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Datadog OverviewUNIXBusinessApplication

Datadog is #2 ranked solution in APM tools, #2 ranked solution in best Network Monitoring Tools, #2 ranked solution in Infrastructure Monitoring tools, #2 ranked solution in top Cloud Monitoring Software, #2 ranked solution in top AIOps tools, and #3 ranked solution in Log Management Software. IT Central Station users give Datadog an average rating of 8 out of 10. Datadog is most commonly compared to Dynatrace:Datadog vs Dynatrace. Datadog is popular among the large enterprise segment, accounting for 58% of users researching this solution on IT Central Station. The top industry researching this solution are professionals from a computer software company, accounting for 30% of all views.
What is Datadog?
Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
Datadog Buyer's Guide

Download the Datadog Buyer's Guide including reviews and more. Updated: November 2021

Datadog Customers
Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's
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Pricing Advice

What users are saying about Datadog pricing:
  • "My advice is to really keep an eye on your overage costs, as they can spiral really fast."
  • "If you do your homework, you'll find that if you're really concerned with cost, it's good."
  • "It is easy to run up a large bill, so become familiar with the cost of each piece of your bill and use the metrics they supply to estimate and monitor your bill."
  • "Pricing seemed easy until the bill came in and some things were not accounted for."
  • "Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick."
  • "The cost is high and this can be justified if the scale of the environment is big."
  • "It has a module-based pricing model."

Datadog Reviews

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reviewer1494894
Senior Manager, Site Reliability Engineering at Extra Space Storage
Real User
Top 20
Provides insightful analytics and good visibility that assist with making architectural decisions

Pros and Cons

  • "Datadog has given us near-live visibility across our entire cloud platform."
  • "We have recently had a number of issues with stability and delays on logging, monitoring, metric evaluation, and alerts."

What is our primary use case?

We primarily use Datadog for logs, APM, infrastructure monitoring, and lambda visibility.

We have built a number of critical dashboards that we display within our office for engineers to have a good understanding of the application performance, as well as business partners to understand at a high level the traffic flowing through the app.

We started with logging, as our primary monitor, and have shifted to APM to get a deeper understanding of what our system is doing, and how the changes we are making impact the apps.

How has it helped my organization?

Datadog has given us near-live visibility across our entire cloud platform. We are finally in a state where we are alerting our users about degraded performance well before the helpdesk tickets start rolling in.

We are making major architectural decisions based on the data we are getting from Datadog. It also gives us an idea of where the complexity really lies in some older, monolithic apps. 

We have used the APM endpoint monitoring to prioritize work on slower endpoints because we can see the total count, as well as the latency. That has been a big driver in our refactor work prioritization.

We have struggled to get more business-centric measures in our code to surface actual business values in our reports, but that is our next initiative.

What is most valuable?

We started with Log analytics in the beginning stages of our monitoring journey. Those were very insightful, but obviously only as useful as we made them with good logging practices.

The dashboards we created are core indicators of the health of our system, and it is one of the most reliable sources we have turned to, especially as we have seen APM metrics impacted several times lately. We can usually rely on logs to tell us what the apps are doing.

APM and Traces have been crucial to understanding how users are actually using the app. That drives a lot of our decisions around refactoring and focusing our limited engineering resources.

What needs improvement?

Continued improvement around cost and pricing model is needed. It is pretty complex and takes a fair amount of intimate knowledge to know exactly how turning on a single function is going to impact your bill, especially when you don't see the metrics for a day or two. 

We have recently had a number of issues with stability and delays on logging, monitoring, metric evaluation, and alerts. More often than not in the past month, it seems that we get the banner across the to of our dashboards that some service is impacted. They don't always show up on the incident page, either.

For how long have I used the solution?

We have been using Datadog for two years.

What do I think about the stability of the solution?

Overall, it has been fairly stable for us. There are the occasional issues with importing data, that has usually been resolved in a short time. We have never had an issue where that data was lost, just delayed, and eventually backfilled. 

It seems (anecdotally, of course) that there have been a few more stability issues lately. We have noticed several days that we are getting in-app alert banners indicating that some metric or log ingestion was delayed, or the web app itself was experiencing severe slowness. 

Overall, these issues are resolved rather quickly - kudos to their engineering teams. I hear that they actually use Datadog to monitor Datadog. 

