reviewer1493811 - PeerSpot reviewer
Sr. Architect - SaaS Ops at CommVault
Real User
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.

Buyer's Guide
Datadog
November 2022
Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: November 2022.
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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 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.
PeerSpot user
Architect at SEI Investments
Real User
Great support with a helpful APM and profiler
Pros and Cons
  • "The most valuable aspects of the product include the APM and profiler."
  • "I find the training great. That said, it is set for the LCD (lowest common denominator). Of course, this is very helpful to sell the product, yet, to really utilize the product, you need to get more detailed."

What is our primary use case?

We primarily use Datadog for:

  • Native memory
  • Logging
  • APM
  • Context switching
  • RUM
  • Synthetic
  • Databases
  • Java
  • JVM settings
  • File i/o
  • Socket i/o
  • Linux
  • Kubernetes
  • Kafka
  • Pods
  • Sizing

We are testing Datadog as a way to reduce our operational time to fix things (mean time to repair). This is step one. We hope to use Datadog as a way to be proactive instead of reactive (mean time to failure).

So far, Datadog has shown very good options to work on all of our operational and development issues. We are also trying to use Datadog to shift left, and fix things before they break (MTTF increase).

How has it helped my organization?

We are currently in a POC and do not own Datadog at the moment. 

So far, there have been a few issues due to security. There are two main security issues. 

The first is moving data off-prem. This has been resolved to a point (filtering logs, etc). However, there is still an issue with moving a JFR as a JFR potentially contains data that is not allowed off-prem.

The second security issue is more internal, however, the main installation requires root access or using an ACL. Our company does not use ACLs on our Linux platform. This is problematic since the install sets a no-login on the Datadog user.

What is most valuable?

The most valuable aspects of the product include the APM and profiler.

These two have given us insights into things that are very difficult to track down given the standard OS (Linux) tools. 

The native memory tracking is super difficult to see exactly where it comes from. I attended a course (continuous profiling), and it showed me the potentially very important capabilities.

If you add these details to a standard dashboard, or a sub-dashboard for techy people, or even just a notebook, it would be easy to identify issues before they occur.

Combining these details with the basic tools (infra, logging, APM, and good rules), Datadog can easily show the details that a true engineer would need. It isn't just for monitoring, however, I see the value in it for engineers.

What needs improvement?

I have done every training offered (and in a short period of time: two days for 20 courses).

I find the training great. That said, it is set for the LCD (lowest common denominator). Of course, this is very helpful to sell the product, yet, to really utilize the product, you need to get more detailed.

If I did the training as it is written and I cut/paste a bunch of stuff and see the cut/paste work, I didn't really learn anything. Later sessions (I quit using the editor and switched to VI) stopped cutting and pasting, and learned much more.

For how long have I used the solution?

I've used the solution for one month.

What do I think about the stability of the solution?

I' give stability a thumbs up.

What do I think about the scalability of the solution?

We are not sure yet in terms of scalability. The off-prem solution seems to scale well (although had issues with the training slowing down).

How are customer service and support?

Technical support is great.

How would you rate customer service and support?

Positive

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

I previously used Dynatrace and Elastic. We didn't switch. We are in a POC.

How was the initial setup?

The initial setup is simple yet complex. There are too many teams are needed.

What about the implementation team?

We did the initial setup in-house.

What was our ROI?

In terms of ROI, the labor saving is probably the biggest. The NPR is probably second - although management would probably reverse these.

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

Pricing and licensing is fairly complicated. A GB for .1 sounds great, however, once you put all 16 or so prices together, it adds up fast. A cost model sheet on the main site would be very helpful.

Which other solutions did I evaluate?

We are currently in a POC.

What other advice do I have?

We work with all product versions.

Which deployment model are you using for this solution?

On-premises

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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Buyer's Guide
Datadog
November 2022
Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: November 2022.
653,522 professionals have used our research since 2012.
Felix Flores - PeerSpot reviewer
Staff Engineer at a tech services company with 1,001-5,000 employees
Real User
Great distributed tracing and flame graphs for debugging with a relatively painless setup
Pros and Cons
  • "We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."
  • "Once Datadog has gained wide adoption, it can often be overwhelming to both know and understand where to go to find answers to questions."

What is our primary use case?

We are using a mixture of on-prem and cloud solutions to bridge the gap with healthcare entities in the service of providing patients with the medication they need to live healthy lives.

