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reviewer2004192 - PeerSpot reviewer
Lead Support Engineer at a tech vendor with 11-50 employees
Real User
Good centralization of data with good integration but can be overwhelming at first
Pros and Cons
  • "The integration into AWS is key as well as our software is currently bound to AWS."
  • "The ability to find what you are looking for when starting out could be improved."

What is our primary use case?

Our use case is mainly deploying into our applications for monitoring/logging observability. We currently have our microservices feed into an actuator that exists in each instance of our application that extends to a local and central Grafana for client and internal visibility. The application we use is Grafana.

Logging captures application and system logs that are ported to each application instance for querying.

Whenever anything occurs that is considered unhealthy from a range of health checks, we have notification rules configured internally and externally for a prompt response time.

How has it helped my organization?

We have been able to be a more confident, knowledgeable, and capable team when everything is being ported into a centralized format. Beforehand, knowledge was isolated to individuals. Knowledge in terms of what information represented and where it was led to a lack of confidence. By having everything in one place, rules out that confusion and allows us to respond better to issues.

It also allows for personal growth as our team is learning the application from the ground up, and each person is enhancing their own skills.

What is most valuable?

The valuable features include the following: 

  • We are currently utilizing a decentralized distributed framework for our deployment, including our monitoring/logging observability capabilities. Centralizing them, if contingent on our company privacy guidelines, will be a big help in tracking and responding to issues that come up and have the means to understand the origin of the log management tools that were demonstrated.
  • The ability to fiddle around and manipulate how logs are outputted.
  • The ability to track AWS Lambda functions, Cloudformation, and Cloudwatch allow someone that is not savvy to dip their toe into understanding their own product.
  • The integration into AWS is key as well as our software is currently bound to AWS.

What needs improvement?

The ability to find what you are looking for when starting out could be improved. It was a bit overwhelming trying to figure out what is the best solution. It led to many prototypes or time spent just perusing documentation. If we were able to select bundles or template use cases, we would hit the ground running quicker.

Buyer's Guide
Datadog
August 2025
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For how long have I used the solution?

I've used the solution for one year.

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: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
reviewer2003829 - PeerSpot reviewer
Sr Platform Engineer at a pharma/biotech company with 11-50 employees
Real User
Good logging with lots of great integrations and an interesting dashboard
Pros and Cons
  • "Datadog has a lot of features to be able to drill down deep into the swath of logs that our platforms generate."
  • "Some of the interface is still confusing to use."

What is our primary use case?

We use it mostly for logging log messages from our Kubernetes and EC2 instances, for example, system messages and errors. Also, we want log messages from our firewalls and other network infrastructure in case of network issues. We intend to use it for application logging, et cetera, to get insight into internal problems in the applications in Kubernetes pods. We want to use it for monitoring in case of system problems and hardware failures so that it can notify us.

How has it helped my organization?

It's good to have a single location for all the logs. If you have logs coming from a whole lot of sources, it makes it hard to find where the problem lies. 

We had to spend a lot of time logging into various systems and pursuing a billion different log files looking for something that stands out as a possible cause of the issue. That can take a lot of time and doesn't give much visibility into the possible interactions between systems.

What is most valuable?

Datadog has a lot of features to be able to drill down deep into the swath of logs that our platforms generate. 

It has a lot of ability to make fancy and deep searches using regular expressions and to graph them into useful and interesting dashboard graphs. 

The plethora of built-in/downloadable integrations make it much easier to set up for our platforms. Otherwise, we'd have to parse the log files ourselves, which would take a great deal of effort. Had to do it before when had to use an ELK stack for logging, which was painful.

What needs improvement?

Some of the interface is still confusing to use. It has many features, and it takes a lot of effort to figure out what they all mean. Maybe having tooltips or something would be helpful. Also, some of the integrations are better than others.

For how long have I used the solution?

I've used the solution for a month.

What do I think about the stability of the solution?

The solution seems very stable.

Which solution did I use previously and why did I switch?

Have used an ELK stack before. However, it took a lot of effort to maintain, and parsing the logs was difficult.

How was the initial setup?

We implemented the solution in-house.

