I intend to use Datadog for application performance monitoring, digital user experiences, and troubleshooting to find the root cause analysis of tickets that will be generated in my managed environment. Digital user experience happens to be the priority for me, as I am evaluating this feature across some competing products.
Datadog Enterprise
DatadogExternal reviews
730 reviews
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Monitoring has improved digital experiences and speeds root cause analysis for incident tickets
What is our primary use case?
What is most valuable?
The best features Datadog offers are digital user experience, troubleshooting, and remediation capabilities, which help identify what is going wrong and where. I focused on the root cause analysis of incidents and tickets, as examining the RCAs makes it easier to find remediations and helps with shifting incidents left. Datadog will positively impact my organization by allowing me to handle ticket resolutions at a much faster pace and bring productivity by reducing the number of support engineers required at the monitoring level. If I integrate Datadog with my managed environment or cloud environment, the RCAs and all the left shift will be automated, and with automation, I will be able to reduce the number of support engineers.
What needs improvement?
Datadog could be improved with a simpler graphical user interface that can be extended to non-technical users, such as a CXO, if they want to review the dashboard overall for current tickets and the ticketing dashboard. It would be beneficial to have documentation auto-generated while examining remediations or integration with existing systems.
For how long have I used the solution?
I have been working for more than fifteen years in data center, disaster recovery solutions, and cloud computing, which includes private, public, and hybrid environments.
What do I think about the stability of the solution?
Datadog seems to be more stable, and I really want to have a complete demo before making a call to decide on this.
What do I think about the scalability of the solution?
I hope that Datadog will be able to extend to digital users, even if they are on a scale of thousands for an organization and connect to corporate bandwidth, and the server should be pretty much scalable on the server side.
How are customer service and support?
I find the customer support impressive from what I have heard about Datadog, and I really want to onboard this solution for my customers.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
As of now, we are using cloud-native monitoring with CloudWatch and Azure Monitor for our multi-cloud environment, and we really want to extend it to greater detail that will cover deliberations at greater depth. We have looked at ManageEngine and SolarWinds before choosing Datadog, but they were not very impressive, as the amount of Datadog functionality is not available in these two platforms.
How was the initial setup?
I am looking to deploy Datadog on AWS and Azure for multi-cloud management support and really want to extend it at the server side and at the end-user side for digital user experience. I will start with AWS and extend it to Azure six months down the line. I plan to purchase Datadog through the AWS Marketplace once I have the demo.
What was our ROI?
I am looking at metrics that will help me decide whether I need to really deploy Datadog, and the metrics will primarily be centered around reducing the number of employees and cost optimization.
What's my experience with pricing, setup cost, and licensing?
I did not get the complete information regarding the licenses and commercials associated with Datadog, and I would like to have some idea about the license.
What other advice do I have?
I hope to have some literature on how I can leverage my managed support for cloud environments, plus how I can integrate this with my managed support at the end-user devices. Finding the root cause analysis at greater depth, reducing the number of employees to manage or monitor infrastructure incidents, and increasing satisfaction on the application performance monitoring part are the advice I would give to others looking into using Datadog. I give this review a rating of eight.
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Unified monitoring has streamlined global reporting and standardized alerts across teams
What is our primary use case?
My main use case for Datadog is that we offer the application performance management service within PwC as a global team.
A specific example of how my team uses Datadog for performance management is that my team does not directly use Datadog for performance management; however, we work with approximately 300 teams that use it daily for monitoring their apps. One of the most used cases is to observe when services are up and down and if services are not degraded.
We use most of every product within Datadog across the 300 customers that we have internally.
How has it helped my organization?
Datadog has positively impacted my organization because before Datadog, we had multiple APM tools and monitoring tools, which fragmented the service. The reason was that some tools offered benefits to certain teams, while other tools offered different benefits to other teams. With Datadog, we managed to get everyone on board into a single place and a single tool, providing teams with one spot where they can check everything related to monitoring, and enabling management and leadership to have an overview of all tools working together.