What do I think about the scalability of the solution?

Datadog is very scalable but just watch the cost.

How are customer service and technical support?

Technical support is hit and miss; there are a number of nuances to how this tool should be implemented, and it is difficult to re-explain how our infrastructure and applications are set up every time we need an in-depth investigation to understand what is broken.

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

Previously, we used AppDynamics. The pricing model didn't seem to fit with actual cloud spend. Now we may have swung the pendulum a little too far, and seem to be dealing with pricing on every facet of the application. 

How was the initial setup?

The initial setup was pretty straightforward. Additional tweaks and configuration have been a bit more difficult as we get deeper and deeper into the guts of the integrations. Making sure we are keeping up with a rapid release schedule, and keeping our server clients in sync with our app packages has been troublesome. There have been some major changes in the APM that have introduced a number of bugs and broken some of our dashboards and alerts.

What about the implementation team?

Our in-house team handled the deployment, with a lot of tickets created for the Datadog team.

What was our ROI?

ROI is difficult to measure completely. Our first year spend compared to our second and now going into the third year spend have been significantly different.

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

My advice is to really keep an eye on your overage costs, as they can spiral really fast. We turned on some additional span measures and didn't realize until it was too late that it had generated a ton.

Frankly, we love the visibility it gives us into our applications, but it is a bit cumbersome to ensure we are paying for the right stuff. Overall, the cost is worth it, as it helps us keep system-critical applications up and running, and reduces our detection and correction times significantly.

Which other solutions did I evaluate?

We evaluated Dynatrace and AppD before choosing this product.

What other advice do I have?

Datadog requires pretty close supervision on the usage page to ensure you aren't going out of control. They have provided a bunch of new features to assist in retention percentage, but it can be a bit confusing on what is being retained, and what can be viewed again after triggering an alert. It's a difficult balance of making sure you are getting the right data for alerts, and still having the correct information still available for research after the fact.

Which deployment model are you using for this solution?

Public Cloud

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

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
BrianHeisler
Principal Enterprise Systems Engineer at a healthcare company with 10,001+ employees
Real User
Top 20
An out-of-the-box solution that allows you to quickly build dashboards

Pros and Cons

  • "I like that you can build out a dashboard pretty quickly. There are some things that come out of the box that you don't really need to do, which is great because they're default settings."
  • "I think better access to their engineers when we have a problem could be better."

What is our primary use case?

We deploy agents on-premise to collect data on on-premise VM instances. We don't use Datadog in our cloud network. We do have some Cloud apps that we have it on and we also have Containers. We have it on their headquarters, the main software for them is on their own Cloud.

Eventually, we're building out the process now and using it better. We plan to use Datadog for root cause analysis relating to any kinds of issues we have with software, with applications going down, latency issues, connection issues, etc. Eventually, we're going to use Datadog for application performance, monitoring, and management. To be proactive around thresholds, alerts, bottlenecks, etc. 

Our developers and QA teams use this solution. They use it to analyze network traffic, load, CPU load, CPU usage, and then Tracey NPM, API calls for their application. There are roughly 100 users right now. Maybe there's 200 total, but on a given day, maybe 13 people using this solution.

How has it helped my organization?

It hasn't improved the way our organization functions yet, because there's a lot of red tape to cut through with cultural challenges and changes. I don't think it's changed the way we do things yet, but I think it will — absolutely it will. It's just going to take some time.

What is most valuable?

I like that you can build out a dashboard pretty quickly. There are some things that come out of the box that you don't really need to do, which is great because they're default settings. Once you install the agent on the machine, they pick up a lot of metrics for you that are going to be 70 or more percent of what you need. Out of the box, it's pretty good.

For how long have I used the solution?

I have been using Datadog every day since September 2020. I also used it at a previous company that I worked for.

What do I think about the stability of the solution?

Stability-wise, it's great.

What do I think about the scalability of the solution?

It seems like it'll scale well. We're automating it with Ansible scripts and service now so that when we build a new virtual machine it will automatically install Datadog on that box.

How are customer service and technical support?

The tool itself is pretty good and the customer service is good, but I think they're a growing company. I think better access to their engineers when we have a problem could be better. For example, if I asked the question, "Hey, how do I install it on this type of component?" We'll try to get an engineer on the phone with us to step us through everything, but that's a challenge because they're so busy.

