Datadog Reviews

We have used this solution primarily for application performance monitoring. To do this, we needed to make sure we had the right data in the system so that people could be able to monitor their applications end-to-end.

The infrastructure monitoring capabilities are really valuable. You can just log on and see everything that is happening within an IT environment.

Their security features could be improved. We looked at their Security Monitoring feature but it was early in its development. Datadog are just getting into the security space so I'm sure this will improve in the future.

This is a stable solution. 

This is a scalable solution. 

To get started with this solution, I would recommend front-loading it with some sort of data or process and filter out to view only the information you need.

I would rate this solution a nine out of ten. 

We use Datadog to monitor our product on the cloud.

The performance of Datadog is good.

Datadog has a lot of features kind of cramped into one dashboard. It's quite hard to get around what feature does exactly what. There was a steep learning curve, trying to navigate through menus.

The menu navigation could improve. If there was a more straightforward way of adding new functions or features to where each menu is placed that would be an improvement.

I have been using Datadog for approximately six months.

The solution is stable.

The scalability of Datadog is pretty good. However, we haven't arrived at the level that we need to test out the scalability.

We have five people using the solution.

I have not used the support from Datadog.

We have not used other solutions previously.

The initial setup is straightforward, and the process took approximately three days.

We have approximately six people that implement and support the solution.

Sometimes it's very hard to project how much it will cost for the monthly subscription for the next month when you add certain features.  Having better visibility of the cost would give a better experience.

There are not any additional costs for the use of this solution.

I would recommend this solution to others.

My advice to others is to use a few features of the solution before going full scale.

I rate Datadog an eight out of ten.

I am using Datadog for error reporting.

I have found error reporting and log centralization the most valuable features. Overall, Datadog provides a full package solution.

I have been using this solution for approximately three years.

The solution is stable.

I used to process a million requests easily with Datadog, I never had any scalability issue.

I have not needed to contact support.

The initial setup is easy.

Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs.

I rate Datadog a nine out of ten.

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.

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.

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.

I have been using this solution for almost four years.

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

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.

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

It is usually pretty complex. 

It has a module-based pricing model.

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.

We're in the process of doing a Proof of Concept with the solution right now.

One of the solution's greatest aspects is its overall simplicity. It is very easy to use. It's easier to handle than other brands we have access to.

The monitoring capabilities that the solution provides are very good.

We find they have a very helpful alert system.

The product has been very stable. We've liked the performance provided.

The initial setup is simple and easy to handle. It's not hard at all.

The experience we've had with technical support has been very positive so far. They are helpful.

The integration capabilities have been pretty good overall. We have no complaints.

We haven't used the solution too much yet to assess what features it is missing or would improve. The support in Latin American is a point that would mark as a point to improve

The stability of the solution is excellent. There are no bugs or glitches. It doesn't crash or freeze. It's very reliable in terms of performance.

Technical support has been helpful overall. They are knowledgeable and responsive. We are quite satisfied with the level of service they provide to our company. 

We are actually still using actually Elasticsearch and Kibana, however, we prefer to use Datadog due to the fact that it is very simple. We really enjoy how it operates

We found the initial setup to not be overly complex. It's rather straightforward and easy to execute. A company shouldn't have any issues with the process.

I'm not sure if the license is expensive or cheap. It's managed by the customer and we've recently come on board.

I am an end-user and customer. I don't have any business relationship with the product itself. We work with clients on the infrastructure and IT developer infrastructure mostly. We work with a variety of solutions, including Dynatrace, Datadog, Elasticsearch, etcetera.

In general, due to its simplicity and ease of use, I would rate the solution at a nine out of ten. We've been very satisfied with the solution overall.

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.

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.

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.

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.

We have been using Datadog for two years.

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. 

Datadog is very scalable but just watch the cost.

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.

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. 

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.

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

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.

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.

We evaluated Dynatrace and AppD before choosing this product.

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.

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.

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

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.

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.

We have been using Datadog for more than six months.

Stability-wise, it has been good.

The scalability is good so far. 

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.

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

Setup is hassle-free and pretty straightforward. 

I deployed it myself.

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

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.

Prior to implementing Datadog, we evaluated Splunk.

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.

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.

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.

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, RDS, Kubernetes 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.

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.

We have been using Datadog for one year.

We have not run into any issues with stability.

The scalability of Datadog is very good.

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.

we did not.

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.

We deployed it ourselves.

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

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.

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.

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.