I measured the impact of bringing everything into one place through observation, and I can confirm that efficiency in reporting improved dramatically and it became much easier to observe changes. Standardization was a tremendous win for us. Having a set of standard alerts and monitoring in place allowed us to speed up onboarding for every app. Once the resources are in Datadog, the system provides alerting out of the box. Additionally, cost has decreased dramatically.
What is most valuable?
Datadog's best features include very high demand for logs management for alerting on indexed logs and a shift towards Flex Logs for storage and long-term storage. Most recently, BitsAI and the LLM part within Datadog has been in focus for us.
Flex Logs has helped my teams because we are migrating from other services to have a unique place to store all the logs, the non-security logs, and the app logs. This has benefited those teams because they also benefit from other services within Datadog such as APM or other monitoring solutions. By bringing the logs into Datadog, they now have a single place where they can correlate everything.
The LLM integration within Datadog has helped my teams because LLM usage is at the beginning stage right now, and people are very excited. We have all these AI and LLM-based tools, and having the option of monitoring them is a great benefit for us. However, we are in the exploratory phase of this process and have just begun.
BitsAI is very interesting; we have done some testing and we are going to promote it and use it in our production environment. This is a very exciting new tool for us.
What needs improvement?
Datadog can be improved because sometimes it seems it has not been developed for enterprises. We work with over 300 customers, with each customer having multiple instances or apps within Datadog. We are facing difficulties in controlling access, in privacy settings, and splitting usage and costs for these customers.
We want to be able to customize the cost part, and we would appreciate more granular access control.
For how long have I used the solution?
I have been using Datadog for four or five years.
What do I think about the stability of the solution?
Datadog is stable.
What do I think about the scalability of the solution?
We have never had an issue with Datadog's scalability.
How are customer service and support?
Datadog's customer support is good; it could be improved in terms of communication, but it is adequate.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
How was the initial setup?
My experience with pricing, setup cost, and licensing is good; nothing out of the ordinary.
Which other solutions did I evaluate?
Before choosing Datadog, the biggest contender we evaluated was AppDynamics.
What other advice do I have?
My advice for others looking into using Datadog is to test it out and see if it works for you. Try to become accustomed to the tagging part of things, and go through each product to understand what each product within Datadog is offering. I would rate this product an eight out of ten.
Real-Time Insights and Effortless Error Tracking
What do you like best about the product?
I like that Datadog shows issues in real time and the filters help me quickly find the key errors without digging through everything.
What do you dislike about the product?
Sometimes the dashboard feels a bit heavy, and it can take time to set up the right filters when the data gets large. and some time the errors are small but it shows high alerts for it.
What problems is the product solving and how is that benefiting you?
Datadog helps us catch issues fast during live esports events like the World Cup. By checking logs and errors in real time, we can fix problems quickly and keep everything running smoothly.
Effortless Monitoring Across Platforms with Datadog
What do you like best about the product?
A lot to consider about Datadog: mainly, it is used to monitor a wide range of applications and infrastructure. Application monitoring for container-based, server-based, and web-based applications. Also the it reduces the human effort for checking the exact error.
It is easy to use and supports different kinds of platforms like AWS, Azure, and GCP. Installation is very easy. Datadog provides all the required documents for integrating the agent. We can use the predefined dashboard templates many times, which is a lifesaver if we have repeated monitoring services.
Large-scale monitoring services and tracking are very easy, and the UI is clean, and we can find every service and access the running process via UI as well.
It is easy to use and supports different kinds of platforms like AWS, Azure, and GCP. Installation is very easy. Datadog provides all the required documents for integrating the agent. We can use the predefined dashboard templates many times, which is a lifesaver if we have repeated monitoring services.
Large-scale monitoring services and tracking are very easy, and the UI is clean, and we can find every service and access the running process via UI as well.
What do you dislike about the product?
There are only a few things that I was not satisfied with Datadog, those are.
Cost is somewhat high; we have to pay even we utilize the resources or not.
And the main con is the customer support; they only deal via email, and we have to dump the log data into their storage. They first analyse the logs and come back to us; it will typically take 24-36 hours, which has an impact on the clients. Also, they only come on a call on production issues.
Cost is somewhat high; we have to pay even we utilize the resources or not.