Technically-wise, everything's fine. We don't need any support, everything that I need to do, I can do right out of the box. But as far as, in the knowledge of their engineers on how to configure it on given systems that we have, that's maybe at six because they're just not as available as I would've hoped.

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

We were using AppDynamics. Technically, we still have it in-house because it's tightly wound into certain systems, but we'll probably pull that off slowly over time. The reason we added Datadog and eventually we'll fully switch over is due to cost. It's more cost-friendly to do it with Datadog.

Which other solutions did I evaluate?

Yes, we looked at Dynatrace, AppDynamics, and New Relic. Personally, I wouldn't have chosen Datadog for the POC if it were up to me. Datadog was a leader, but New Relic was looking really good. In the end, the people above me decided to go with Datadog — it's a big company, so they wanted to move fast, which makes sense.

What other advice do I have?

If you're interested in using Datadog, just do your homework, as we did. We're happy so far I think; time will tell as we are still rolling things out. It's a very good company. It's going to be a year before we really can tell anything. If you do your homework, you'll find that if you're really concerned with cost, it's good.

There are some strengths that AppDynamics and Dynatrace have that Datadog I don't think will have down the road, but they're not things we necessarily need — they're outliers. It would be nice to have them, but we can manage without them.

Know what you want. There is no need to pay for solutions like Dynatrace or AppDynamics that are more expensive or things that are just nice to have if you don't absolutely need to have them. That's something people need to understand. You just have to make sure you understand what it is that you need out of the tool — they are all a little different, those three. I would say to anybody that's going with Datadog: you just have to be patient at the beginning. It's a very busy company right now. They're very hot in the market.

Overall, on a scale from one to ten, I would give Datadog a rating of eight. It does what we need it to do, and it seems to be pretty user-friendly in terms of setting things up.

Features-wise, I'd give them a rating of ten out of ten. The better access we get to assistance from the engineers on how to configure dashboards and pulling metrics that we need, that would bring it up a little bit. So overall it would be harder and it would have to be perfect for it. I would say maybe they could bring it to a nine.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: November 2021.
552,695 professionals have used our research since 2012.
reviewer1479957
Senior Director of DevOps at Housecall Pro
Real User
Good graphing and dashboards, and it improves visibility for developers

Pros and Cons

  • "Having a wealth of information has helped us investigate outages, and having historical data helps us tune our system."
  • "Datadog has a lot of documentation, but a lot of that documentation assumes you know how the service works, which can lead to confusion."

What is our primary use case?

We primarily use Datadog for the monitoring of EC2 and ECS containers running mostly Rails applications that host a SaaS product. We also monitor ElasticSearch and RDS, and we are working on adding their Application Performance Monitoring solution to monitor our applications directly.

We use DataDog to create dashboards, graphs, and alerts based on interesting metrics. DataDog is our first place to look to find the performance of our system.

We also use their logging platform and it works well. Especially useful is that the logs and metrics are tightly integrated so you can jump between them easily.

How has it helped my organization?

Developers are able to see how code is running in production, where this was mostly opaque previous to us implementing DataDog. We are able to emit custom metrics that are specific to our business, and the built-in metrics have also proven useful. Having a wealth of information has helped us investigate outages, and having historical data helps us tune our system.

DevOps engineers are able to put sensors around our system to proactively detect problems, whereas before, our engineers heard about problems from customers. Logs are easier to find for developers.

What is most valuable?

Metric graphing and Dashboards are the most valuable features because they give us good observability into our system and work well to alert us when interesting things happen. We use this functionality daily.

We value the monitoring capability since it allows us to be pushed alerts, rather than have to observe graphs continually. The integrations with Slack and PagerDuty enable us to be interrupted appropriately and keep a running tab on the system without bothering us unnecessarily.

The online process monitoring has been extremely helpful, as it gives engineers the ability to see the live status of all the processes running our systems without them having to log in.

What needs improvement?

Their logging solution is expensive for our use case. They do have the capability to rehydrate old or incomplete logs, and it works, but I would rather not have to think about that operation.

Datadog has a lot of documentation, but a lot of that documentation assumes you know how the service works, which can lead to confusion. Positive note is that they do have lots of documentation, it just needs better curation.

Their APM solution still needs some work, but they are actively developing it. I would also like to see more database-specific application monitoring.

