We use it mostly for logging log messages from our Kubernetes and EC2 instances, for example, system messages and errors. Also, we want log messages from our firewalls and other network infrastructure in case of network issues. We intend to use it for application logging, et cetera, to get insight into internal problems in the applications in Kubernetes pods. We want to use it for monitoring in case of system problems and hardware failures so that it can notify us.
Sr Platform Engineer at a pharma/biotech company with 11-50 employees
Good logging with lots of great integrations and an interesting dashboard
Pros and Cons
- "Datadog has a lot of features to be able to drill down deep into the swath of logs that our platforms generate."
- "Some of the interface is still confusing to use."
What is our primary use case?
How has it helped my organization?
It's good to have a single location for all the logs. If you have logs coming from a whole lot of sources, it makes it hard to find where the problem lies.
We had to spend a lot of time logging into various systems and pursuing a billion different log files looking for something that stands out as a possible cause of the issue. That can take a lot of time and doesn't give much visibility into the possible interactions between systems.
What is most valuable?
Datadog has a lot of features to be able to drill down deep into the swath of logs that our platforms generate.
It has a lot of ability to make fancy and deep searches using regular expressions and to graph them into useful and interesting dashboard graphs.
The plethora of built-in/downloadable integrations make it much easier to set up for our platforms. Otherwise, we'd have to parse the log files ourselves, which would take a great deal of effort. Had to do it before when had to use an ELK stack for logging, which was painful.
What needs improvement?
Some of the interface is still confusing to use. It has many features, and it takes a lot of effort to figure out what they all mean. Maybe having tooltips or something would be helpful. Also, some of the integrations are better than others.
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March 2025

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For how long have I used the solution?
I've used the solution for a month.
What do I think about the stability of the solution?
The solution seems very stable.
Which solution did I use previously and why did I switch?
Have used an ELK stack before. However, it took a lot of effort to maintain, and parsing the logs was difficult.
How was the initial setup?
We implemented the solution in-house.
Disclosure: I am a real user, and this review is based on my own experience and opinions.

support Eng
Helpful dashboards with a good cloud security posture manager and cloud workload security
Pros and Cons
- "It helps us better manage our logs."
- "They should continue expanding and integrating with more third-party apps."
What is our primary use case?
We use the application for our application monitoring, data security monitoring, and log management. What we like about the application is that it helps us to track issues more proactively instead of reactively.
There are other improvements we would like to see.
1. Being able to restrict users from seeing or viewing specific dashboards once they log in
2. They can cut down the prices for Cloud SIEM. It seems very useful, however, the prices are high. Some organizations are finding it difficult to make decisions in terms of getting the tool.
How has it helped my organization?
We use the application for our application monitoring, data security monitoring, and log management. It helps us to track issues proactively instead of reactively.
It helps us better manage our logs.
We can effectively track down issues.
We have dashboards that give us an overview of our environment.
What is most valuable?
The tools I have found useful include the Datadog cloud security posture manager and cloud workload security.
What needs improvement?
Datadog is a great tool, and we value the services they offer. They should continue expanding and integrating with more third-party apps.
For how long have I used the solution?
I've used the solution for three years.
What do I think about the stability of the solution?
I love its stability.
What do I think about the scalability of the solution?
It is very scalable.
How are customer service and support?
Technical support has been great.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We previously used AWS.
How was the initial setup?
The initial setup is not too complex.
What was our ROI?
We've seen an ROI of 50%.
What's my experience with pricing, setup cost, and licensing?
It's a little pricy yet worth it.
Which other solutions did I evaluate?
We did not previously evaluate another solution.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Buyer's Guide
Datadog
March 2025

Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
844,944 professionals have used our research since 2012.
Sr. Director of Software Engineering at a tech consulting company with 1,001-5,000 employees
Helpful support, good incident management, and helps triage faster
Pros and Cons
- "The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support."
- "The pricing is a bit confusing."
What is our primary use case?
The RUM is implemented for customer support session replays to quickly route, triage, and troubleshoot support issues which can be sent to our engineering teams directly.
Customer Support will log in directly after receiving a customer request and work on the issue. Engineers will utilize the replay along with RUM to pinpoint the issue combined with APM and Infra trace to be able to look for signals to find the direct cause of the customer impact.
Incident management will be utilized to open a Jira ticket for engineering, and it integrates with ITSM systems and on-call as needed.
How has it helped my organization?
The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support.
The RUM is implemented for customer support. It can quickly route, triage, and troubleshoot support issues that are sent to our engineering teams.