Disclosure: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
Buyer's Guide
Datadog
August 2025
Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: August 2025.
865,384 professionals have used our research since 2012.
reviewer2004069 - PeerSpot reviewer
support Eng
Real User
Helpful dashboards with a good cloud security posture manager and cloud workload security
Pros and Cons
  • "It helps us better manage our logs."
  • "They should continue expanding and integrating with more third-party apps."

What is our primary use case?

We use the application for our application monitoring, data security monitoring, and log management. What we like about the application is that it helps us to track issues more proactively instead of reactively.

There are other improvements we would like to see.

1. Being able to restrict users from seeing or viewing specific dashboards once they log in

2. They can cut down the prices for Cloud SIEM. It seems very useful, however, the prices are high. Some organizations are finding it difficult to make decisions in terms of getting the tool.

How has it helped my organization?

We use the application for our application monitoring, data security monitoring, and log management. It helps us to track issues proactively instead of reactively.

It helps us better manage our logs.

We can effectively track down issues.

We have dashboards that give us an overview of our environment.

What is most valuable?

The tools I have found useful include the Datadog cloud security posture manager and cloud workload security.

What needs improvement?

Datadog is a great tool, and we value the services they offer. They should continue expanding and integrating with more third-party apps.

For how long have I used the solution?

I've used the solution for three years. 

What do I think about the stability of the solution?

I love its stability.

What do I think about the scalability of the solution?

It is very scalable.

How are customer service and support?

Technical support has been great.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

We previously used AWS.

How was the initial setup?

The initial setup is not too complex.

What was our ROI?

We've seen an ROI of 50%.

What's my experience with pricing, setup cost, and licensing?

It's a little pricy yet worth it.

Which other solutions did I evaluate?

We did not previously evaluate another solution.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
reviewer2003478 - PeerSpot reviewer
Data Engineer II at a comms service provider with 10,001+ employees
Real User
Ingests data from various sources, integrates well, and offers a helpful alert mechanism
Pros and Cons
  • "Datadog agents act as an integration to different services, providing easy access and management."
  • "Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted."

What is our primary use case?

Ingesting data from various sources to monitor the log metrics of the system and enabling an alert mechanism to notify the teammates if something goes wrong.

More specifically, having Datadog agents as integration to different services provides easy access and management.

How has it helped my organization?

The solution has helped out organization by allowing us to ingest data from various sources to monitor log metrics and enabling alert mechanisms to notify teams if something goes wrong.

Datadog agents act as an integration to different services, providing easy access and management.

What is most valuable?

The solution is useful for ingesting data from various sources. This helps to monitor the log metrics of the system. It has alert mechanisms that can be enabled to notify the teams if something goes wrong.

Datadog offers good integration to different services. It provides for easy access and management.

What needs improvement?

Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted. 

For how long have I used the solution?

We've used the solution for close to 1.5 years.

What other advice do I have?

We use a SaaS deployment.

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
reviewer2003616 - PeerSpot reviewer
Production engineer at a consultancy with 51-200 employees
Real User
Offers great flexibility with useful APM traces and logging for debugging
Pros and Cons
  • "The flexibility to create notebooks and dashboards and fully customize them gives us a lot of power to track the exact services and endpoints we are working on."
  • "We need more visibility into the error tracking dashboard."

What is our primary use case?

We have deep integration with Datadog for observability and monitoring.

We use everything from APM, logs, and RUM to monitor and dashboards for tracking system health. 

We are trying to move from many different solutions for error tracking/observability to a single platform (Datadog).

We are currently in the process of setting up logging in Datadog in order to maintain our logs better. We are looking to create more insights into the real user flows by using real user monitoring (RUM) too.

How has it helped my organization?

We use Datadog quite extensively. I primarily work with APM traces and logs to debug issues and unblock myself in my day-to-day role. I have found the traces and spans most useful in providing details about why certain services are performing poorly.

Datadog provides a lot of value in terms of adding monitoring and observability to our app. There are so many different solutions, it is sometimes difficult to gauge where to start, and I sometimes miss a lot of functionality (such as the very useful error-tracking dashboard mentioned in my review above).

What is most valuable?

As I mentioned above, we use Datadog quite extensively. In my day-to-day role, I primarily work with APM traces and logs to debug issues and unblock myself. 

I have found the traces and spans most useful in providing details about why certain services are performing poorly.

Additionally, the flexibility to create notebooks and dashboards and fully customize them gives us a lot of power to track the exact services and endpoints we are working on.