For how long have I used the solution?

I have been using Datadog for five years across two companies.

What do I think about the stability of the solution?

Any issues are addressed and communicated very quickly. I have not had any issues with uptime.

What do I think about the scalability of the solution?

If you do not need 100% of data such as logs, APM traces, etc., this scales well. It does not scale as well if you want 100% of your logs indexed. You should understand any other usage-based bills before using any part of their service as it is very easy to run up a large bill.

The performance of the system scales very well, and host monitoring and APM are relatively cheap.

How are customer service and technical support?

Account support is excellent.

Customer support is good if you get them to go beyond pointing out the right documentation.

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

Previously, I used homebuilt solutions with Nagios and Cacti but found that there was far too much work to understand them and keep them up and fed compared to the value that I got. They also did not integrate well with existing data sources without a lot of effort.

I also previously used StackDriver and found it too opinionated. I like that DataDog gives you tools to work with certain types of data and make your own graphs, monitors, etc., whereas, with StackDriver, I felt like there were a limited number of ways you could accomplish goals.

How was the initial setup?

The basic setup is easy. A more advanced setup can be tricky because the documentation assumes you know how the system works already. Support is somewhat helpful, but mostly points out the documentation you should already have found.

What about the implementation team?

We implemented in-house.

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

My advice is to understand what number of hosts and data you want to commit to. Beware that usage-based billing is both a blessing and a curse. It is easy to run up a large bill, so become familiar with the cost of each piece of your bill and use the metrics they supply to estimate and monitor your bill.

I have had good luck with their support team helping us to figure out the correct commit levels. Their account support is excellent in this regard. I have heard their sales team can be aggressive, but I have not experienced it personally.

Which other solutions did I evaluate?

I originally chose Datadog because of my previous experience. We recently considered moving over to New Relic because we liked their APM solution better. However, the pricing of New Relic and our familiarity with Datadog won over. New Relic is a good product but it didn't fit our overall needs as well as Datadog.

Which deployment model are you using for this solution?

Public Cloud

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

Disclosure: I am a real user, and this review is based on my own experience and opinions.
reviewer1476039
Network Engineer / AWS Cloud Engineer / Network Management Specialist at CareFirst
Real User
Top 20
Good visualizations and dashboards help to minimizes downtime and resolve issues quickly

Pros and Cons

  • "The most valuable feature is the dashboards that are provided out of the box, as well as ones we were able to configure."
  • "More pre-configured "Monitor Alerts" would be helpful."

What is our primary use case?

We were in need of a cloud monitoring tool that was operationally focused on the AWS Platform. We wanted to be able to responsibly and effectively monitor, troubleshoot, and operate the AWS platform, including Server, Network, and key AWS Services.

Tooling that highlighted and detected problems, anomalies, and provided best practice recommendations. Tooling that expedites root-cause analysis and performance troubleshooting.

    Datadog provided us the ability to monitor our cloud infrastructure (network, servers, storage), platform/middleware (database, web/applications servers, business process automation), and business applications across our cloud providers.

    How has it helped my organization?

    Datadog provided us the tooling to help us effectively monitor, troubleshoot, and operate the AWS platform, including Server, Network, Database, and key AWS Services. It highlights detected problems and anomalies and provides best practice recommendations, expedites root-cause analysis, and performance troubleshooting.

    Datadog provides analytics and insights that are actionable through out-of-the-box visualizations, dashboards, aggregation, and intuitive searching that shortens the time to value and account for our limited time & resources we have to operate in production.

    What is most valuable?

    The most valuable feature is the dashboards that are provided out of the box, as well as ones we were able to configure. Specific Dashboards that were provided that made things easier were EC2, RDSKubernetes dashboards.

    We also use the logging tool, which makes searching for specific error logs easier to do.

    Datadog Logging provides the capability for us to use AWS logs such as VPC Flow Logs, ELB, EC2, RDS, and other logs that provide lots of relevant operational data but are not actionable. Datadog provides a tool that can provide us analytics and insights that are actionable for visualizations, dashboards, alerting, and intuitive searching.

      What needs improvement?

      More pre-configured "Monitor Alerts" would be helpful. Datadog's knowledge of its customers and what they are looking for in terms of monitoring and alerting could be taken advantage of with pre-canned alerts. They have started this with "Recommended Monitors".  That feature was very helpful when configuring our Kubernetes alerts. More would be even better. 

