We primarily use the solution for logging and APM, and for real user metrics.
Sr. Manager - DevOps at a aerospace/defense firm with 10,001+ employees
Excellent RUM, session replay, and APM
Pros and Cons
- "The solution has helped out organization gain improved visibility."
- "The product needs a better Datadog agent installation."
What is our primary use case?
How has it helped my organization?
The solution has helped out organization gain improved visibility.
What is most valuable?
The most useful aspects of the solution include RUM, session replay, and APM.
What needs improvement?
The product needs a better Datadog agent installation.
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April 2025

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For how long have I used the solution?
I've used the solution for one year.
Which solution did I use previously and why did I switch?
We previously used App Dynamics.
Which other solutions did I evaluate?
Before choosing Datadog, we looked at Splunk.
Disclosure: I am a real user, and this review is based on my own experience and opinions.

Senior Engineering Manager,Mobile Wireless Engineering at a comms service provider with 10,001+ employees
Efficient and helps with integration and creating queries
Pros and Cons
- "Datadog is providing efficiency in the products we develop for the wireless device engineering department."
- "We need more integration functionality, including certain metrics integration."
What is our primary use case?
The product is primarily used for the DevOps team.
How has it helped my organization?
It has helped us build pipelines for ops review and other functions.
What is most valuable?
Datadog is providing efficiency in the products we develop for the wireless device engineering department. We had to provide more developer integration tools and also needed to help in creating easy queries that would help in creating efficient toolsets for management to make decisions based on these metrics.
What needs improvement?
We need more integration functionality, including certain metrics integration. We should be able to monitor devs and need it to build more monitoring tools and offer leadership metrics.
For how long have I used the solution?
I've used the solution for almost six months.
Which deployment model are you using for this solution?
Private 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
April 2025

Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: April 2025.
848,989 professionals have used our research since 2012.
Devops Engineer II at a comms service provider with 11-50 employees
Great CPU profiler and lots of features but can be overwhelming
Pros and Cons
- "Even if we don't end up using Datadog, it revealed problems and optimizations to us that weren't obvious before."
- "The sheer amount of products that are included can be overwhelming."
What is our primary use case?
We use the solution for monitoring our logs across distributed clusters. Right now, we have an Elasticsearch solution that is tied to each platform (our product is a PaaS solution).
We are looking at moving to a single pane of glass solution, which Datadog would be good for (plus, we could wrap up other tools like Prometheus, Grafana, Pagerduty, Pingdom, and more). We want to be able to have Datadog running on one single cluster and ingesting and processing logs from all our distributed clusters.
How has it helped my organization?
So far, we are just in the evaluation stages so it's hard to say how it's improved out organization. However, one positive impact it had is it's been just showing us an example of how to build in observability, metrics, tracing, etc., in a better way.
Even if we don't end up using Datadog, it revealed problems and optimizations to us that weren't obvious before. One potential reason why it may not help us is that we have strict rules around log parsing and may not be able to send it to an external organizaton for ingestion/processing.
What is most valuable?
The CPU profiler has been interesting even though it isn't our core use case.
We are finding that Datadog has way more offerings than originally expected, so we are constantly finding new parts of it that would be convincing to use.
The log and ingestion are very similar to our current Elasticsearch setup. We find the tracing and overall integration/ecosystem to be the most valuable part. Basically, the CPU profiler is a good example of a value add for a problem we knew we had yet was low priority and had hacky workarounds. The value proposition is in the ecosystem as a whole.
What needs improvement?
The sheer amount of products that are included can be overwhelming.
The solution requires better overarching UI, which would make things clearer. Even though I generally dislike the AWS UI, it makes the different services very clear, and it also makes where you are at any given point clear.
The sidebar for all the different services is a bit much.
I also found the tagging of logging pipelines to be a bit tedious. It would be great if, once marked up, it would automatically be a first-class citizen in Datadog.
For how long have I used the solution?
We are still in the evaluation stage and have used it less than one month.
What do I think about the stability of the solution?
The stability looks good so far.
What do I think about the scalability of the solution?
It seems easier to scale and build app functionality across multiple teams rather than other solutions.
Which solution did I use previously and why did I switch?
We have used Elasticsearch, Grafana, and Prometheus. We are still evaluating Datadog.
What was our ROI?
The product has provided good ROI by saving development time as well as time managing setting up ES.
What's my experience with pricing, setup cost, and licensing?
It is somewhat expensive compared to open-source options.
Which other solutions did I evaluate?
We evaluated Elasticsearch, Grafana, and Prometheus. We are still evaluating Datadog.
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: My company has a business relationship with this vendor other than being a customer: evaluator
Software Engineer at a comms service provider with 11-50 employees
Industry-standard with good profiling and helpful alerts
Pros and Cons
- "The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling."
