We run the agent in AWS.
Software Engineer at a computer software company with 51-200 employees
Excellent autocomplete for everything in the UI
Pros and Cons
- "Excellent autocomplete for everything in the UI."
- "It has empowered all our platform engineers with a very powerful and easy to use monitoring system."
- "Going from viewing a metric to creating a monitor alerting on a metric is very easy."
- "The web app has a real-time support chat window in which a support engineer is chatting with you within a minute."
- "It would be nice to be able to graph metrics by excluding certain tags (like you can do in monitors)."
- "It would also be nice if we had more insight into our own usage of Datadog (agents and custom metrics). They provide a usage page which does help, but it is not in real-time."
- "It would be great if usage metrics were automatically created and we could create custom metrics, instead we ended up building some of our own stuff to track and alert on our own usage."
What is our primary use case?
How has it helped my organization?
It has empowered all our platform engineers with a very powerful and easy to use monitoring system. Most of our platform organization is now involved in monitoring. Previously, only a handful of platform engineers were involved, because Graphite and Sensu were so cumbersome to use.
What is most valuable?
It is incredibly easy to do common monitoring actions:
- Excellent autocomplete for everything in the UI.
- Using tags is very intuitive (in contrast to the cumbersome regex-like based querying in Graphite).
- Going from viewing a metric to creating a monitor alerting on a metric is very easy. This is very important as the easier it is to create monitors, the more monitors will be created by people. With Graphite and Sensu, the effort required to create and test a monitor was so great that we had only a handful of monitors. We now have over 300 monitors.
What needs improvement?
- It would be nice to be able to graph metrics by excluding certain tags (like you can do in monitors).
- It would also be nice if we had more insight into our own usage of Datadog (agents and custom metrics). They provide a usage page which does help, but it is not in real-time.
- It would be great if usage metrics were automatically created and we could create custom metrics, instead we ended up building some of our own stuff to track and alert on our own usage.
Buyer's Guide
Datadog
March 2025

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For how long have I used the solution?
One to three years.
What do I think about the stability of the solution?
Very rarely. Maybe only once or twice that we noticed. It is very reliable.
What do I think about the scalability of the solution?
No.
How are customer service and support?
It is excellent. The web app has a real-time support chat window in which a support engineer is chatting with you within a minute. That is the "right" way to do support.
Which solution did I use previously and why did I switch?
We previously ran Graphite and Sensu ourselves. By moving to Datadog, we did not need to manage our own monitoring infrastructure anymore. Graphite was somewhat complex to run.
How was the initial setup?
Initial setup is easy. Install the agent and send it metrics. There are StatsD/Datadog libraries available for most languages.
What's my experience with pricing, setup cost, and licensing?
Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure. It is hard to say without looking at all of this.
Which other solutions did I evaluate?
We looked at several competitors at the time (Summer 2016). There did not seem to be any compelling alternatives. Once we did the PoC with Datadog, we loved it and decided to move forward.
What other advice do I have?
Try it out and see if you like it.
Disclosure: I am a real user, and this review is based on my own experience and opinions.

Software Engineering Manager at a healthcare company with 501-1,000 employees
Great CI visibility, logging, and monitoring
Pros and Cons
- "Datadog helps us detect issues early on and helps in troubleshooting."
- "We would really like to see more from the Service Catalog."
What is our primary use case?
We mainly use the product to monitor our infrastructure and apps. It is the go-to tool when we want to check that things are running properly. We use Datadog synthetic monitors to ensure our app works across different locations in the United States.
We also have set up Datadog monitors to send alerts if things stop working as expected.
We use Continuous Integration Pipeline visibility to make sure our developers are not being blocked by infrastructure and other things that might be out of their control.
How has it helped my organization?
Datadog helps us detect issues early on and helps in troubleshooting. Creating Service Level Objectives and defining monitors is helping us to stay on top of potential issues that might affect our users.
We take advantage of Application Performance Monitoring to ensure our applications are working as expected, and our users can get the healthcare they need at a price they can afford.
Synthetic monitoring also helps us in testing our application in different browsers.
What is most valuable?
The most valuable aspects of the solution include:
CI visibility, which helps us in making sure our CI systems are running efficiently and are not blocking our developers from releasing new software and fixing bugs.
Logs, which help us in debugging issues where we can search for logs and can make sure they are relevant to the issues we are looking at.
APM, which can help us to stay on top of our applications by giving us the confidence that our apps are running.
Monitoring. We use monitoring a lot to ensure we know about potential issues and fix them before they affect our customers.