Since we're a heavily regulated company, a lot of our solutions grew from on-premises monoliths. However, as we scaled out, it became harder and harder to move forward with that architecture. Today, we're investing heavily in transforming our systems from monoliths into distributed systems.

With this change in mind, the ability for us to connect the dots using Datadog has been invaluable.

How has it helped my organization?

We have an API that serves as a critical aspect of our system for generating new requests for us to process in service of a patient. This service has many tentacles, and it was always hard to track down how issues from this API are affecting things downstream. Since we've added more instrumentation in this API, Datadog has changed our status from a reactive posture to a proactive one.

It has also served as a prime example to other applications on what the benefit of a well-instrumented system is for that application and other applications around it. Due to this, more and more people are using Datadog.

What is most valuable?

We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions. It has also informed our developers on how our various systems are interconnected and the downstream effects of the problems we might encounter for certain services.

We're still working on getting widespread adoption of these products. Still, we're already seeing a shift in the developer's perspective from application-specific and starting to look at things from a more holistic systems perspective.

While this is not part of the question, this is relevant: Now that I've learned more about RUM, this will be something that we will heavily leverage moving forward to give us a whole complete view of our system from the front and back end perspective.

What needs improvement?

Once Datadog has gained wide adoption, it can often be overwhelming to both know and understand where to go to find answers to questions. Currently, we use a combination of documentation and COPs to ensure that folks know how to leverage what we have in Datadog properly.

While the guides for Datadog go a long way, a way to customize the user experience from "advanced" to "novice" mode would go a long way.

For how long have I used the solution?

I've been using the solution for two years.

What do I think about the stability of the solution?

It has never failed us and therefore I consider it to be very stable.

What do I think about the scalability of the solution?

It's magic. For the most part, we just installed the product and a lot of it just worked out of the box.

How are customer service and support?

Technical support is excellent.

How would you rate customer service and support?

Positive

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

We have used Splunk, Sentry, and a suite of hand-made solutions. We switched since the Datadog solution was both comprehensive and cohesive. It was also easier to onboard people since the solution was well-documented and standardized.

How was the initial setup?

For the most part, it was really painless to set up.

What about the implementation team?

We implemented the solution in-house.

What was our ROI?

We're still early on in our transformation process. That said, we are gaining a lot of steam in terms of adoption. Both the engineering team and the product team are seeing tremendous value from this solution.

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


Which other solutions did I evaluate?


What other advice do I have?

Adding more tooltips and links to documentation or how-tos within the application would really go a long way for those trying to get their feet wet with Datadog.

Which deployment model are you using for this solution?

Hybrid Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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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.
PeerSpot user
DevOps Engineer at a printing company with 51-200 employees
Real User
Great visibility, good logs, and a helpful dashboard
Pros and Cons
  • "For us to have visibility into our app stack and the hardware we run has been highly beneficial."
  • "I want to applaud the efforts in making the UI extremely usable and approachable. My suggestion would be to take another look at how the menu structure is put together, however. Even after using the platform mostly every day for months, I still find myself trying to find a service or feature in the menus."

What is our primary use case?

Log aggregation for us was a key component since we have a fairly old-school app running on VMs on bare metal. We previously didn't have much insight into our logs unless we manually tunneled them into each server.

The solution is reducing manual labor in troubleshooting problems in our environments server by server.

We also needed to monitor our Java app and MySQL database to understand their problems so that we could take action and resolve them.

Our use cases have since expanded to encompass all aspects of monitoring.

How has it helped my organization?

Before Datadog, all we had to go on was the gut reaction of the old guard on our team. While useful, the reactions and inherent knowledge only benefited a few folks.

Datadog has allowed us to create comprehensive dashboards and proactively send out alerts. We used the knowledge of people very versed with our products to help set up the platform and have since benefited from that.

The operative word here is visibility, and we've seen a huge improvement in that.

What is most valuable?

Seeing log trends and patterns and aggregate search was a huge first step for us. We then began using other features of the Datadog platform by enabling APM. After that, we did other integrations.

For us to have visibility into our app stack and the hardware we run has been highly beneficial.

We leverage APM, log management, and at least ten other integrations. Our DB, web servers, network, storage, and other areas are now monitored and hooked up to dashboards.

Dashboarding has also proven useful when information is going to be viewed by anyone in the organization.

What needs improvement?

Our experience has been overwhelmingly positive so far. That said, there is one area that could benefit from some polish. For example, I want to applaud the efforts in making the UI extremely usable and approachable. My suggestion would be to take another look at how the menu structure is put together, however. Even after using the platform mostly every day for months, I still find myself trying to find a service or feature in the menus.