And the main con is the customer support; they only deal via email, and we have to dump the log data into their storage. They first analyse the logs and come back to us; it will typically take 24-36 hours, which has an impact on the clients. Also, they only come on a call on production issues.
What problems is the product solving and how is that benefiting you?
Wide range, like we need to sit in front of the servers or app all the time. If there is any error, it will send an email or notifications regarding the error. So no need to worry.
Unmatched Observability and AI Insights, Lightning-Fast Setup
What do you like best about the product?
Datadog gives us a single observability layer that ties metrics, logs, traces, and AI-driven insights together. What I like most is how fast it is to instrument new services, define custom metrics, and build dashboards that actually help teams make decisions. We also use Datadog extensively for deploying internal AI agents—its event streams, log ingestions, and metric pipelines make it easy to create intelligent triggers and automated workflows.
The correlation between logs → metrics → alerts is incredibly powerful, and the AI-based anomaly detection has helped us reduce blind spots in our observability stack.
The correlation between logs → metrics → alerts is incredibly powerful, and the AI-based anomaly detection has helped us reduce blind spots in our observability stack.
What do you dislike about the product?
The biggest drawback is cost. Datadog becomes expensive very quickly—especially when log volumes grow or when you create many custom business metrics. Even with strict retention windows and log pipelines, the monthly bill requires constant governance. It’s a powerful platform, but the pricing model can be a challenge for teams that want broad coverage without compromising on granularity.
What problems is the product solving and how is that benefiting you?
Datadog helps us run a reliable observability platform. We use it to monitor application health, detect failures early, and define custom KPIs for product and engineering teams. It also acts as the signal layer for deploying AI agents—our automated workflows listen to Datadog metrics and logs to trigger alerts, escalations, and self-healing actions.
As a Product Manager, Datadog enables me to set clear SLOs, understand system behavior end-to-end, and reduce MTTD/MTTR significantly. It gives us a proactive observability mindset powered by intelligent metrics and real-time insights, helping us deliver a more stable and predictable platform for users.
As a Product Manager, Datadog enables me to set clear SLOs, understand system behavior end-to-end, and reduce MTTD/MTTR significantly. It gives us a proactive observability mindset powered by intelligent metrics and real-time insights, helping us deliver a more stable and predictable platform for users.
Comprehensive and Dynamic Monitoring for a Complete End-to-End View
What do you like best about the product?
its end-to-end monitoring since it shows us everything we need to see and likewise see what is consumed and all its logs, traces, metrics in a more dynamic way
What do you dislike about the product?
its way of containers that makes the price go up if not configured properly
What problems is the product solving and how is that benefiting you?
Before, I had to check five different tools: one to see the CPU usage of my servers (Metrics), another to find out what caused the error (Logs), and another to see which part of the code slowed down (Traces). This is slow and makes me waste time jumping between tabs.
Comprehensive Monitoring, But Setup Could Improve
What do you like best about the product?
I love how Datadog integrates seamlessly into a multi-cloud platform, providing real-time metrics that are crucial for monitoring and observability. The highly customizable dashboards allow me to tailor the analytics to fit my exact needs while the fine-tuning alert options ensure that I am always informed without being overwhelmed. These combined features help significantly in tracking system performance metrics and logs, greatly aiding in root cause analysis (RCA).
What do you dislike about the product?
I find the setup of Datadog to be inefficient and somewhat challenging, making the initial configuration process moderately hard. Additionally, the cost of using Datadog is quite high, and it would be beneficial if there were discounts available for first-time users to ease the financial burden.
What problems is the product solving and how is that benefiting you?
I use Datadog for centralized monitoring and observability, tracking system performance metrics, logs, and root cause analysis. It integrates with multi-cloud platforms, provides real-time metrics, and features customizable dashboards and alert options.
Has helped centralize activity monitoring and generate detailed reports for leadership
What is our primary use case?
My main use case for Datadog is logging security signals and monitoring account activity and suspicious behavior within our company.
For monitoring suspicious behavior, we look for alerts with things like unusual sign-in locations, unusual sign-in times, or registering new multi-factor devices in unusual circumstances or locations.
In addition to that, we also look for patterns and frequency of how often MFA is being prompted from individuals.
What is most valuable?