      Datadog tech support is very good. One area that could be more helpful is actually talking to someone or sharing your screen to help troubleshoot issues that arise. For new cloud engineers just coming into the cloud monitoring field, there is a learning curve. There is a lot to learn and figure out. For example, we still ran into some issues configuring the private link and more videos of how to do things could be of use.

      For how long have I used the solution?

      We have been using Datadog for one year.

      What do I think about the stability of the solution?

      We have not run into any issues with stability.

      What do I think about the scalability of the solution?

      The scalability of Datadog is very good.

      How are customer service and technical support?

      Customer service has been excellent.  I communicate weekly a Datadog Customer Success Manager.  He helps me followup on any open issues or questions that we may have.  Technical support has been very good. Opening tickets is easy.  Sometimes a Tech Engineer may take a bit of time to get back with you.  Communicating with Tech Engineer has to be done via ticket/email - no phone assistance is available.

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

      we did not.

      How was the initial setup?

      Procedures for setup seemed straightforward but once you got going, there were some issues. For us, getting our private link to work needed additional tech support. They were able to help us resolve the issue we were experiencing. I think the procedures could be done a bit better to help you with setup.

      What about the implementation team?

      We deployed it ourselves.

      What was our ROI?

      Datadog helps us minimize downtime and helps us resolve issues quickly.  

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

      Pricing seemed easy until the bill came in and some things were not accounted for. The issue may have been that we didn't realize what was being accounted for, such as the number of servers and the number of logs being ingested.

      Datadog had really good pre-sale reps that work with us but need to make sure all the details are covered.

      Which other solutions did I evaluate?

      The solution we were looking for needed to provide out-of-the-box capabilities that shorten the time to value. We had limited time & limited resources. Datadog had high recommendations in these areas, so we decided to do a trial with them.

        What other advice do I have?

        We are very pleased with Datadog overall.

        Datadog has assigned an account rep to us that meets with us regularly to make sure all our needs are being met and help us get answers to any questions or issues we are running up against. They have been of great helping us standup monitoring of our Kubernetes environment.

        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)
        Disclosure: I am a real user, and this review is based on my own experience and opinions.
        reviewer1477686
        Senior DevOps Engineer at DigitalOnUs
        Real User
        Top 20
        Affordably-priced and improves visibility of infrastructure, apps, and services

        Pros and Cons

        • "Having a clear view, not only of our infrastructure but our apps and services as well, has brought a great added value to our customers."
        • "The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances."

        What is our primary use case?

        Our primary use of Datadog includes: 

        • Keeping a close look into our AWS resources. Monitoring our multiple RDS and ElastiCache instances play a big role in our indicators.
        • Kubernetes. We aren't using all of the available Kubernetes integrations but the few of them that work out of the box adds great value to our metrics.
        • Monitoring and alerting. We wired our most relevant monitoring and alerts to services like PagerDuty, and for the rest of them, we keep our engineers up to date with constant Slack updates. 

        How has it helped my organization?

        Observability is something that a lot of Companies are trying to achieve. Having a clear view, not only of our infrastructure but our apps and services as well, has brought a great added value to our customers.

        For a logging solution, we use to have Papertrail. It did the trick but having a single point that manages and indexes all the logs is a BIG improvement. Also, having the option to generate metrics from logs is a game-changer that we're trying to include in our monitoring strategy.

        I would like to say the same about APM but the support for PHP seems to be somewhat lacking. It works but I think this service could provide us more information.

        What is most valuable?

        With respect to logs, we used to integrate various kinds of tools to achieve very basic tasks and it always felt like a very fragile solution. I think logs are by far the most useful feature and at the same time, the one that we could improve.

        APM - This is either a hit or miss, allow me to explain: we use various programming languages, mainly PHP and Ruby, and the traces generated don't always provide all of the information we want. For example, we get a great level of detail for the SQL queries that the app generates but not so much for the PHP side. It's hard to track where exactly where all of the bottlenecks are, so some analysis tools for APM could make a good addition.

        What needs improvement?

        Please add PHP profiling; you already have it for other popular programming languages such as Python and Java, which is great because we have a little bit of those, but our main app is powered by PHP and we don't have profiling for this yet. I guess it's only a matter of time for this to be added, so in the meanwhile, you can consider this review as a vote for the PHP profiling support.

