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reviewer1494894 - PeerSpot reviewer
Senior Manager, Site Reliability Engineering at Extra Space Storage
Real User
Top 20
Improved time to discovery and resolution but needs better consumption visibility
Pros and Cons
  • "Several critical dashboards were created years ago and are still in use today."
  • "We would love to see a % consumed and alert us if we are over budget before getting an overage charge 20 days into the month."

What is our primary use case?

The product monitors multiple systems, from customer interactions on our web applications down to the database and all layers in between. RUM, APM, logging, and infrastructure monitoring are all surfaced into single dashboards.

We initially started with application logs and generated long-term business metrics out of critical logs. We have turned those metrics and logs into a collection of alerts integrated into our pager system. As we have evolved, we have also used APM and RUM data to trigger additional alerts

How has it helped my organization?

The solution has surfaced how integrated our applications really are and helps us track calls from the top down, identifying slowness and errors all through the call stack.

The biggest improvement we have seen is our time to discovery and resolution. As Datadog has improved, and we add new features, the depth and clarity we get from top to bottom has been excellent. Our engineering teams have quickly adopted many features within Datadog, and are quick to build out their own dashboards and alerts. This has also led to a rapid sprawl when left unchecked.

What is most valuable?

We started with application logs and have expanded over the years to include infrastructure, APM, and now RUM. All of these tools have been incredibly valuable in their own sphere. The huge value is tying all of the data points together.

Logging was the first tool we started with years ago, replacing our ELK stack. It was the easiest to get in place, and our engineers quickly embraced the tools. Several critical dashboards were created years ago and are still in use today. Over time, we have shifted from verbose logs and matured into APM and RUM. That has helped us focus on fine-tuning the performance of our applications.

What needs improvement?

We need better visibility into our consumption rate, which is tied to our commit levels. We would love to see a % consumed and alert us if we are over budget before getting an overage charge 20 days into the month.

The biggest complaint we hear comes from the cost of the tool. It is pretty easy to accidentally consume a lot of extra data. Unless you watch everything come in almost daily, you could be in for a big surprise. 

We utilize the Datadog estimated usage metrics to build out alerts and dashboards. The usage and cost system page still doesn't tie into our committed spending - it would be wonderful to see the monthly burn rate on any given day.

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For how long have I used the solution?

I've used the solution for six years.

What do I think about the stability of the solution?

There have not been as many outages in the past year. We also haven't been jumping into the new features as quickly as they come out. We may be working on more stable products.

What do I think about the scalability of the solution?

It has scaled up to meet our needs pretty well. Over the years, we have only managed to trigger internal DataDog alerts once or twice by misconfiguring a metric and spiralling out of control with costs.

How are customer service and support?

Support has been lacking. Opening a chat with the tech support rep of the day is always a gamble. We are looking into working with third-party support because it has been so rough over the years.

How would you rate customer service and support?

Neutral

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

We used the ELK stack for logging and monitoring and AppDynamics for APM.

How was the initial setup?

The initial setup for new teams has become easier over the years. We are increasing our adoption rate as we shift our technology to more cloud-native tools. Datadog has supported easy implementation by simply adding a package to the app. 

They have really focused on a lot of out-of-the-box functionality, but the real fun happens as you dive deeper into the configuration. We have also begun adapting open telemetry standards. This has kept us from going too deep into vendor-specific implementations.

What about the implementation team?

We did the initial setup via an in-house team.

What was our ROI?

As long as we stay on top of our consumption mid-month, it has been worth it. However, the few engineers we have who are dedicated to playing whack-a-mole with the growing spending could be better utilized in teaching best practices to new users. I suppose our implementation of the rapidly changing tools over the years has led to a fair amount of technical debt.

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

It is quite easy to set up any specific tool, but to take advantage of the full visibility it offers, you need to instrument across the board—which can be time-consuming. Be careful about how each tool is billed, and watch your consumption like a hawk.

Which other solutions did I evaluate?

We evaluated AppDynamics and Dynatrace.

What other advice do I have?

It's a very powerful tool, with lots of new features coming, but you certainly will pay for what you get.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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JulianLewis - PeerSpot reviewer
Senior Engineer at a educational organization with 5,001-10,000 employees
Real User
I like the amount of tooling and the number of solutions they sold with their monitoring.
Pros and Cons
  • "I like the amount of tooling and the number of solutions they sold with their monitoring. Datadog was highly intuitive to use."
  • "Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible."

What is our primary use case?

Datadog is a SaaS solution we tried for URL and synthetic monitoring. You record a transaction going into a website and replay that transaction from various locations. Datadog is mainly used by the admin, but three or four other guys had access to the reports and notifications, so it's five altogether.  