The best features Datadog offers include the ability to generate reports very quickly and put in extensive filtering to get very specific information.
The report generation and filtering help me in my day-to-day work by assisting in generating reports for higher-ups and turning data into actionable items.
Since using Datadog, it has positively impacted our organization by giving us a one-stop shop for multiple applications and services that we can analyze in one spot.
Having a one-stop shop has made things easier for my team, and we have seen specific outcomes such as saving a lot of time.
What needs improvement?
Datadog could be improved if the menu system was a little clearer and less cluttered, making it easier to navigate.
Additionally, more documentation is always beneficial to have.
For how long have I used the solution?
I have been using Datadog for about three years.
What do I think about the stability of the solution?
Datadog is very stable.
What do I think about the scalability of the solution?
Its scalability is good, and it has kept up as our organization has grown or changed.
How are customer service and support?
I have not had to reach out to customer support, so I cannot comment on that experience.
How would you rate customer service and support?
Negative
Which solution did I use previously and why did I switch?
I did not previously use a different solution before Datadog.
What was our ROI?
While I don't have any specifics on money saved, I can say that it has definitely improved our efficiency overall.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing for Datadog shows that the pricing is very fair and setup has been very simple and easy to do.
Which other solutions did I evaluate?
Before choosing Datadog, I did not evaluate other options.
What other advice do I have?
My advice to others looking into using Datadog is to read the documentation. I would rate this product a 9 out of 10.
Comprehensive Monitoring Tool with Powerful Insights but High Costs
What do you like best about the product?
What I like best about Datadog is how seamlessly it brings together metrics, logs, and traces in one place. The dashboard is very intuitive, and it’s easy to set up real-time monitoring for applications and infrastructure. I also like how flexible it is — you can create custom dashboards, set alerts, and get deep visibility into performance issues quickly. It really helps in identifying bottlenecks before they impact users.
What do you dislike about the product?
The main downside of Datadog is its pricing — it can get quite expensive as your infrastructure and data volume grow. Managing costs can be tricky, especially when you’re monitoring multiple environments. Also, the interface, while powerful, can feel a bit overwhelming at first due to the number of features and options available. It takes some time to get fully comfortable navigating everything.
What problems is the product solving and how is that benefiting you?
Datadog helps us monitor our entire system — from backend services and APIs to frontend performance — all in one place. It gives real-time visibility into logs, metrics, and traces, which makes it much easier to detect and troubleshoot issues quickly. Thanks to Datadog, we’ve reduced downtime, improved application performance, and gained better insights into how different parts of our system interact. It really helps our team stay proactive instead of reactive when it comes to performance and reliability.
Custom dashboards and alerts have made server issue detection faster
What is our primary use case?
My main use case for Datadog is monitoring our servers.
A specific example of how I'm using Datadog to monitor my server is that we are maintaining request and latency and looking for errors.
What is most valuable?
I really enjoy the user interface of Datadog, and it makes it easy to find what I need. In my opinion, the best features Datadog offers are the customizable dashboards and the Watchdog.
The customizable dashboards and Watchdog help me in my daily work because they're easy to find and easy to look at to get the information I need. Datadog has positively impacted my organization by making finding and resolving issues a lot easier and efficient.
What needs improvement?
I think Datadog can be improved by continually finding errors and making things easy to see and customize.
For how long have I used the solution?
I have been using Datadog for one month.
What do I think about the stability of the solution?
Datadog is stable.
What do I think about the scalability of the solution?
Datadog's scalability has been easy to put on each server that we want to monitor.
How are customer service and support?
I have not had to contact customer support yet, but I've heard they are great.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
We previously used our own custom solution, but Datadog is a lot easier.
What was our ROI?
I'm not sure if I've seen a return on investment.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing is that it was easy to find and easy to purchase and easy to estimate.
Which other solutions did I evaluate?
I did not make the decision to evaluate other options before choosing Datadog.
What other advice do I have?
I would rate Datadog a nine out of ten.
I give it this rating because I think just catching some of the data delays and latency live could be a little bit better, but overall, I think it's been great.
I would recommend Datadog and say that it's easy to customize and find what you're looking for.
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?
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