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Richard Chennault - PeerSpot reviewer
Senior Director with 10,001+ employees
Real User
Top 10
A good solution for infrastructure, but not for application-level monitoring
Pros and Cons
  • "Datadog's ability to group and visualize the servers and the data makes it relatively easy for the root cause analysis."
  • "Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high."

What is our primary use case?

We used Datadog to capture the salvatory of our AWS fleet of around 1,200 servers.

What is most valuable?

Datadog's ability to group and visualize the servers and the data makes it relatively easy for the root cause analysis.

What needs improvement?

Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high.

For how long have I used the solution?

I have been using Datadog for about three years.
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What do I think about the stability of the solution?

Stability really wasn't ever an issue. We didn't have any outages specific to Datadog where we couldn't get reports or insights to information. We were more concerned about the stability of our own systems and applications.

What do I think about the scalability of the solution?

There was no issue with scaling as such. It didn't scale well only from the cost perspective.

How are customer service and support?

Fortunately, because of the stability of the solution, we never had reasons to deal with technical support. Most of our interaction was with their product management, which was focused on the feature capability and ultimately pricing.

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

It didn't scale well from the cost perspective. We had a custom package deal.

Which other solutions did I evaluate?

We switched from Datadog to New Relic because it offered ET functionality. Datadog was traditionally born out of monitoring infrastructure. Over the years, they have improved their ability to give you insights at the application layer and to be considered under APM. New Relic really started at the application layer and has worked its way down.  Ultimately, we were able to accept New Relic because coming from an operations team, infrastructure was more important. As our application became more complex, our application developers needed better insight. Because there is a significant overlap in the Venn diagram between Datadog and New Relic, we felt that the needs of the infrastructure team and the applications team could be met with New Relic and its expansion in providing a sort of lightweight security.

What other advice do I have?

Datadog started off at the infrastructure level, and New Relic started off at the application level. Both of them were expanding not only into each other's space but also into the SIM space. There are a lot of options out there. For folks like me, it becomes a costly proposition because, at the end of the day, we're talking about logs, events that get pushed out. I have to push out some to Datadog and some to the security event manager. Then you start to think why can't you just push them to one place and let a product do that. That's where these products are trying to grow. They're not quite there yet because the SIM space is pretty mature. An enterprise like ours needs something fully focused and dedicated. Startups can live with New Relic that has a security capability or Datadog. I would advise you to really understand the value that you're trying to go after. Make sure that you're not trying to solve all problems that you have from the observability perspective with Datadog because that will erode the value you get out of this solution. Make sure that you are going to use Datadog for infrastructure, and it is going to be great. If you start adding other kinds of stuff to it, you'll probably start losing some of that value. Especially, if you want to go for application-level monitoring, you may be a bit disappointed. I would rate this solution a six out of ten. I'm a very price-conscious kind of purchaser.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Jaswinder Kumar - PeerSpot reviewer
Senior Manager - Cloud & DevOps at Publicis Sapient
Real User
Overall useful features, beneficial artificial intelligence, and effective auto scaling
Pros and Cons
  • "Most of the features in the way Datadog does monitoring are commendable and that is the reason we choose it. We did some comparisons before picking Datadog. Datadog was recommended based on the features provided."
  • "All solutions have some area to improve, and in Datadog they can improve their overall technology moving forward."

What is our primary use case?

My customers were using Datadog for monitoring purposes. They were using it only because the solution is running on AWS and it's a microservices-based solution. They were using an application called Dynatrace for their log.

What is most valuable?

Most of the features in the way Datadog does monitoring are commendable and that is the reason we choose it. We did some comparisons before picking Datadog. Datadog was recommended based on the features provided.

Most of the monitoring tools nowadays are have or are going to have embedded artificial intelligence and machine learning to make monitoring and logging more proactive and intelligent. Datadog has incorporated some artificial intelligence.

The solution does not require a lot of maintenance.

The solution had all the features we were looking for and we were able to create a central dashboard as per our requirements.

What needs improvement?

All solutions have some area to improve, and in Datadog they can improve their overall technology moving forward.

For how long have I used the solution?

I have been using Datadog for approximately four months.

What do I think about the stability of the solution?

Datadog is a stable solution.

What do I think about the scalability of the solution?