- "It can be overwhelming for new people as it has a lot of features."
What is our primary use case?
We use different tools for log collection and monitoring. Using Datadog will combine different use cases into one product that will be easier to manage.
The tools we use are open-source, so there is no commercial support. Having customer support would be ideal since we're a small team.
Profiling would be another great feature to have. Currently, it's manual. Having Datadog would give us a standard, and we don't have to do much manual work.
How has it helped my organization?
It will solve a lot of our problems. We have different tools for each of them in our organization; they are open-source and therefore not very well maintained with there is no customer support.
Having an industry-standard product such as Datadog would be ideal for us as we are short on manpower. Since this is a managed all-in-one product with readily available support, we will be able to focus on application logic rather than figuring out why a tool isn't working.
What is most valuable?
The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling. We have different tools for each of them in our organization and all of them are open-source. These are not very well maintained and there is no customer support.
Having an industry-standard product is ideal for us as we are short on manpower. Profiling is another amazing feature. Currently, we rely on some open-source solutions, and it's all done locally. Having it done on Kubernetes would give us more insights and help with performance. Alerting is again a nightmare for us. Datadog solves all of these issues.
What needs improvement?
It can be overwhelming for new people as it has a lot of features. The UI could certainly be improved. Having less information with better organization could help newcomers. I haven't seen the documentation, however, a well-organized documentation would invite many varied users.
For how long have I used the solution?
I've been using the solution for three years.
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.
SRE at a computer software company with 51-200 employees
Great for log aggregation, searching, and system monitoring
Pros and Cons
- "The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents."
- "Datadog could always lower the price!"
What is our primary use case?
We are using Datadog for server metrics, log aggregation and searching, system monitoring, alerting the team about errors, and dashboards for our developers. It's used by the Site Reliability Engineering team and Management of all levels.
It's assisting us in proving SOC II compliance.
We're looking to improve our usage of Datadog's RUM and APM components to get better and more performance insights on our production environments.
We're also looking to leverage more synthetic monitors and runbooks for anyone responding to incidents.
How has it helped my organization?
The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents so far this year, and we heavily rely on a series of dashboards showing us various queues and load on CPU and memory for servers.
We also have a view of the information required when we begin the patch and/or upgrade processes.
I've also set up several monitors to alert the Site Reliability Engineering team when various metrics show a server might be reaching capacity. We use it to send an email suggesting we increase the size of the cloud instance.
What is most valuable?
The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents. We heavily rely on dashboards that are showing us various queues and load on CPU and memory for servers.
We also have a view of the information required when we begin the patch and/or upgrade processes.
I've arranged several monitors to alert the Site Reliability Engineering team when various metrics show a server that might be reaching capacity. We use it to send an email suggesting we increase the size of the cloud instance.
What needs improvement?
Datadog could always lower the price! In general, more demos online and maybe more free hands-on tutorials for basic functionality would be good for less technical users.
I would also prefer more chances to amend the contract more than twice a year. As a smaller but growing company, it can be difficult to adequately predict demand.
For how long have I used the solution?
I've used the solution for more than three years.
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.
Technical Lead at a wholesaler/distributor with 1,001-5,000 employees
Great dashboards, easy to tweak, and showcases helpful metrics
Pros and Cons
- "The ease of correcting these dashboards and widgets when needed is amazing."
- "The parallel editing of the dashboards should not cause users to lose the work of another person."
What is our primary use case?
We use Datadog for observability and monitoring primarily. Various cross-functional teams have built various dashboards, including Developers, QA, DevOps, and SRE.
There are also some dashboards created for senior leadership to keep tabs on days to day activities like cost, scale, issues, etc.
Also, we've set up monitors and alarms that kick off when any metrics go beyond the threshold. With Slack and PagerDuty integration, correct team members get alerted and react to solve the issue based on various runbooks.
How has it helped my organization?
Using Datadog metrics has helped the organization a lot in many manners. With one centralized monitoring place, it's a lot less effort to keep track of the system and applications' health.
Using this also helps teams be proactive in dealing with any issues before they get escalated by customers.
Lastly, having so many integrations makes the DevOps and SRE's lives a lot easier when automating the detection and resolution of any issues hidden in the system or applications. Overall, it has helped a lot.
What is most valuable?
My favorite feature is creating dashboards as that empowers me to sleep calmly at night and not to keep watch on critical system metrics. Be it DB metrics or computer-related metrics, it's always easy to view them.
The ease of correcting these dashboards and widgets when needed is amazing.
The only issue I face is when more than one person editing these dashboards simultaneously, one or the other person sometimes loses his/her work. That said, they will resolve that soon. With the variety of widgets, it's so easy to plot the data in a timely manner, and that makes monitoring a lot easier.
What needs improvement?