        The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances.

        For how long have I used the solution?

        We have been using Datadog for one year.

        What do I think about the stability of the solution?

        It's pretty stable for the main integrations. There was only one time where Datadog was down and that was scary since all of our monitoring is handled by Datadog. There was a lot of uncertainty while the outage was in place.

        What do I think about the scalability of the solution?

        For everyday use, it's adequate, but for very specific tasks, not so much. There was a time where I had to do a big export and as expected, the API is somewhat limited. Since it was a one-time task, it was not a big deal but if this was a regular task, I wouldn't be happy about it.

        How are customer service and technical support?

        For small tasks, I think it's great. For specialized support, it feels like you're under-staffed, having to wait days/weeks for a solution is a big NO-NO.

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

        I've used a few other products such as NewRelic and AppDynamics. The switch is usually affected by two factors: pricing and convenience.

        How was the initial setup?

        Getting APM metrics out of Kubernetes is always a painful task. We got support to take a look at this and we had to go through various iterations to get it right, and then AGAIN the next year. This was a bad experience.

        What about the implementation team?

        It was all implemented in-house. The documentation is fairly up to date, for the most part.

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

        Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick.

        Which other solutions did I evaluate?

        Unfortunately, it wasn't my call to include Datadog for this Company but sure I'm glad that the Lead Architect took this decision. It brought many improvements in a small span of time.

        What other advice do I have?

        Please add PHP profiling soon!

        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.
        reviewer1493811
        Sr. Architect - SaaS Ops at CommVault
        Vendor
        Top 20
        Improves infrastructure visibility, integrates well, and fine-tuning the monitors is easy to do

        Pros and Cons

        • "The ability to send notifications based on metadata from the monitor is helpful."
        • "Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."

        What is our primary use case?

        We primarily use DataDog for performance and log monitoring of cloud environments, which include VMs and Azure Services like Azure compute, storage, network, firewall, and app services via event hubs.  

        Alerting based on monitors via teams and PagerDuty

        Logs collection for Azure services like Azure database, Azure Application Gateway, Azure AKS, and other Azure services.

        Custom metrics using a Python script to collect metrics for components not natively supported by Datadog.

        Synthetic testing to ensure uptime and browser tests via CI/CD pipeline.

        How has it helped my organization?

        Datadog has improved our visibility into infrastructure topology and performance. It provided a simplified view and ability to drill down to system performance, process usage, and logs.

        We were able to set up monitors for infrastructure and applications, as the metrics were readily available in the platform. Fine-tuning monitors is very easy and the ability to configure monitor alerts with details on how to resolve the alert is a key value add. 

        Integration with PagerDuty, teams ensure timely alerting. PagerDuty integration bring tags from Datadog to PagerDuty, which is very useful in routing incidents to the right service

        What is most valuable?

        The Host Map, Live Process provides performance metrics of our application. The support team likes using Datadog for identifying resources affected and obtaining the logs. 

        Monitors are easy and quick to setup. Metrics are easily accessible and quick to use. The ability to send notifications based on metadata from the monitor is helpful. The setup for monitors is one time and it works for all workloads, whether it is Azure or any other cloud.

        Logs rehydration helps us archive and rehydrate logs as we need. We don't need logs to be indexed at all times. Logs are required only for escalations and rehydrating does the job and provides cost savings.

        What needs improvement?

        We need the ability to create a service dependency map like Splunk ITSI. We have to build this in PagerDuty and it's not the best user experience. The ability to create custom inventory objects based on logs ingested would be a value add. It would be better if Datadog makes this a simple click and enable.

        It would be helpful to have the ability to upgrade agents via the Datadog portal. Once agents are connected to the Datadog portal, we should be able to upgrade them quickly.

        Security monitoring for Azure and Operating System (Windows and Linux) are features that need to be addressed.

        Dashboards for Azure Active Directory metrics and events should be improved.

        For how long have I used the solution?

        We have been using Datadog for more than six months.

        What do I think about the stability of the solution?

        Stability-wise, it has been good.

        What do I think about the scalability of the solution?

        The scalability is good so far. 

        How are customer service and technical support?

        Support team has been very responsive. Only complain is on issues they don't understand, they should have a quick call and unblock the customer.