Customer support can log in and start troubleshooting after receiving a customer request. The replay and RUM help pinpoint the issue. This functionality is combined with APM and Infra trace to be able to look for the cause of the issue. Incident management is leveraged to open a Jira ticket for engineering, and it can integrate with ITSM systems and on-call as needed.
What is most valuable?
RUM with session replay combined with a future use case to support synthetics will help to identify issues earlier in our process. We have not rolled this out yet but plan for it as a future use case for our customer support process. This, combined with integrated automation for incident management, will drive down our MTTR and time spent working through tickets. Overall, we are hoping to use this to look at our data and perfection rate over time in a BI-like way to reduce our customer support headcount by saving on time spent.
What needs improvement?
I would like to see retention options greater than 30-days for session replay. I'd also like to see forwarding options for retention to custom solutions, and a greater ability to event and export data from the tooling overall to BI/DW solutions for reporting across the long term and to see trends as needed.
For how long have I used the solution?
I've used the solution for about nine months.
What do I think about the stability of the solution?
So far, stability has been great.
What do I think about the scalability of the solution?
I'd like to see more bells and whistles added over time. Widgets are coming soon to help with RUM.
How are customer service and support?
Support is very good. They are responsive and gave us the help we need.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We have utilized New Relic, however, not for RUM. We went with Datadog to potentially switch the entire platform into an all-in-one solution that makes sense for a company of our size.
How was the initial setup?
We started on the beta, and the documentation was lagging behind. We also needed direct instructions and links from the customer support/account representative that was not immediately available by searching online.
What about the implementation team?
We implemented the solution ourselves.
What was our ROI?
Ideally, this will inform our strategy to not increase our customer support headcount as significantly into 2023 and beyond.
What's my experience with pricing, setup cost, and licensing?
The pricing is a bit confusing. However, the RUM session replay, in general, is very inexpensive compared to whole solutions.
Which other solutions did I evaluate?
We looked into LogRocket and New Relic.
What other advice do I have?
I'd advise other users to try it out.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Cloud Specialyst at a financial services firm with 501-1,000 employees
Centralized with good observability and many modules
Pros and Cons
- "The most valuable aspect is for us to have everything in one place."
- "We need a lot of modules since we collect all data logs from all operating systems."
What is our primary use case?
We collect all data logs from all operating systems, such as Windows, Linux, VMware, and bare metal data centers. We also automatize the installation of the agent on servers.
Now we are starting a POC to analyze the APM module. In the feature, the next step is to do a POC of security modules.
The final idea is to have a unique portal for observability. This will make it easy to troubleshoot and for layer levels 1 and 2.
How has it helped my organization?
We are looking into a lot of modules. We collect all data logs from all operating systems, including Windows, Linux, VMware, and bare metal data centers. We also automatize the installation of the agent on servers.
We're developing POCs for APM and security modules. We'll also have a unique portal for observability. This will make it easy to troubleshoot.
The most valuable aspect is for us to have everything in one place.
What is most valuable?
We're investigating many modules. We collect all data logs from all operating systems (Windows, Linux, VMware, and bare metal data centers). We also automatize the installation of the agent on servers.
We're doing POCs in APM and security.
Soon, we'll have a unique portal for observability. This will make troubleshooting easy at levels 1 and 2.
The most valuable aspect for us is to have everything in the same place.
What needs improvement?
We need a lot of modules since we collect all data logs from all operating systems.
The most important module for us is log management. The second is the security module. The third one is the APM.
For how long have I used the solution?
We've used the solution for one year.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Sales Engineer at Delfia
Great Logging, APM, and RUM capabilities
Pros and Cons
- "The CCM, Workflows, Logs, APM, and RUM are all useful aspects of the solution."
- "We have contact with many customers that cover many areas, so we have cases where the infrastructure administration could be improved."
What is our primary use case?
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.
How has it helped my organization?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I've used the solution for three years.
Which solution did I use previously and why did I switch?
We used to use AppDynamics. We switched due to the fact that the cloud monitoring and K8 monitoring are not as good as Datadog.
What about the implementation team?
I'm a reseller.
What's my experience with pricing, setup cost, and licensing?
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.
Which other solutions did I evaluate?
We did not evaluate other solutions.
What other advice do I have?
We use the solution as a SaaS.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
SRE at a financial services firm with 10,001+ employees
Great visibility, easy to implement, and offers the ability to set thresholds
Pros and Cons
- "It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
- "Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog."
What is our primary use case?
We primarily use the solution for observability, metrics, logs, tracing, and end-to-end user flow monitoring.