We probably tried no more than 8 percent of what Datadog can do. There are so many other bits and modules. I've only gone into about half of what APM can do in the Datadog stack.

How has it helped my organization?

We could detect outages on particular websites or problems in specific locations. If I had paid for the full solution, I'm sure I could get a lot of value out of Datadog.

What is most valuable?

I like the amount of tooling and the number of solutions they sold with their monitoring. Datadog was highly intuitive to use. 

What needs improvement?

Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible. 

For how long have I used the solution?

I have used Datadog for about two or three years.

What do I think about the scalability of the solution?

I was only using Datadog to monitor on a small scale. 

How are customer service and support?

I'd rate Datadog support four out of 10. It was primarily an issue with support in the Asia-Pacific region. I sent them several emails, and they responded around three weeks later. 

They said it went around the houses. Nobody knew who to respond to. That's not good enough. They should have at least told me they'd received the email. I used to work in support.

How would you rate customer service and support?

Neutral

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

We were just trying Datadog, and we've switched temporarily to Site24x7. We're looking for one of the bigger ones. They've all given us proposals, whereas Datadog hasn't come forward with a proposal for what they could do.

I used Datadog because I already had a relationship with them at a previous company. However, that guy's moved on now, and I wanted to see how good they were. 

How was the initial setup?

Setting up Datadog is pretty straightforward. I have a lot of experience doing that sort of thing. It took maybe a day and a half to deploy because I was picking externally facing websites.

I deployed it by myself. One person is enough for the small system we had. However, if we were moving forward, I'd recommend at least two or three people to manage it. 

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

Datadog would've cost around $850 a month based on the loads we were doing, and you could estimate roughly what you would be paying monthly. I liked their pricing model. It was flexible, so you only paid for what you used. I rate Datadog pricing eight out of 10. 

Which other solutions did I evaluate?

We looked at several URL and APM monitoring solutions like Site24x7 and Pingdom. They weren't big players like Dynatrace or any of the those that had already provided us a request for information. 

What other advice do I have?

Even with our negative experiences, I'd still give Datadog an eight out of 10. Datadog is a complete solution with easy-to-use templates and excellent scalability. People should know exactly what they're going to configure before they try it out. The trial is brief. Don't start a trial until you know exactly what you're going to do. 

You must be certain that you can meet any internal security requirements. If you're in the Asia-Pacific region, you might not be able to run something that's running abroad.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Datadog
March 2025
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Lin Qui - PeerSpot reviewer
Works at Berkeley Research Group, LLC
User
Excellent APM, RUM and dashboards
Pros and Cons
  • "The pricing model makes more sense than what we paid for against other competitors."
  • "Logging is not a great experience."

What is our primary use case?

We use the solution for APM, anomaly detection, resource metrics, RUM, and synthetics. 

We use it to build baseline metrics for our apps before we start focusing in on performance improvements. A lot of times that’s looking at methods that take too long to run and diving into db queries and parsing.

I’ve used it in multiple configurations in aws and azure. I’ve built it using terraform and hand rolled. 

I’ve used it predominantly with Ruby and Node and a little bit of Python. 

How has it helped my organization?

The solution provides deep insights into our stack. It gives us the ability to measure and monitor before making decisions.

We're using it to make informed decisions about performance. Being able to show how across a timeline we increased performance from a release via a visual indication of p50+ metrics is almost magical. 

Another way we use it is for leading indicators of issues that might be happening. So for example, anomaly detection on gauge metrics across the app and having synthetics build in with alerting configurations are both ways we can get alerted sometimes even before a big issue is about to happen. 

What is most valuable?

The most valuable aspects include APM, RUM and dashboards. 

I think of Datadog as an analytics company first. And that the integrations around notifications and alerts as a part of insight discoverability. 

Everything Datadog offers for me is around knowledge building and how much do I know about the deep details of my stack.

The pricing model makes more sense than what we paid for against other competitors. I was at one job where we used two competing services because DD didn’t have BAA for APM. And then when it offered it, we immediately dumped the other solution for Datadog.

What needs improvement?

Logging is not a great experience. Searching for specific logs and then navigating around the context of the results is slow and cumbersome. Honestly that is my only gripe for Datadog. It’s a wonderful product outside of log searching. I have had better experience using other services that aggregate logs for search. 

My use case for it is around discoverability. Log search is fine if I’m just looking for something specific. That said, if it’s something else targeted and I am wandering around looking for possible issues, it’s really unintuitive. 

For how long have I used the solution?

I've used the solution for more than eight years.

