Datadog Reviews

The application performance monitoring is pretty good. 

The Log Explorer could be better. I don't think it has log manipulation as Splunk does.

I've only been using Datadog for the past one or two months. 

Datadog is stable. 

The initial setup is pretty easy. It's a kind of agent-based application monitoring. It's similar to Splunk and Elastic Stack.

Although I don't have that much experience with it, overall, on a scale from one to ten, I would give Datadog a rating of eight. 

We use it for our infrastructure network and servers.

From our customer's and our perspective, it has not brought much change in terms of the process. Datadog did not change anything about the process. It only provided a single tool instead of having to use multiple tools.

Its logs are most valuable.

Its pricing model can be improved. Its settings should be improved for a better understanding of billing. They should also provide some alerts when there is an increase in usage. For example, if there is a 20% more increase from one week to another, the customer should get an alert.

I have been using this solution for two years.

It is pretty stable.

The perimeter in which we worked was not big enough to get any information about scalability.

Their technical support is fine.

One of our customers was using another solution. They switched because of the scalability of the perimeter. Their previous solutions were limited in terms of the kind of servers and virtual machines. They had multiple tools, and Datadog provided them a single tool for architecture and infrastructure.

Its initial setup is complex.

We installed it ourselves.

I am not satisfied with its licensing. Its payment is based on the exported data, and there was an explosion of the data for three or four weeks. My customer was not alerted, and there was no way for them to see that there has been an explosion of data. They got a big invoice for one or two months. The pricing model of Datadog is based on the data. The customer was quite surprised about not being alerted about this explosion of data. They should provide some kind of alert when there is an increase in usage.

We evaluated various in-house and external options.

I would advise others to take a step-by-step approach rather than a from-zero-to-everything approach.

I would rate Datadog an eight out of ten.

I implement this solution for clients.

I have found some of the most valuable features to be the way things all come together that gives us a point of view that is useful. The panel is very beautiful and customizable. The configuration file was really helpful, we were able to configure the solution in the way we needed. The portability of this solution is more flexible than other competitors, allowing us to change cloud services when we want. We are not locked into a particular one.

The solution is scalable.

We have used CloudWatch previously and this solution is better at meeting all our needs.

The installation is easy for me. However, if you are new to this solution it might not be so easy.

I am an implementor, I did the implantation of the solution.

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 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.

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.

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.

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

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.

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.

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.

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.

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. 

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.

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 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 use Datadog as a monitoring platform to achieve visibility into our container environments.

Almost all of our workloads are containerized and with DataDog, we are able to get metrics, logs, alerts, and events about all the containers that we are running. Our developers also extensively use APM to find and diagnose performance issues that might appear.

We use Terraform to automatically create all of the necessary monitors and dashboards that our developers need to make sure that our level of service is sufficient.

We implemented Datadog around the same time as the company was growing from 30 to 150 people. Before that, we didn't have a standard stack for monitoring. Each team used their own logging solutions, metrics were missing or non-existent, and it was impossible to correlates metrics collected by different teams. DataDog provided us with an out-of-the-box solution that allowed us to focus on putting in place practices and processes around monitoring, rather than focus on implementation details.

Every squad is now confident in their ability to quickly identify and diagnose issues when they arise.

The fact that everything is under a single pane of glass is really valuable, as developers don't have to spend their time copying correlation IDs across tools to find what they need.

Thanks to the unified tagging system, it's really easy to jump around the different Datadog products without losing the context. That makes debugging really easy for developers because they can go from APM to logs to metrics in a few clicks.

Watchdog is also a great feature that helped us identify overlooked issues more than once.

The incident management beta looks promising, but it is still missing the ability to automatically create incidents based on certain alerts.

SLOs are also a great way to visualize how you are doing with regard to the level of service that you are providing but it missing crucial components like:

• The ability to visualize the remaining error budget and how it evolved during the month. An error budget burndown graph would be helpful.
• The ability to display a different level of alert on an SLO based on how fast it is consuming the error budget. This is the slow burn versus fast burn.

We've been using Datadog for a bit more than two years.

There is extensive documentation and the support is very reactive.

Prior to using Datadog, each team was using their own solutions. This included a mix of custom tooling, third-party tools, and AWS tools.

The initial setup is very easy.