We are looking to implement this as a company-wide standard for cloud solutions.
At this time, we're currently in a POC, and we're interested in using either a Datadog agent or the OTel agent with a Datadog exporter. We have dashboards with panels that correlate metrics and allow you to link through to traces. Flame graphs to show latency across services and the various spans.
While we are not security minded, we still require it and are interested in more. It's used for monitoring critical systems.
How has it helped my organization?
It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it. This provided a standard way to approach observability and visibility.
Monitoring rules and alerting thresholds can also be set and exported to other teams for use.
There is an issue with federated dashboards, as multiple teams running on different Datadog instances cannot use features like the service catalog or easily switch between services in a long business flow.
What is most valuable?
The K8 monitoring is extremely useful in Datadog. Preset dashboards that it provides help to speed up the work.
The metrics summary is useful. Tracing with a span breakdown is helpful for us. We like the dashboarding with power packs and logging correlation with traces and logs.
The Flame graph for tracing helps determine where the latency is the highest.
Dashboards are created as a standard set and then exported into other Datadog instances for other teams.
These dashboards would be updated regularly and pushed out to the teams. Unfortunately, there is no way to automatically push or deploy code in a quicker way. Each team I work with has its own Datadog instance.
What needs improvement?
Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog. Additionally, using an OTel agent would be more acceptable and allow for easier adoption of Datadog across the hundreds of teams here.
For how long have I used the solution?
I've used the solution for four months.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Technology Competency and Solution Head at LearningMate
Good infrastructure and traffic visualizations help with capacity planning
Pros and Cons
- "The error traceability is an area that can be improved."
What is our primary use case?
We use Datadog for application monitoring, to help identify errors. It is also used to monitor application performance.
It helps organizations to understand User Experience with user behaviour pattern
How has it helped my organization?
Helped to reduce production issues in a defined timeframe
Helped to refine UX
What is most valuable?
Datadog has a very good visualization for my complete infrastructure and network traffic, which enabled me to create a capacity plan.
This product is great because it shows you the SQL and your application request in a single view.
What needs improvement?
The error traceability is an area that can be improved. This is something that helps us to pinpoint the area where a problem is occurring. It is a function stack, and it should be showing us how each function is defined.
For how long have I used the solution?
We have been using Datadog for the past couple of Years.
What do I think about the stability of the solution?
I have not worked on it long enough to properly comment on stability, yet, because it has to be tested across my other platforms.
What do I think about the scalability of the solution?
We have not done a full evaluation yet, but given that it is cloud-based, DataDog has to be scalable.
How are customer service and support?
I have not needed to contact technical support.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We were using New Relic prior to implementing Datadog. In terms of application monitoring, Datadog is not up to the level that New Relic is. It is a better product but the price is too high, which is why we switched.
How was the initial setup?
Yes. It is not complex. It allows you to get a certification of DataDog prior deployment of associates to administration and configuration
What about the implementation team?
Inhouse. We got our Admin team certified.
What was our ROI?
Time to resolution production issue
What's my experience with pricing, setup cost, and licensing?
The price is better than some competing products.
Which other solutions did I evaluate?
NewRelic
What other advice do I have?
This is a good product and I can recommend it to others, although New Relic is still my first choice. Datadog is my second choice.
Overall, it is a good product and my main complaint is that it needs better error traceability.
I would rate this solution a nine out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Disclosure: I am a real user, and this review is based on my own experience and opinions.
DevOps Engineer at a printing company with 51-200 employees
Great visibility, good logs, and a helpful dashboard
Pros and Cons
- "For us to have visibility into our app stack and the hardware we run has been highly beneficial."
- "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."
What is our primary use case?
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.
How has it helped my organization?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I've used the solution for around six or eight months. We've had the Datadog agents deployed on our various environments.
What do I think about the stability of the solution?
So far, we have not had any issues with stability. It should be very stable and easy to update.
What do I think about the scalability of the solution?
The solution is currently deployed on a limited scale. That said, we see the potential and benefits of deploying this in a cloud scenario.
How are customer service and support?
Customer service and the support teams have been very responsive when we need them. They are very professional.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
This was our first solution in this space.
How was the initial setup?
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.
What about the implementation team?
We did an in-house implementation.
What was our ROI?
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.
What's my experience with pricing, setup cost, and licensing?
Ensure you have your ingestion pipelines dialed in, or you'll likely spend more than you were expecting.
Which other solutions did I evaluate?
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.
What other advice do I have?
There is nothing that the documentation cannot help with; it's very good.
Which deployment model are you using for this solution?
Private Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.

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