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

        We didn't have a solution in place. The only thing we had were logs.

        How was the initial setup?

        Setup is hassle-free and pretty straightforward. 

        What about the implementation team?

        I deployed it myself.

        What was our ROI?

        No returns yet. We are in growth mode. If this becomes expensive we may have to look at alternative options.

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

        The cost is high and this can be justified if the scale of the environment is big.

        Datadog needs to provide better pricing for large customers.

        Which other solutions did I evaluate?

        Prior to implementing Datadog, we evaluated Splunk.

        What other advice do I have?

        Overall, the Datadog product is really good.

        It doesn't need a sales team and yet, the sales team has screwed up on some occasions. It's a great product and the customer success needs to put an extra effort to help customers with best practices rather than passing them off to support.

        Customer success doesn't evangelize product features and the customer doesn't know what new is coming unless they ask about it.

        Which deployment model are you using for this solution?

        Public Cloud

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

        Microsoft Azure
        Disclosure: I am a real user, and this review is based on my own experience and opinions.
        PN
        Head of Digital & Cognitive Services at a tech company with 11-50 employees
        Real User
        Top 5Leaderboard
        Provides seamless monitoring, increases visibility, and optimizes the time spent on monitoring and management activities, but needs an artificial intelligence component

        Pros and Cons

        • "Its integration definitely stands out. It provides seamless monitoring of all our systems, services, apps, and whatever else we secure and monitor. Visualizations have become simpler with dashboards. We are getting visibility into systems, services, and apps stack through a single pane of glass, which is good. We are able to put logs in context."
        • "It can have an artificial intelligence component. Even though I can seamlessly look at end-to-end security, it would be better to have alerts and notifications powered by an AI engine. I am not sure if they have an AI component. We have not reached out to them or looked at it, but this is something that I keep on talking about within our company in terms of features. Such a feature would be good to have, and it would further optimize my Security Ops team's abilities."

        What is our primary use case?

        We use it for monitoring and instrumentation of security. We secure our databases and servers. It is typically for the security of apps, services, and systems. We are using its latest version.

        How has it helped my organization?

        It has reduced some challenges, and it has optimized the time spent on monitoring and management activities. It has improved the visualization and the ability to monitor and control.

        Datadog increases our visibility. It puts all the data in one log so that we can use that log in a contextual manner. Some operational optimizations definitely have happened with this solution. In general, the user community is happier than before. We are basically asking them every quarter how happy they are on a scale of zero to five. That needle has moved but not significantly. If it was 3 earlier, it is still less than 3.5 now, but the user experience is better than before. 

        Because of this monitoring, we are empowered to publish certain dashboards for the business folks as well. We have three to five senior business folks who are looking at their investments and operations optimization. They are basically putting money on the table for this.

        What is most valuable?

        Its integration definitely stands out. It provides seamless monitoring of all our systems, services, apps, and whatever else we secure and monitor. 

        Visualizations have become simpler with dashboards. We are getting visibility into systems, services, and apps stack through a single pane of glass, which is good. We are able to put logs in context.

        What needs improvement?

        It can have an artificial intelligence component. Even though I can seamlessly look at end-to-end security, it would be better to have alerts and notifications powered by an AI engine. I am not sure if they have an AI component. We have not reached out to them or looked at it, but this is something that I keep on talking about within our company in terms of features. Such a feature would be good to have, and it would further optimize my Security Ops team's abilities.

        For how long have I used the solution?

        I have been using this solution for almost six months now.

        What do I think about the stability of the solution?

        It is stable. There is nothing critical about it. I've not heard of any significant issues in terms of operating this solution in the last six months.

        What do I think about the scalability of the solution?

        We have only been using it for six months, and we haven't scaled it. Six months are nothing for such a solution.

        We do monitoring as a service, and we have a hundred team members in the team. There are between 30 to 50 users who actively use it in some way.

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

        We had Carbon Black. We didn't switch from Carbon Black to Datadog. Datadog was something different because of the visualization capability and bringing everything together. We acquired a couple of companies, and Datadog was being purchased. We just validated the purchase specification, features, and assessments. It was not a one-on-one sort of exchange of Carbon Black with Datadog.

        How was the initial setup?

        It was easier than what we had been using in the past. It is a SaaS-based solution, and it was supposed to be a straightforward setup.