Furthermore, we are also using monitoring to page us if things break, and the Slack integration provides us instantaneous feedback on how things are performing.

What needs improvement?

We need more visibility into the error tracking dashboard. I only learned about it during a demo at Dash Con. That said, it seems to be a very useful tool.

Additionally, we want to export our dashboards and monitors to source control, and there doesn't seem to be any easy way to do so.

For how long have I used the solution?

I've used the solution for four years.

Which solution did I use previously and why did I switch?

For logging, we are moving from LogDNA to Datadog to have access to everything in one place. Also, searching and traversing through logs seems easier in Datadog

Which other solutions did I evaluate?

I did not evaluate others, however, my team probably did.

What other advice do I have?

Datadog provides a lot of value in terms of adding monitoring and observability to our app. There are so many different solutions; it is sometimes difficult to gauge where to start, and I sometimes miss a lot of functionality. For example, the very useful error-tracking dashboard that I just discovered.

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: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
reviewer2003781 - PeerSpot reviewer
Product SRE at a computer software company with 51-200 employees
Real User
Good dashboards and documentation with helpful Synthetics Tests
Pros and Cons
  • "Dashboards and their versatility are among the most valuable features."
  • "We would like to see some versioning system for the Synthetic Tests so that we could have a backup of our tests since they are time-consuming to make and very easy to damage in a moment of error."

What is our primary use case?

We use Datadog for application logs, error tracking, performance tracking, alerting, and overall production state surveillance. 

It helps us improve observability and ease of maintenance through better information for our support teams and their issue qualification. 

We also use dashboards to keep all the information at ready and easy to access. SLOs notably for our uptimes but also our feature usage. It also feeds our alerting for our on-call SREs into PagerDuty by launching alerts when specific parameters are exceeded.

How has it helped my organization?

Our usage of Datadog has allowed us to improve our observability at great lengths. We have been able to track pain points more easily with it, and be able to define custom metrics to track our user's usage of the features we roll out.

Being able to generate dashboards has given higher management a better view of our teams' work and has allowed for better client information by our sales team as they have a more transparent way ofdealing with our upcoming features.

What is most valuable?

Dashboards and their versatility are among the most valuable features. They allow us to have internal facing trackers of our application's issues, usages, and features. They also allow us to have a better understanding of how users react to new features, and to display more information to other teams or also clients through uptime SLOs, et cetera.

We also found the Synthetics Tests and especially the Browser Tests very helpful. It is a nicer way to create end-to-end tests in a more user-friendly way than through code. They are very valuable in saving time compared to code-based testing.

Documentation is also very clear and interesting.

What needs improvement?

We would like to see some versioning system for the Synthetic Tests so that we could have a backup of our tests since they are time-consuming to make and very easy to damage in a moment of error.

I look forward to seeing the next features that will be released.

For how long have I used the solution?

I have been using the product for a year and a half. The company has been using it for longer. I don't know the exact details.

What do I think about the stability of the solution?

We have yet to have a large-scale problem with stability using Datadog. It's very satisfying.

What do I think about the scalability of the solution?

The scalability is very good.

How are customer service and support?

I've had only a few experiences with customer support, and it went well. They were fast!

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

We did not use a different solution previously.

How was the initial setup?

I wasn't there for the initial setup.

What about the implementation team?

I wasn't there for the initial setup.

What was our ROI?

I cna't speak to the ROI.

What's my experience with pricing, setup cost, and licensing?

I don't give advice regarding that.

Which other solutions did I evaluate?

I wasn't part of the decision-making process.

What other advice do I have?

It would be nicer if the pricing information was easier to find in the documentation. Sometimes it helps to get an overall idea of the cost of certain options.

Disclosure: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
reviewer2003214 - PeerSpot reviewer
Sr. Director of Software Engineering at a tech consulting company with 1,001-5,000 employees
Real User
Helpful support, good incident management, and helps triage faster
Pros and Cons
  • "The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support."
  • "The pricing is a bit confusing."

What is our primary use case?

The RUM is implemented for customer support session replays to quickly route, triage, and troubleshoot support issues which can be sent to our engineering teams directly. 

Customer Support will log in directly after receiving a customer request and work on the issue. Engineers will utilize the replay along with RUM to pinpoint the issue combined with APM and Infra trace to be able to look for signals to find the direct cause of the customer impact. 

