Datadog Reviews

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 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 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. 

I'm a Datadog partner in Brazil, and I monitor all my applications with Datadog too. I would like to enable all features in my DPN portal and get access to custom demos. We resell Datadog and a full stack of pre-sales, sales, and post-sales services. We have customers for all sectors, including governmental, financial services, services in general, telecom, et cetera. Today, we are the biggest Datadog partner in Brazil, and we are searching for an expansion in our MSP environment.

I resell all solutions in Datadog, so all features are important for our customers.
We are the biggest Datadog partner in Brazil, and we would like to expand our MSP environment.

The CCM, Workflows, Logs, APM, and RUM are all useful aspects of the solution. I resell all solutions in Datadog, so all features are important.

I'm a Datadog partner in Brazil, and I monitor all my applications with Datadog too. 

The solution works within all sectors, including, governmental, financial services, services in general, and telecom. 

We have contact with many customers that cover many areas, so we have cases where the infrastructure administration could be improved. In general, cloud users and microservices users like Kubernetes offer a faster improvement in the environment. Our users of the feature logs had a lot of benefits and found cost reductions also.

I've used the solution for three years. 

We used to use AppDynamics. We switched due to the fact that the cloud monitoring and K8 monitoring are not as good as Datadog.

I'm a reseller.

The licensing model is better, however, if they had the option to block consumption in the Infra and APM, that would help to keep better control of costs.

We did not evaluate other solutions.

We use the solution as a SaaS.

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 solution for charting application metrics.

We use it for all our application metrics, host metrics, and monitors with a PagerDuty integration. 

We integrate our application logs. It is great to be able to tie our metrics and our traces together.

We use the APM module with traces. It is great to be able to link APM, logs, and metrics in one go, as it shortens our troubleshooting and RCA dramatically.

We are loving the tool; it is great to have all those insights in one place. 

We hope that they keep making my life and our engineers' life easier.

The solution improved our organization with:

• Data-driven decision making
• Dashboards we can share with our customer success team
• Dashboards we can share with our sales engineers
• Help during incidents
• Help with preventing incidents
• Integration with PagerDuty.

The most valuable aspects of the solution include:

• The charting application metrics
• help with the business, prioritization, software design, and infrastructure design.

The pricing model hurts and forces us to work around the tool sometimes.

On top of application performance metrics, it would be great to have host performance metrics, suggesting changes to better use a cluster like: "You are over-provisioning this host" or "based on historical data, you will need to scale up in X days."

Adding a module to extract data from Datadog so we can use the data in our own system would be helpful.

I've used the solution for six or more years.

We previously used New Relic, which was a great tool. That said, Datadog is a more complete solution.

The pricing should be less of a surprise. They should allow us to cap costs which would lead to less frustration.

We need better documentation on the pricing.

It might be helpful if they added a pricing simulator.

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.