For how long have I used the solution?

I've used the solution for around six or eight months. We've had the Datadog agents deployed on our various environments.

What do I think about the stability of the solution?

So far, we have not had any issues with stability. It should be very stable and easy to update.

What do I think about the scalability of the solution?

The solution is currently deployed on a limited scale. That said, we see the potential and benefits of deploying this in a cloud scenario.

How are customer service and support?

Customer service and the support teams have been very responsive when we need them. They are very professional.

How would you rate customer service and support?

Positive

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

This was our first solution in this space.

How was the initial setup?

The initial setup steps with the agent are only confusing when using the config files for the first time. The main file includes a lot that you can specify elsewhere and it's not readily apparent which one to use until you dig in more.

What about the implementation team?

We did an in-house implementation.

What was our ROI?

Our ROI with Datadog has been very high. It's given us the ability to see how we're performing, which we didn't have before.

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

Ensure you have your ingestion pipelines dialed in, or you'll likely spend more than you were expecting.

Which other solutions did I evaluate?

We evaluated free and open-source options, however, ultimately, we decided that we didn't have the manpower as a small company to maintain them.

What other advice do I have?

There is nothing that the documentation cannot help with; it's very good.

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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JulianLewis - PeerSpot reviewer
Senior Engineer at a educational organization with 5,001-10,000 employees
Real User
Top 10
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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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
PeerSpot user
Lead Software Engineer at a retailer with 51-200 employees
Real User
Great APM and interesting log management but the UI is daunting
Pros and Cons
  • "The most useful feature is the APM."
  • "As a new customer, the Datadog user interface is a bit daunting."

What is our primary use case?

We are trying to get a handle on observability. Currently, the overall health of the stack is very anecdotal. Users are reporting issues, and Kubernetes pods are going down. We need to be more scientific and be able to catch problems early and fix them faster.

Given the fact that we are a new company, our user base is relatively small, yet growing very fast. We need to predict usage growth better and identify problem implementations that could cause a bottleneck. Our relatively small size has allowed us to be somewhat complacent with performance monitoring. However, we need to have that visibility.

How has it helped my organization?

We are still taking baby steps with Datadog. Hence, it's hard to come up with quantifiable information. The most immediate benefit is aggregating performance metrics together with log information. Having a better understanding of observability will help my team focus on the business problems they are trying solve and write code that is conducive to being monitored, instead of reinventing the wheel and relying on their own logic to produce metrics that are out of context

What is most valuable?

The most useful feature is the APM. Being able to quickly view which requests are time-consuming, and which calls have failed is invaluable. Being able to click on a UI and be pointed to the exact source of the problem is like magic. 

I'm also very intrigued by log management, although I haven't had quite a chance to use it very effectively. In particular, the trace and span IDs don't quite seem to work for me. However, I'm very keen on getting this to work. This will also help my developers to be more diligent and considerate when creating log data.

What needs improvement?

As a new customer, the Datadog user interface is a bit daunting. It gets easier once one has had a chance to get acquainted with it, yet at first, it is somewhat overwhelming. Maybe having a "lite" interface with basic features would make it easier to climb the learning curve.

Maybe the feature already exists. However, I'm not sure how to keep dashboard designs and synthetic tests in source control. For example, we may replace a UI feature, and rebuild a test accordingly in a pre-production environment, yet once the code is promoted to production, the updated test would also need to be promoted.

For how long have I used the solution?

We have just started using the solution and have only used it for about two months.

What do I think about the stability of the solution?

We're new at this. That said, so far, there haven't been any issues to report.

What do I think about the scalability of the solution?

I have not had the opportunity to evaluate the scalability.

How are customer service and support?

Customer support is full of great folks! We're beginning our Datadog journey, so I haven't had that much experience. The little I have had has been great.

How would you rate customer service and support?

Positive

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

This is all new. 

We used to work with New Relic. New Relic has an amazing APM solution. However, it also became cost-prohibitive

How was the initial setup?

Since we are relatively greenfield, it was relatively painless to set up the product. 

What about the implementation team?

Our in-house DevOps team did the implementation.

What was our ROI?

I don't know what the ROI is at this stage.

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

I'm not sure what the exact pricing is. 

What other advice do I have?

So far, it's been great!

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.
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Buyer's Guide
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Updated: November 2022
Buyer's Guide
Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.