What needs improvement?
Overall, we really like the quality and relevance of all of the Datadog products that are currently being used.
The documentation is very well organized and is the go-to place for us to find answers to our questions.
We would really like to see more from the Service Catalog. It is something that we are interested in. However, some might think it lacks some key features at this time. We will definitely keep our eye out for this and adopt it when all the features are implemented.
We're really looking forward to all the great things DD will do.
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?
The stability is great.
What do I think about the scalability of the solution?
The scalability is great.
How are customer service and support?
Technical support is great.
What about the implementation team?
We handled the initial setup in-house.
What's my experience with pricing, setup cost, and licensing?
I don't have any insights into pricing.
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.
839,422 professionals have used our research since 2012.
Associate at a financial services firm with 10,001+ employees
Great for debugging with good UI and helpful filtering capabilities
Pros and Cons
- "It is easy to navigate the menu and create tests."
- "This service could be less costly."
What is our primary use case?
We use the product for recording loggers on our various services across different teams. For example, we use logs to keep track of info logs for events and error logs to catch exceptions.
When users ask us to investigate a situation, we use logs to keep track of events and where the user's code traveled to. We also use synthetic testing and monitoring features to keep track of our many alerts in the production and QA environments.
How has it helped my organization?
We use Datadog mainly for debugging purposes. For example, we use it to navigate where the code trace is when an issue arises due to its ability to search through the logs.
We also use it to address user queries. Sometimes users would ask us a certain question concerning our codebase, we use Datadog to track the code stack and also use time monitoring to get an idea of the time frame around when the use case happened.
What is most valuable?
The feature I have found to be the most valuable is the filtering feature in logs. It is really easy to type plus and minus to filter out different logs. I use it to navigate the noise.
I use synthetic tests as well. It is easy to navigate the menu and create tests.
Much of the UI is very straightforward, and I do appreciate the ability to search for any documentation on the various features when I need to as well. The DASH monitoring boards are nice to give an overview of various performances and allow us to track use cases.
What needs improvement?
This service could be less costly. Right now, we only keep 15 days worth of logs since we want to be more economical in terms of cost. It would be nice if I had the option to monitor logs beyond 15 days. For APM traces, we only keep a year worth of traces. The UI can be a little more straightforward as well. I found it to have too many options.
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?
The stability is good.
What do I think about the scalability of the solution?
The scalability is good.
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.
Infrastructure Engineer at a tech services company with 11-50 employees
Easy to use, simple to set up, and allows for easy visibility
Pros and Cons
- "Datadog has so far been a breeze to use and set up."
- "One thing we have run into is that it is so easy to add monitoring that we turn on things without really understanding the costs."
What is our primary use case?
We currently use it for log aggregation and SEIM. We send logs from our AWS account (particularly our Cloudtrail and S3 logs) and use them to give us security signals.
This has helped with our SOC2 certification process and has given us a window into our processes and the security holes in our system.
We are also considering using the APM features to help with our development effort. We want to be able to profile all of our code and see what is going on with it.
How has it helped my organization?
It has allowed us to see into our systems with ease. We are a very small startup (Less than 30 people, and most of them are in sales and marketing).
When it comes to managing systems, we just don't have time to do everything. However, Datadog has allowed us to do much more with fewer people and still sift through our data with ease.
We hope to start using the APM feature set to extend this to our dev teams as well.
What is most valuable?
The ease of use is the primary aspect. I have used, at previous jobs, the ELK stack and Splunk for log management. Both of them were useful, yet required a lot of manual effort to get set up (and a lot of continuing effort to tweak. A simple monitoring solution turned into a full-time job! However, Datadog has so far been a breeze to use and set up. It looks at what I am sending it and figures out what it is almost by magic. Even the manual configuration makes sense and gives very fast and thorough results
What needs improvement?
One thing we have run into is that it is so easy to add monitoring that we turn on things without really understanding the costs.
I would like a way to show a continuous indication of what my setup will cost on a daily or weekly basis.
For how long have I used the solution?
I've used the solution for six months.
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.
Staff Cloud Engineer at a energy/utilities company with 51-200 employees
Good infrastructure and APM metrics with easy onboarding of new products
Pros and Cons
- "We rely heavily on the API crawlers that Datadog uses for cloud integrations. These allow us to pick up and leverage the tags teams have already deployed without having also to make them add them at the agent level."
- "The real issue with this product is cost control."
What is our primary use case?