What do I think about the stability of the solution?

Very stable. 

What about the implementation team?

We always implement the solution in-house. 

Which deployment model are you using for this solution?

Private Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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reviewer1974104 - PeerSpot reviewer
Software Engineering Manager at Finalsite
User
Top 10
Centralized pipeline with synthetic testing and a customized dashboard
Pros and Cons
  • "The ability to create custom dashboards has been incredibly useful, allowing us to visualize key metrics and KPIs in a way that makes sense for different teams and stakeholders."
  • "I spent longer than I should have figuring out how to correlate logs to traces, mostly related to environmental variables."

What is our primary use case?

Our primary use case is custom and vendor-supplied web application log aggregation, performance tracing and alerting. 

We run a mix of AWS EC2, Azure serverless, and colocated VMWare servers to support higher education web applications. Managing a hybrid multi-cloud solution across hundreds of applications is always a challenge. 

Datadog agents on each web host, and native integrations with GitHub, AWS, and Azure gets all of our instrumentation and error data in one place for easy analysis and monitoring.

How has it helped my organization?

Through the use of Datadog across all of our apps, we were able to consolidate a number of alerting and error-tracking apps, and Datadog ties them all together in cohesive dashboards. 

Whether the app is vendor-supplied or we built it ourselves, the depth of tracing, profiling, and hooking into logs is all obtainable and tunable. Both legacy .NET Framework and Windows Event Viewer and cutting-edge .NET Core with streaming logs all work. The breadth of coverage for any app type or situation is really incredible. It feels like there's nothing we can't monitor.

What is most valuable?

Centralized pipeline tracking and error logging provide a comprehensive view of our development and deployment processes, making it much easier to identify and resolve issues quickly. 

Synthetic testing has been a game-changer, allowing us to catch potential problems before they impact real users. Real user monitoring gives us invaluable insights into actual user experiences, helping us prioritize improvements where they matter most. 

The ability to create custom dashboards has been incredibly useful, allowing us to visualize key metrics and KPIs in a way that makes sense for different teams and stakeholders. 

These features form a powerful toolkit that helps us maintain high performance and reliability across our applications and infrastructure, ultimately leading to better user satisfaction and more efficient operations.

What needs improvement?

I'd like to see an expansion of the Android and IOS apps to have a simplified CI/CD pipeline history view. 

I like the idea of monitoring on the go, yet it seems the options are still a bit limited out of the box. While the documentation is very good considering all the frameworks and technology Datadog covers, there are areas - specifically .NET Profiling and Tracing of IIS-hosted apps - that need a lot of focus to pick up on the key details needed. 

In some cases the screenshots don't match the text as updates are made. I spent longer than I should have figuring out how to correlate logs to traces, mostly related to environmental variables.

For how long have I used the solution?

I've used the solution for about three years.

What do I think about the stability of the solution?

We have been impressed with the uptime and clean and light resource usage of the agents.

What do I think about the scalability of the solution?

The solution has been very scalable and customizable.

How are customer service and support?

Sales service is always helpful in tuning our committed costs and alerting us when we start spending outside the on-demand budget.

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

We used a mix of a custom error email system, SolarWinds, UptimeRobot, and GitHub actions. We switched to find one platform that could give deep app visibility regardless of whether it is Linux or Windows or Container, cloud or on-prem hosted.

How was the initial setup?

Generally simple, but .NET Profiling of IIS and aligning logs to traces and profiles was a challenge.

What about the implementation team?

We implemented the solution in-house. 

What was our ROI?

I'd count our ROI as significant time saved by the development team assessing bugs and performance issues.

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

Set up live trials to asses cost scaling. Small decisions around how monitors are used can have big impacts on cost scaling. 

Which other solutions did I evaluate?

NewRelic was considered. LogicMonitor was chosen over Datadog for our network and campus server management use cases.

What other advice do I have?

Excited to dig further into the new offerings around LLM and continue to grow our footprint in Datadog. 

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?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Tejaswini A - PeerSpot reviewer
Application Engineer at Discover Financial Services
User
Top 20
Consolidates all our logs into a single place, making it easier to find errors
Pros and Cons
  • "The best way it has helped us is by consolidating all our logs into a single place and making it easier to find errors."
  • "Another issue that I have is with the search syntax, it could be simpler and it feels like there are too many ways to do the same things."

What is our primary use case?

We have a tech stack including all backend services written in TS/Node (mostly) and as a full stack engineer, it is crucial to keep track of new and existing errors. Our logs have been consolidated in Datadog and are accessible for search and review, so the service has become a daily tool for my work. 

