Sold by: Datadog
Deployed on AWS
Datadog is a monitoring and analytics platform for large-scale applications that aggregates data across your entire stack with 250+ integrations for troubleshooting, alerting and graphing.
4.4
Overview
This listing provides a container-based agent for "Datadog Enterprise". You will need to subscribe to https://aws.amazon.com/marketplace/pp/B07HMG17ZR before using this agent.
Datadog is a SaaS-based monitoring and analytics platform for large-scale applications and infrastructure. Combining real-time logs, metrics from servers, containers, databases, and applications with end-to-end tracing, Datadog delivers actionable alerts and powerful visualizations to provide full-stack observability. Datadog includes over 250+ vendor-supported integrations, APM libraries for several languages, anomaly detection, forecast monitoring and live process monitoring.
Datadog Enterprise is available for customers wishing to monitor 100+ hosts.
Note on usage: Price is based on committed use per month over total term of the agreement (the Total Expected Use).
Highlights
- Turn-key integrations and easy-to-install agent to start monitoring all of your servers and resources in minutes.
- Easy-to-use API allows you to extend Datadog integrations and send metrics and events from your own applications.
- Rich, out-of-the-box dashboards plus drag-and-drop tools to create your own.
Details
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Datadog Enterprise
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Operating system
Linux
Deployed on AWS
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Delivery details
Datadog Enterprise
Supported services: Learn more
- Amazon ECS
- Amazon EKS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
N/A
Additional details
Usage instructions
The Datadog Agent can be deployed as a Docker Container, an ECS or Fargate Task, or via the Kubernetes Daemonset or Helm Chart. For basic usage refer to: /agent. For advanced documentation see: https://github.com/DataDog/datadog-agent/tree/master/Dockerfiles/agent
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Contact our knowledgable Support Engineers via email, live chat, or in-app messages
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Datadog is a SaaS-based unified observability and security platform providing full visibility into the health and performance of each layer of your environment at a glance.
Datadog is a SaaS-based unified observability and security platform providing full visibility into the health and performance of each layer of your environment at a glance.
Datadog is a monitoring service for large-scale applications that aggregates data across your entire stack with 250+ integrations for troubleshooting, alerting and graphing.
Datadog is a SaaS-based unified observability and security platform providing full visibility into the health and performance of each layer of your environment at a glance.
Customer reviews
BasilJiji
Unified observability has improved incident response and now reduces downtime across environments
Reviewed on Dec 29, 2025
Review from a verified AWS customer
What is our primary use case?
My main use case for Datadog is unified observability, as I use it to correlate metrics, traces, and logs in a single pane of glass to ensure the health and security of our cloud infrastructure and application.
I correlate those metrics, traces, and logs using the Service Map to visualize dependencies between our microservices, and for example, during a latency spike, I can instantly see if there is a bottleneck in a specific database query or a downstream API, which allows me to route the issues to the right team immediately.
What is most valuable?
Datadog is an incredibly powerful daily driver for any engineer, and the recent addition of LLM observability for AI apps and Cloud Security Management makes it feel like a platform that is truly keeping up with modern tech trends. The dashboarding and alert integrations are great features offered by Datadog, giving us all the required information on a single screen, and the alert integration performs its job in a very good manner.
Datadog has positively impacted our organization, as it has eliminated many negative issues, which I call tool sprawl, by replacing four or five separate monitoring tools with one unified platform. This has improved our MTTR and broken down silos between Dev and Ops teams.
Since Datadog has been introduced, the response time when seeing an alert has increased, so alerts have been taken care of within less time and routed to the other teams who have been taking the required actions. This has given us a very positive approach towards the entire working culture.
What needs improvement?
Datadog is a platform that can be improved by making its pricing more predictable, as sometimes it is difficult to forecast exactly how much a new project will cost until after we have started ingesting the data.
When it comes to the documentation, we do not have much available right now, so if Datadog can improve the documentation part, it would really help the engineers to work on this.
Datadog is the most comprehensive observability tool on the market, and it only loses two points because the pricing for log ingestion can grow quickly if we do not carefully manage our filters.
For how long have I used the solution?
I have been using Datadog for about three years to monitor our cloud-native application and infrastructure across multiple environments.
What do I think about the stability of the solution?
Datadog is extremely stable, as it is built for high scalable environments and consistently maintains high availability, which is why I trust it as our primary monitoring tool.
What do I think about the scalability of the solution?
Datadog is built for hyperscale, as it automatically scales when we add new hosts or containers, and its Monitoring as Code approach via Terraform allows us to scale our monitoring setup instantly as our infrastructure grows.
How are customer service and support?
Their technical documentation is some of the best in the industry, and their support engineers are very proactive, helping us optimize the ingestion cost.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I previously used a mix of open-source tools like Prometheus and Grafana , and I switched because manual upkeep was too high and I needed a platform that could handle logs and traces alongside metrics without having to manage the backend storage.
How was the initial setup?
Buying Datadog through the AWS Marketplace was seamless and helped me meet AWS spending commitments, and while Datadog's custom metric pricing can be complex, the setup cost is very low because the agent is easy to deploy.
What was our ROI?
I have seen a strong ROI through a thirty percent reduction in downtime and significant cost savings by identifying under-utilized cloud resources, for example, the ideal EC2 instances through their cloud cost management.
Which other solutions did I evaluate?
I evaluated New Relic , Dynatrace , and Amazon CloudWatch before choosing Datadog, and I chose Datadog because of its massive library of over seven hundred integrations and its superior user interface, which is easier for our developers to use daily.
What other advice do I have?
My biggest advice is to set up ingestion rules and filters early, as you should not send all your logs and metrics at once, and being selective about what you need to store can maximize your ROI from day one. I would rate this review as an eight.
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)
Aman
Monitoring has improved digital experiences and speeds root cause analysis for incident tickets
Reviewed on Dec 13, 2025
Review from a verified AWS customer
What is our primary use case?
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.
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)
Andrei Mita
Unified monitoring has streamlined global reporting and standardized alerts across teams
Reviewed on Dec 05, 2025
Review provided by PeerSpot
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.
reviewer2774049
Has helped centralize activity monitoring and generate detailed reports for leadership
Reviewed on Oct 30, 2025
Review provided by PeerSpot
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.
Benjamin Martin
Custom dashboards and alerts have made server issue detection faster
Reviewed on Oct 20, 2025
Review from a verified AWS customer
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