We are using the solution for migrating out of the data center. Old apps need to be re-architected. We plan to move to multi-cloud for disaster recovery and avoid vendor lockouts. The migration is a mix between an MSP (Infosys) and in-house devs. The hard part is ensuring these apps run the same in the cloud as they do on-prem. Then we also need to ensure that we improve performance when possible. With deadlines approaching quickly, it is important not to cut corners which is why we needed observability.
How has it helped my organization?
The product has created a paradigm shift in how we deploy monitoring. Before, we had a one-to-one lookup in service now. This wouldn't scale, as teams wouldn't be able to create monitors on the fly and would have to wait on us to contact the ServiceNow team to create a custom lookup. Now, in real-time, as new instances are spun up and down, they are still guaranteed to be covered by monitoring. This used to require a change request, and now it is automatic.
What is most valuable?
For use, the most valuable features we have are infrastructure and APM metrics. The seamless integration between Datadog and hundreds of apps makes onboarding new products and teams a breeze.
We rely heavily on the API crawlers that Datadog uses for cloud integrations. These allow us to pick up and leverage the tags teams have already deployed without having also to make them add them at the agent level. Then we use Datadogs conditionals in the monitor to dynamically alert hundreds of teams, and with the ServiceNow integration, we can also assign tickets based on the environment. Now, our top teams are using APM/profiler to find bottlenecks and improve the speed of our apps.
What needs improvement?
The real issue with this product is cost control. For example, when logs first came out, they didn't have any index cuts. This leads to runaway logs and exploding costs.
It seems that admin cost control granularity is an afterthought. For example, synthetics have been out for over four years, yet there are no ways to limit teams from creating tests that fire off every minute. If we could say you can't test more than once every five minutes that would save us 5X on our bill.
For how long have I used the solution?
I've been using the solution for about three years.
What do I think about the stability of the solution?
The solution is very stable. There are not too many outages, and they fix them fast.
What do I think about the scalability of the solution?
It is easy to scale. It's why we adopted it.
How are customer service and support?
Before premium support, I would avoid using them since it was so bad.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
We previously used App Dynamics. It isn't built for the cloud and is hard to deploy at scale.
How was the initial setup?
The initial setup was not complex. We just had to teach teams the concept of tags.
What about the implementation team?
We implemented the solution in-house. It was me. I am the SME for Datadog at the company.
What was our ROI?
We have seen an ROI. It has saved months of time and reduced blindspots for all app teams.
What's my experience with pricing, setup cost, and licensing?
We'd advise new users to be careful with logs, and the APM as those are the ones that can get expensive fast.
Which other solutions did I evaluate?
We looked into Dynatrace. However, we found the cost to be high.
Which deployment model are you using for this solution?
Hybrid Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Infrastructure engineer at a insurance company with 10,001+ employees
Good infrastructure, helpful logs, and useful alerts
Pros and Cons
- "It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
- "I sometimes log in and see items changed, either in the UI or a feature enabled. To see it for the first time without proper communication can sometimes come as a shock."
What is our primary use case?
Our use case is to provide cloud organization application monitoring. I use it for insight into what host in what region has activity or what market is using Datadog to its fullest potential and utilizing that for cost. This may also help determine who is using monitoring and setting alerts or just setting up monitoring and not doing anything about it. The use case can also be to check when the host or applications are down, or if the usage of CPU, memory, etc, is too high.
How has it helped my organization?
The solution has improved our organization from a market perspective. We have multiple departments and need some time to gather that data from a grouping point of view. Grouping that data via tag or seeing the separation is easy. In addition, it provides metrics and insights for senior leadership to have a high level of usage and cost. Application teams have better insight into their application, outages, when to plan for patches, updates, etc. Also, they have a better understanding of where the data gaps may be.
What is most valuable?
The infrastructure is the most valuable. It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers. It provides confirmation that the layer where the application is running is monitored and will be alerted when it is down and not functional. The customers can have ease of mind knowing their metrics are accurately being measured. The value of data provided, including service name, logs, and all other pertinent details tied to the host, makes it a valuable source of data
What needs improvement?
The solution can be improved via open communication to the broader audience on what has changed and what has not changed. I sometimes log in and see items changed, either in the UI or a feature enabled. To see it for the first time without proper communication can sometimes come as a shock.
For how long have I used the solution?
I have been using the solution for three years.
What do I think about the stability of the solution?
The stability is great.
How are customer service and support?
Technical support is great. Datadog has the resources and knowledge to tackle questions.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I did not previously use a different solution.
How was the initial setup?
The initial setup is straightforward.
What about the implementation team?
The initial setup was handled in-house.
Which other solutions did I evaluate?
