoint. It could be a non-prod environment where they're going through testing and various functionalities. It helps them be able to be more successful with their deployments.

The visibility that it provides is valuable. It is helping in being proactive around incident management. It is helping us to be able to get more visibility into our customers' applications so that we can assist them at the application layer. We also provide them the infrastructure from an AWS standpoint. We are able to make sure that our customers are aware of certain critical things around the analytical piece of either the network or the application. We're able to call customers before they even know about the issue. From there, we can start putting together some change management processes and help them a bit.

It can have a more modernized pricing mechanism. We're actually working with them to figure out how to become more modular and have a better and more modernized pricing mechanism. The issue with Datadog is that you have to buy the whole suite of different products, and you kind of get stuck in the old utilization of 40% of their suite. Most organizations today break down between application development, networking, and security. Therefore, there should be a way to break down different modules into just app dev, infosec, networking, etc. Customers have various needs across their business lines, and sometimes, they're just not willing to have tools that they're not using 100%. AppDynamics is probably a little bit better in terms of being modular.

I have been using this solution for almost four years.

We haven't lost any customers for Datadog. It must be stable.

As long as you're willing to pay for 100% but utilize only 40%, it can scale and do anything you want. In an organization, its users are usually the app group, the security group, and the network group.

We're certified in Datadog, and we have our own internal engineers to support the customers. We handle steps two and three.

It is usually pretty complex. 

It has a module-based pricing model.

I would advise others to review the overall functionality. If you're looking for different APN tools, then Datadog is a good tool. If you're not looking for it to handle all aspects of your environment and your application from the security infrastructure aspect, there are other tools out there that you could possibly utilize for each one of those areas. 

We do a lot of proof of concepts in helping our customers understand the micro and macro pieces of deployment. We're able to be a true advocate and value-add for our customers in utilizing the tool.

I would rate Datadog a seven out of ten. This space is a very competitive space, and a lot of organizations are trying to figure out how to become better in the full life cycle of a deployment. There'll be a lot of changes for different companies going forward.

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.

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.