More recently, session replay has been adopted at my company, but I do not like it so much because the UI elements are not in their place, so it is very hard to see what the users on the web app are actually clicking on.

How has it helped my organization?

The best way it has helped us is by consolidating all our logs into a single place and making it easier to find errors. Previously using AWS Cloudwatch was cumbersome and time-consuming. One issue I do have with logs is the length of time they are on the platform. Some issues happen sporadically, so it would be good to have logs for longer than one month by default or make it a configuration. 

Another issue that I have is with the search syntax, it could be simpler and it feels like there are too many ways to do the same things.

What is most valuable?

Logs search is the most valuable feature because it has consolidated all of our backend services logs into one place. Now we can see the relationship between them as requests are going from one service to other dependencies. 

What needs improvement?

One issue I do have with logs is the length of time they are on the platform. Some issues happen sporadically, so it would be good to have logs for longer than one month by default or make it a configuration. I have yet to try rehydrating logs, so this might be an option I need to try. Another issue I have is with the search syntax, it could be simpler. The syntax is a bit cumbersome and there is not an intuitive to save them to look for similar searches in the future. 

Finally, while my company replaced a different tool for session replay with DataDog's version, I find it clunky and in need of further improvements. For example, when troubleshooting a web portal issue, it is super important to know what the user clicked, but the elements are not where they should be in the replay.

It is also hard to find details about the sessions, and metadata such as user email, account, etc. that exist on other services with replay features.

For how long have I used the solution?

I have been using Datadof for approximately five years.

What do I think about the stability of the solution?

So far we haven't had any issues with uptime and Datadog has been available when needed.

What do I think about the scalability of the solution?

It seems to scale well as we continue to add services that need monitoring.

How are customer service and support?

I haven't had to contact support.

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

Cloudwatch was not a great tool for what we need to do to troubleshoot issues.

What about the implementation team?

We deployed it in-house with intermediate expertise.

What was our ROI?

I am not sure how much we are paying, but I use the app often enough to feel like we are getting a good ROI.

Which other solutions did I evaluate?

I was not involved in the choosing process as a software engineer

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Nuno Rosa - PeerSpot reviewer
Principal Consultant at Infosys
MSP
Top 10
Easy to set up and good UI but needs better customization capabilities
Pros and Cons
  • "The many dozens of integrations that the solution brings out of the box are excellent."
  • "Deploying the agents is still very manual."

What is our primary use case?

The solution is basically used for servers and applications.

What is most valuable?

The UI, basically, is the most valuable aspect of the solution. I really like the look and feel of the solution. It's not very distinctive now since other players have caught up, however, they were the first in the market to present such an effective UI. 

The many dozens of integrations that the solution brings out of the box are excellent.

It's easy to set up.

What needs improvement?

Deploying the agents is still very manual. 

Network monitoring could be better or rolled into this solution so that you do not have to buy a different product.

Customization of the tool itself should be taken into account. At the moment, although what they provide out of the box is good, they don't offer many customization possibilities. I know it's difficult, however, it's something that they would need to look at. When the customer gets some customization, they want customized requirements. We cannot do it. 

For how long have I used the solution?

I've been dealing with the solution for five years. 

What do I think about the stability of the solution?

It's quite stable. I have never had an issue in regard to reliability, so it's very stable.

What do I think about the scalability of the solution?

It's very scalable. I have not reached the limits at any time, never in the solution. I've never seen any performance degradation in large environments. I would say it's very scalable.

Each client has its own instance. We do not share instances with multiple customers. There's usually between 20 and 30, depending on the customer.

How are customer service and support?

I never use technical support, to be honest.

How was the initial setup?

The initial setup for the solution itself is quite straightforward. You just set it up and that's it. However, when it comes to, for instance, deploying the agents to the servers, or at least the target machines, it's still a manual task. They still do not have centralized management of the FD agents, which basically delays the deployment of the solution. It's very manual still.

How long it takes to deploy is difficult to pin down. It will vary based on the environment size. Obviously, if it's ten servers, it will basically take half an hour or one hour. If it's 5,000, obviously, besides the number of notes, other considerations will need to be taken into account. If t's a large environment, it will take much longer. We would need to basically develop a solution, or an effective process to deploy the agent and configure them in a standardized manner. This is something that the tool itself or the tool provider does not offer out of the box. You need to build it. That's a drawback.

How many people you need for the deployment and maintenance processes depends on the environment's size and geographical area. On average,  I would usually require for every 500 notes, one resource for implementation. Then for overall support, I usually put one resource per 1500.

What was our ROI?