I did not evaluate any other solutions.
Which deployment model are you using for this solution?
Hybrid 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.
Senior Cloud Engineer at a comms service provider with 10,001+ employees
Good platform monitoring and great cost and performance optimization
Pros and Cons
- "The observability pipelines are the most valuable aspect of the solution."
- "Geo-data is also something very critical that we hope to see in the future."
What is our primary use case?
We use the solution primarily for platform monitoring for the services that are deployed in AWS. It gives a better way to monitor the services, including pods, cost, high availability, etc. This way, observability is ensured and also customer services are uninterrupted.
Also, we host the data pipelines between the cloud and the on-prem for which Datadog is used to ensure better services. We report issues based on the metrics reported over it.
How has it helped my organization?
Cost and performance optimization were the major enhancements for our organization. It gives us platform monitoring for the services that are deployed in AWS for a better way to monitor the services (pods, cost, high availability, etc.). With this product, we ensure that observability and also keep customer services uninterrupted. We host the data pipelines between the cloud and the on-prem. Datadog helps to ensure better services. We find we can report issues based on the metrics reported over it.
What is most valuable?
The observability pipelines are the most valuable aspect of the solution.
Platform monitoring for the services that are deployed in AWS is helpful. It gives a better way to monitor the services. With Datadog, we ensure observability and maintain uninterrupted customer service.
We can host the data pipelines between the cloud and the on-prem. Issues are easily reported.
The data streams are good. Data lineage is something that really helped in ensuring tracking of the data and metrics and also the volumes processed.
What needs improvement?
We'd like to see better transformers.
Live chat would be the best way to support us.
Also, the features that we saw getting launched recently were something we expected and we're glad to see them coming.
Geo-data is also something very critical that we hope to see in the future.
For how long have I used the solution?
I've used the solution for two or more years.
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.
Software Engineer at a tech vendor with 1,001-5,000 employees
Great profiling and tracing but storage is expensive
Pros and Cons
- "Anything I've wanted to do, I found a way to get it done through Datadog."
- "When it comes to storing the logs with Datadog, I'm not sure why it costs so much to store gigabytes or terabytes of information when it's a fraction of the cost to do so myself."
What is our primary use case?
We use the solution for application hosting and a little bit of everything when it comes to supporting a worldwide logistics tracking service. It's used as a central service for collecting telemetrics and logs. We find it does the same work as all of our old tools combined, including Prometheus, Kibana, Google Logs, and more; putting all of this information in a single platform makes it easy to corroborate information and associate a request with the data, which might be lost when it is saved as logs.
How has it helped my organization?
At my organization, we have plenty of microservices written in different languages. Different teams prefer one or the other framework or library within those languages.
With Datadog, we can get in a single line and march in the same direction; our logs and metrics are collected in the same fashion, making it easy to find bugs or integration problems across services and understand how they interact with other systems.
What is most valuable?
I primarily prefer to utilize the profiling and tracing feature. It can potentially be used as a more-informed alternative to logs.
Beyond that, anything I've wanted to do, I found a way to get it done through Datadog. It allows for testing, logging, hardware monitoring, system performance, memory consumption, advanced observability, AI assistance, cross-team collaboration, and business analytics. Datadog helps some of the world’s biggest brands transform faster with the help of true AIOps, AI-assisted answers, UX and business analytics, cloud observability, and smart AI assistance.
It's all supporting my desire to build a great application, and in a centralized SaaS application, it's hard to say anything can beat it.
What needs improvement?
The storage of logs is a little bit unexpected; most services generate gigabytes of logs, and their size is not excessive. When it comes to storing the logs with Datadog, I'm not sure why it costs so much to store gigabytes or terabytes of information when it's a fraction of the cost to do so myself.
For how long have I used the solution?
I've used the solution for one year.
What do I think about the stability of the solution?
We have no concerns with stability.
What do I think about the scalability of the solution?
It appears to be that there are no issues with scaling.
How are customer service and support?
Technical support is slow. It takes forever to get responses from the support team.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
I've previously used Kibana and Prometheus. We are still using these.
How was the initial setup?
Setting up through the environment variables made it unbelievably easy to get started.
What about the implementation team?
We've implemented the solution in-house.
What was our ROI?
I do not have this number off-hand, as I am not the finance guy. I just like the product.
What's my experience with pricing, setup cost, and licensing?
I'd advise new users not to start off by sending logs.
Which other solutions did I evaluate?
We did not really look at other options.
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?
Google
Disclosure: I am a real user, and this review is based on my own experience and opinions.

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