The solution can be improved in a few areas.
The parallel editing of the dashboards should not cause users to lose the work of another person.
Secondly, we would like to see more demos of tools that are in beta version, when they come live. I am sure they will help us a lot.
For how long have I used the solution?
I've been using the solution for slightly over two years.
What do I think about the stability of the solution?
I find the solution to be very stable.
What do I think about the scalability of the solution?
I totally love it. It is scalable.
Which solution did I use previously and why did I switch?
We previously used Sumo Logic.
How was the initial setup?
The initial setup is not so difficult.
What about the implementation team?
We implemented the solution in-house.
What was our ROI?
The ROI is very fair so far.
What's my experience with pricing, setup cost, and licensing?
I can't recommend the licensing.
Which other solutions did I evaluate?
I was not involved in any pre-evaluation process.
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.
Software Engineer at Enable Medicine
Centralizes logs and provides high-level views but is quite expensive
Pros and Cons
- "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."
- "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."
What is our primary use case?
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.
How has it helped my organization?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
We've used the solution for around two years.
Which solution did I use previously and why did I switch?
This was the first solution we tried.
What's my experience with pricing, setup cost, and licensing?
It is quite expensive, especially if you don't know how the pricing works.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Sr. Architect - SaaS Ops at CommVault
Improves infrastructure visibility, integrates well, and fine-tuning the monitors is easy to do
Pros and Cons
- "The ability to send notifications based on metadata from the monitor is helpful."
- "Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."
What is our primary use case?
We primarily use DataDog for performance and log monitoring of cloud environments, which include VMs and Azure Services like Azure compute, storage, network, firewall, and app services via event hubs.
Alerting based on monitors via teams and PagerDuty.
Logs collection for Azure services like Azure database, Azure Application Gateway, Azure AKS, and other Azure services.
Custom metrics using a Python script to collect metrics for components not natively supported by Datadog.
Synthetic testing to ensure uptime and browser tests via CI/CD pipeline.
How has it helped my organization?
Datadog has improved our visibility into infrastructure topology and performance. It provided a simplified view and ability to drill down to system performance, process usage, and logs.
We were able to set up monitors for infrastructure and applications, as the metrics were readily available in the platform. Fine-tuning monitors is very easy and the ability to configure monitor alerts with details on how to resolve the alert is a key value add.
Integration with PagerDuty, teams ensure timely alerting. PagerDuty integration bring tags from Datadog to PagerDuty, which is very useful in routing incidents to the right service
What is most valuable?
The Host Map, Live Process provides performance metrics of our application. The support team likes using Datadog for identifying resources affected and obtaining the logs.
Monitors are easy and quick to setup. Metrics are easily accessible and quick to use. The ability to send notifications based on metadata from the monitor is helpful. The setup for monitors is one time and it works for all workloads, whether it is Azure or any other cloud.
Logs rehydration helps us archive and rehydrate logs as we need. We don't need logs to be indexed at all times. Logs are required only for escalations and rehydrating does the job and provides cost savings.
What needs improvement?
We need the ability to create a service dependency map like Splunk ITSI. We have to build this in PagerDuty and it's not the best user experience. The ability to create custom inventory objects based on logs ingested would be a value add. It would be better if Datadog makes this a simple click and enable.
It would be helpful to have the ability to upgrade agents via the Datadog portal. Once agents are connected to the Datadog portal, we should be able to upgrade them quickly.
Security monitoring for Azure and Operating System (Windows and Linux) are features that need to be addressed.
Dashboards for Azure Active Directory metrics and events should be improved.
For how long have I used the solution?
We have been using Datadog for more than six months.
What do I think about the stability of the solution?
Stability-wise, it has been good.
What do I think about the scalability of the solution?
The scalability is good so far.
How are customer service and technical support?
Support team has been very responsive. Only complain is on issues they don't understand, they should have a quick call and unblock the customer.
Which solution did I use previously and why did I switch?
We didn't have a solution in place. The only thing we had were logs.
How was the initial setup?
Setup is hassle-free and pretty straightforward.
What about the implementation team?
I deployed it myself.
What was our ROI?
No returns yet. We are in growth mode. If this becomes expensive we may have to look at alternative options.
What's my experience with pricing, setup cost, and licensing?
The cost is high and this can be justified if the scale of the environment is big.
Datadog needs to provide better pricing for large customers.
Which other solutions did I evaluate?
Prior to implementing Datadog, we evaluated Splunk.
What other advice do I have?
Overall, the Datadog product is really good.
It doesn't need a sales team and yet, the sales team has screwed up on some occasions. It's a great product and the customer success needs to put an extra effort to help customers with best practices rather than passing them off to support.
Customer success doesn't evangelize product features and the customer doesn't know what new is coming unless they ask about it.
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?
Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.

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