Incident management will be utilized to open a Jira ticket for engineering, and it integrates with ITSM systems and on-call as needed.

How has it helped my organization?

The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support.

The RUM is implemented for customer support. It can quickly route, triage, and troubleshoot support issues that are sent to our engineering teams. 

Customer support can log in and start troubleshooting after receiving a customer request. The replay and RUM help pinpoint the issue. This functionality is combined with APM and Infra trace to be able to look for the cause of the issue. Incident management is leveraged to open a Jira ticket for engineering, and it can integrate with ITSM systems and on-call as needed.

What is most valuable?

RUM with session replay combined with a future use case to support synthetics will help to identify issues earlier in our process. We have not rolled this out yet but plan for it as a future use case for our customer support process. This, combined with integrated automation for incident management, will drive down our MTTR and time spent working through tickets. Overall, we are hoping to use this to look at our data and perfection rate over time in a BI-like way to reduce our customer support headcount by saving on time spent.

What needs improvement?

I would like to see retention options greater than 30-days for session replay. I'd also like to see forwarding options for retention to custom solutions, and a greater ability to event and export data from the tooling overall to BI/DW solutions for reporting across the long term and to see trends as needed.

For how long have I used the solution?

I've used the solution for about nine months.

What do I think about the stability of the solution?

So far, stability has been great.

What do I think about the scalability of the solution?

I'd like to see more bells and whistles added over time. Widgets are coming soon to help with RUM.

How are customer service and support?

Support is very good. They are responsive and gave us the help we need.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

We have utilized New Relic, however, not for RUM. We went with Datadog to potentially switch the entire platform into an all-in-one solution that makes sense for a company of our size.

How was the initial setup?

We started on the beta, and the documentation was lagging behind. We also needed direct instructions and links from the customer support/account representative that was not immediately available by searching online.

What about the implementation team?

We implemented the solution ourselves.

What was our ROI?

Ideally, this will inform our strategy to not increase our customer support headcount as significantly into 2023 and beyond.

What's my experience with pricing, setup cost, and licensing?

The pricing is a bit confusing. However, the RUM session replay, in general, is very inexpensive compared to whole solutions.

Which other solutions did I evaluate?

We looked into LogRocket and New Relic.

What other advice do I have?

I'd advise other users to try it out.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
PeerSpot user
reviewer2003286 - PeerSpot reviewer
Software engineer at a marketing services firm with 501-1,000 employees
Real User
Helps catch bugs, easy for non-technical users, and useful for tracking issues
Pros and Cons
  • "This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."
  • "Datadog could make their use cases more visible either through their docs or tutorial videos."

What is our primary use case?

We use metrics to track the metrics of our application. We use logging to log any errors or erroneous application behavior as well as successful behavior. We use events to log successful steps in our pipeline or failed steps in our deployment. We use a combination of all these features to diagnose bugs. 

It makes it much more efficient to look at all the data in one place. This speeds up our development speed so that we can be agile.

How has it helped my organization?

This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime. 

It also allows us to accurately record and project current and future revenue by measuring the application's metrics. This way, my team can accurately and rapidly create reports for upper management that are easy to read and understand. 

Datadog is also easy to read by non-technical personnel. This way, if there are any erroneous readings, everybody has a chance to find them.

What is most valuable?

We use metrics to track the metrics of our application. We use logging to log any errors or erroneous application behavior as well as successful behavior. We use events to log successful steps in our pipeline or failed steps in our deployment. 

We use a combination of all these features to diagnose bugs. It makes it much more efficient to look at all the data in one place. This speeds up our development speed so that we can be agile.

These features are the features that I use the most since it is incredibly difficult to track down intermittent bugs if I were to look directly under the hood in a CLI.

What needs improvement?

Datadog could make their use cases more visible either through their docs or tutorial videos. There are different implementations of certain features that we utilize to customize Datadog functionality and in that way, we sometimes get results that are not conducive to what Datadog thinks their features' use cases are.

For how long have I used the solution?

I've used the solution for at least one year.

Which solution did I use previously and why did I switch?

We have only used Datadog. We did not previously use a different product.

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 does not have a business relationship with this vendor other than being a customer.
PeerSpot user
Buyer's Guide
Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.
Updated: August 2025
Buyer's Guide
Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.