Before, the ROI was much higher as you would not have to compete with any kind of tool since they were very good in the space. However, with time, other companies have picked up the slack. Now, you have other tools which provide a higher ROI. I cannot give a specific ROI percentage since I don't use it for personal use with deployment. We deploy it on behalf of customers. Obviously, depending on the deal, depending on the size, and the ROI will vary. If people are looking for a global monitoring solution in the same tool as Datadog network monitoring, they are always hindered as Datadog does not provide an adequate solution for it. That kind of decreases the ROI since you still need to get another tool to do the network monitoring.

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

The licensing is a bit complicated. When you pay for it on a note basis, that's perfectly fine. However, when you put log analytics on top of it, it's based on traffic. This is actually an issue. It gets complicated.

What other advice do I have?

I'm providing Datadog. I'm a retailer.

I would recommend the solution. 

I would suggest if their environment is in the cloud, companies have their environments in the public cloud, such as GCP, Azure, or AWS. Datadog is a very good candidate to provide an overview of the monitoring. If you want to consider a hybrid solution where systems and servers and applications also provide a good solution and have a lot of APM capabilities, the only drawback will be network monitoring. When you grab a tool that you want to basically monitor the entire environment at a single point of contact, with Datadog, it's possible, however, there's not an effective tool to do network monitoring.

I'd rate the solution seven out of ten.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer:
PeerSpot user
Bharath Babu  Kasimsetty - PeerSpot reviewer
Director at CBRE
Real User
Flexible, excellent support, and reliable
Pros and Cons
  • "The most valuable features of Datadog are the flexibility and additional features when compared to other solutions, such as AppDynamics and Dynatrace. Some of the features include AI and ML capabilities and cloud and analysis monitoring"
  • "Datadog could improve the flexibility with AI and ML concepts. This will allow customers to be more leveraged towards publishing."

What is most valuable?

The most valuable features of Datadog are the flexibility and additional features when compared to other solutions, such as AppDynamics and Dynatrace. Some of the features include AI and ML capabilities and cloud and analysis monitoring 

What needs improvement?

Datadog could improve the flexibility with AI and ML concepts. This will allow customers to be more leveraged towards publishing.

For how long have I used the solution?

I have been using Datadog for approximately one year.

What do I think about the stability of the solution?

Datadog is stable. We did not have a single outage.

What do I think about the scalability of the solution?

I have found Datadog to be scalable.

We have approximately 2,000 users using the solution in my organization.

How are customer service and support?

The support from Datadog is excellent.

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

I have previously used AppDynamics and Dynatrace. 

How was the initial setup?

Datadog's initial setup is easy because they have helped us come up with the easiest way of instrumenting any of the features which need to be deployed.  We worked on it with their engineers and we were able to happily do it. We have done approximately 60 application monitoring through Datadog since our deployment.

What about the implementation team?

We have a very tiny team of four members that do the maintenance of Datadog.

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

The price of Datadog is reasonable. Other solutions are more expensive, such as AppDynamics.

What other advice do I have?

Datadog is far better than any other monitoring tool in introducing any of the new capabilities because they think before Amazon AWS and Microsoft Azure before they introduce the concepts. Datadog is a good tool to have for monitoring your own infrastructure.

I rate Datadog a ten out of ten. 

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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reviewer1599867 - PeerSpot reviewer
Senior Performance and Architecture Analyst at a manufacturing company with 10,001+ employees
Real User
Top 20
Great technology with a nice interface
Pros and Cons
  • "The solution is stable."
  • "The technology itself is generally very useful and the interface is great."
  • "There should be a clearer view of the expenses."
  • "I find the setup cost to be too expensive. The setup cost for Datadog is more than $100. I am evaluating the usage of this solution, however, it is too expensive."

What is most valuable?

The technology itself is generally very useful and the interface it great.

What needs improvement?

There should be a clearer view of the expenses.

For how long have I used the solution?

I have used the solution for four years.

What do I think about the stability of the solution?

The solution is stable.

How are customer service and support?

I have not personally interacted with customer service. I am satisfied with tech support.

How would you rate customer service and support?

Neutral

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

I am using ThousandEyes and Datadog. Datadog supports AI-driven data analysis, with some AI elements to analyze, like data processing tools and so on. AI helps in Datadog primarily for resolving application issues.

How was the initial setup?

It was not difficult to set up for me. There was no problem.

What was our ROI?

I can confirm there is a return on investment.

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

I find the setup cost to be too expensive. The setup cost for Datadog is more than $100. I am evaluating the usage of this solution, however, it is too expensive.

What other advice do I have?

I would rate this solution eight out of ten. 

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.
Updated: March 2025
Buyer's Guide
Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.