        What was our ROI?

        It is too early for that. I have not yet seen the impact on my budgetary lines or process optimization. I had ten people in my Security Ops team earlier, and I still have ten people. They are definitely happier as users than before, but what does that give to the organization is not yet clear to me. 

        What other advice do I have?

        I would rate Datadog a seven out of ten. It is too early to say whether we are getting our money's worth, but we have felt the difference in terms of optimization and user experience.

        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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        AB
        Director of Cloud Operations at a tech services company with 11-50 employees
        Reseller
        Top 20
        Provides good visibility and helps in being proactive, but needs a more modernized pricing mechanism

        Pros and Cons

        • "The visibility that it provides is valuable. It is helping in being proactive around incident management. It is helping us to be able to get more visibility into our customers' applications so that we can assist them at the application layer. We also provide them the infrastructure from an AWS standpoint. We are able to make sure that our customers are aware of certain critical things around the analytical piece of either the network or the application. We're able to call customers before they even know about the issue. From there, we can start putting together some change management processes and help them a bit."
        • "It can have a more modernized pricing mechanism. We're actually working with them to figure out how to become more modular and have a better and more modernized pricing mechanism. The issue with Datadog is that you have to buy the whole suite of different products, and you kind of get stuck in the old utilization of 40% of their suite. Most organizations today break down between application development, networking, and security. Therefore, there should be a way to break down different modules into just app dev, infosec, networking, etc. Customers have various needs across their business lines, and sometimes, they're just not willing to have tools that they're not using 100%. AppDynamics is probably a little bit better in terms of being modular."

        What is our primary use case?

        Our clients use it for monitoring applications. Its deployment depends on our customer's use case. 

        It is 100% cloud. We have got a multi-tenant environment, so we segment it out.

        How has it helped my organization?

        It helps us to be more proactive. We can help customers with their e-commerce applications for any networking issues. We can also help them in any area from a development standpoint. It could be a non-prod environment where they're going through testing and various functionalities. It helps them be able to be more successful with their deployments.

        What is most valuable?

        The visibility that it provides is valuable. It is helping in being proactive around incident management. It is helping us to be able to get more visibility into our customers' applications so that we can assist them at the application layer. We also provide them the infrastructure from an AWS standpoint. We are able to make sure that our customers are aware of certain critical things around the analytical piece of either the network or the application. We're able to call customers before they even know about the issue. From there, we can start putting together some change management processes and help them a bit.

        What needs improvement?

        It can have a more modernized pricing mechanism. We're actually working with them to figure out how to become more modular and have a better and more modernized pricing mechanism. The issue with Datadog is that you have to buy the whole suite of different products, and you kind of get stuck in the old utilization of 40% of their suite. Most organizations today break down between application development, networking, and security. Therefore, there should be a way to break down different modules into just app dev, infosec, networking, etc. Customers have various needs across their business lines, and sometimes, they're just not willing to have tools that they're not using 100%. AppDynamics is probably a little bit better in terms of being modular.

        For how long have I used the solution?

        I have been using this solution for almost four years.

        What do I think about the stability of the solution?

        We haven't lost any customers for Datadog. It must be stable.

        What do I think about the scalability of the solution?

        As long as you're willing to pay for 100% but utilize only 40%, it can scale and do anything you want. In an organization, its users are usually the app group, the security group, and the network group.

        How are customer service and technical support?

        We're certified in Datadog, and we have our own internal engineers to support the customers. We handle steps two and three.

        How was the initial setup?

        It is usually pretty complex. 

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

        It has a module-based pricing model.

        What other advice do I have?

        I would advise others to review the overall functionality. If you're looking for different APN tools, then Datadog is a good tool. If you're not looking for it to handle all aspects of your environment and your application from the security infrastructure aspect, there are other tools out there that you could possibly utilize for each one of those areas. 

        We do a lot of proof of concepts in helping our customers understand the micro and macro pieces of deployment. We're able to be a true advocate and value-add for our customers in utilizing the tool.

        I would rate Datadog a seven out of ten. This space is a very competitive space, and a lot of organizations are trying to figure out how to become better in the full life cycle of a deployment. There'll be a lot of changes for different companies going forward.

        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 has a business relationship with this vendor other than being a customer: Reseller
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