Datadog Reviews

We primarily use the solution for the RUM, security monitoring, and streams.

We need to monitor users and what they access. We also need to identify security loopholes and attack patterns and identify and quickly respond to issues.

We can identify pushbacks, and get insight into application components that stack up with each other. We can understand which components, libraries, and code to alert teams.

Using Datadog, we can raise incidents, track incidents to completion, and be able to gather data for reporting and post-mortem.

The solution allows us to track fixes and tracks their test coverage. With it, we get confidence in the fix/improvement phase and be able to provide a response.

The solution has improved the organization by providing good insights into app performance and offering good dashboards.

With it, our company can track fixes and track test coverage. We get confidence in the fix/improvement and are able to provide a response.

I've been able to present data to the team/ management based on the team's dashboards.

It's helped us when we've needed to monitor users and what they access or needed to identify security loopholes and attack patterns. It can help identify and quickly respond to issues.

Datadog allows us to identify pushbacks, and get insight into application components (how they stack up with each other). When we need to know which component, libraries, code, and teams to alert, we can raise and track incidents to completion and gather data for reporting and post-mortems.

The APM and container monitoring are excellent aspects of the solution.

It helps with monitoring users and what they access.

We can identify security loopholes and attack patterns while quickly responding to issues.

Our team can now identify pushbacks and get insights into application components. We can gather data for reporting and post-mortem, and we can track fixes and test coverage. Datadog allows us to gain confidence in the fix/improvement.

I've been able to present data to the team/ management based on the team's dashboards.

We'd like Datadog to make the log storage cheaper. Right now, it makes our life difficult since logs are stored separately.

We should not have to rely on team members to educate themselves in Datadog features. There should be templates that anyone can select, and they should be able to create dashboards easily. This is really slowing us down. It takes time to to explore the full potential of Datadog.

I've used the solution for two years.

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.

Log aggregation for us was a key component since we have a fairly old-school app running on VMs on bare metal. We previously didn't have much insight into our logs unless we manually tunneled them into each server.

The solution is reducing manual labor in troubleshooting problems in our environments server by server.

We also needed to monitor our Java app and MySQL database to understand their problems so that we could take action and resolve them.

Our use cases have since expanded to encompass all aspects of monitoring.

Before Datadog, all we had to go on was the gut reaction of the old guard on our team. While useful, the reactions and inherent knowledge only benefited a few folks.

Datadog has allowed us to create comprehensive dashboards and proactively send out alerts. We used the knowledge of people very versed with our products to help set up the platform and have since benefited from that.

The operative word here is visibility, and we've seen a huge improvement in that.

Seeing log trends and patterns and aggregate search was a huge first step for us. We then began using other features of the Datadog platform by enabling APM. After that, we did other integrations.

For us to have visibility into our app stack and the hardware we run has been highly beneficial.

We leverage APM, log management, and at least ten other integrations. Our DB, web servers, network, storage, and other areas are now monitored and hooked up to dashboards.

Dashboarding has also proven useful when information is going to be viewed by anyone in the organization.

Our experience has been overwhelmingly positive so far. That said, there is one area that could benefit from some polish. For example, I want to applaud the efforts in making the UI extremely usable and approachable. My suggestion would be to take another look at how the menu structure is put together, however. Even after using the platform mostly every day for months, I still find myself trying to find a service or feature in the menus.

I've used the solution for around six or eight months. We've had the Datadog agents deployed on our various environments.

So far, we have not had any issues with stability. It should be very stable and easy to update.

The solution is currently deployed on a limited scale. That said, we see the potential and benefits of deploying this in a cloud scenario.

Customer service and the support teams have been very responsive when we need them. They are very professional.

Positive

This was our first solution in this space.

The initial setup steps with the agent are only confusing when using the config files for the first time. The main file includes a lot that you can specify elsewhere and it's not readily apparent which one to use until you dig in more.

We did an in-house implementation.

Our ROI with Datadog has been very high. It's given us the ability to see how we're performing, which we didn't have before.

Ensure you have your ingestion pipelines dialed in, or you'll likely spend more than you were expecting.

We evaluated free and open-source options, however, ultimately, we decided that we didn't have the manpower as a small company to maintain them.

There is nothing that the documentation cannot help with; it's very good.

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. 

We’re currently using logging, monitoring, metrics, APM, etc.  

We've started to use קSLOs. However, it takes a bit of time to work through those.

RUM (Real User Monitoring) has been very useful. I have used this in the past to debug problems in production, which has been great.

We also want to start using synthetics and tracing more. 

Our application currently runs in many different environments based on our customers' requirements. This allows us to see everything in one place and still filter by the environment as required, which is extremely useful. 

The solution has offered increased visibility via logging APM, metrics, RUM, etc. Going from almost nothing to something that didn’t take a lot of time to set up has been great since we have so little time to spare

As a startup, we have limited resources, and no one has enough time for anything. There are so many easy integrations and things configurable by YAML making everything easy to set up without needing a full-time employee. Just configuring monitoring solutions is very desirable. 

The APM is very useful for tracking down anything that’s gone wrong. I’ve been using it to make sure everything is working correctly after deployment, to make sure we don’t suffer performance degradation, and to track down anything that’s gone wrong in real-time  

The logs are great and necessary for any application. Before this, our solution would have been to SSH into a machine and tail log files. This is untenable for many reasons, and one of the first things I wanted to change.

The RUM is useful for seeing how real users interact with our website.

Sometimes it’s difficult to customize certain queries to find specific things, specifically with the logging solution. I’ve used other logging platforms in the past that have extensive and mature query languages, which might not be super friendly to start out with, yet they can be very powerful. I wish there was more of an emphasis on that instead of the UI-based tooling that Datadog provides. Even though it is powerful on its own, UI-based design lacks the elegance, efficiency, and complexity that something like that can provide. 

I've been using the solution for six months or so.

We did not previously use a different solution.

I don’t handle the licensing or pricing.

We did look into Splunk.

We primarily use the dashboard/metric with many tags.

It makes the system easier to debug. 

We really like the charts and visualization.

Sometimes, it takes a long time to load the dashboard if we have many charts.

I've used the solution for five years.

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. 

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.