Datadog is a highly scalable solution because it is a SaaS solution. Having this solution be a SaaS is one of its most appealing attributes. When the vendor is going to manage data scaling and everything for you, you are only going to use the solution as per your requirements. Autoscaling is a great feature that they have.

How are customer service and support?

The support from Datadog is exellent. If you're stuck on something or you are facing any issue, support from the vendor itself is available. You will receive a response instantly from the vendor on anything related to the requirement,  issues, or feature you are looking for. The responses have always been in a timely manner.

I rate the technical support from Datadog a five out of five.

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

I have used other similar solutions to Datadog and when I do a comparison between the other tools Datadog is on top, it is great.

How was the initial setup?

Since Datadog is a SaaS solution we had not deployed the Datadog on-premise or in any Cloud. We were using the SaaS solution from the vendor itself. From the provisioning perspective or from the monitoring and dashboard perspective, we were using Terraform to create the typical monitoring as code. Everything was basically automated, we were not doing anything manually.

What other advice do I have?

If someone wants to set up Datadog on-premise or in any of the Cloud machines, they have to consider a lot of things from the auto-scaling perspective.

My recommendation is Datadog is very good. Your team can mainly focus on the development rather than the solution itself. The vendor is going to take care of auto-scaling and maintenance and everything for you.

I rate Datadog a nine out of ten.

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: My company has a business relationship with this vendor other than being a customer: partner
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reviewer1486134 - PeerSpot reviewer
Infrastructure Engineer at DataCamp
Real User
Easy to set up, supported with good documentation, and the single pane of glass improves efficiency
Pros and Cons
  • "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."
  • "The incident management beta looks promising, but it is still missing the ability to automatically create incidents based on certain alerts."

What is our primary use case?

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.

How has it helped my organization?

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.

What is most valuable?

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.

What needs improvement?

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.

For how long have I used the solution?

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

How are customer service and technical support?

There is extensive documentation and the support is very reactive.

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

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

How was the initial setup?

The initial setup is very easy. 

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.
Senior Cloud Security Engineer at a financial services firm with 201-500 employees
Real User
Top 20
Straightforward to integrate and automate; excellent technical support
Pros and Cons
  • "Straightforward to integrate and automate."
  • "Could be a little more user friendly."

What is our primary use case?

I'm a senior cloud security engineer and we are customers of Datadog. 

What is most valuable?

In terms of the public cloud provider integration of AWS, I would say it's very easy and straightforward to integrate. We can automate that way as well, because it also provides the cloud formation template and is a way to have a central place to monitor and visualize metrics in a multi-account structure. It's something we really need because the company has many AWS accounts. Rather than jumping from one account to another, Datadog gives us the functionality of having everything on one platform, in one place.

What needs improvement?

I believe there is room for improvement with this solution. It wasn't easy for me to get a quick understanding of what this tool offers us as opposed to the added tools of AWS. By that, I mean in regards to finding a better way to apply some filters or to create some alarms. I don't get more advanced features in comparison to AWS but at least I get a centralized way of doing things, which can be done on the AWS side as well. It's more complicated because you have to configure some other services to stream their logs from multi accounts to one account. It could be more user friendly and include advanced examples in the documentation showing some use cases or customer case studies, so you can get a clear idea that this functionality provides something extra. 

For how long have I used the solution?

I've been using this solution for about a month. 

What do I think about the stability of the solution?

This is a stable solution. 

What do I think about the scalability of the solution?

It's an SaaS solution, so it should be scalable although I don't know the architecture of it.

How are customer service and technical support?

We have support from a technical engineer during the POC, which is still ongoing. It's amazing. Their customization and support during the POC include weekly meetings, with a follow up of any issues through email and Slack. 

How was the initial setup?

The initial setup in regards to integration with AWS was very simple.

What other advice do I have?

I would recommend this solution even though I don't have much experience with it yet. The company is currently using New Relic and we are now investigating Datadog for two reasons; the cost and also the integration with microservices and Kubernetes. I feel like this is a good solution. 

There is some room for improvement, so I would rate this solution an eight out of 10. 

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.
Abdulla Pathan - PeerSpot reviewer
Technology Competency and Solution Head at LearningMate
Real User
Top 5Leaderboard
Good infrastructure and traffic visualizations help with capacity planning
Pros and Cons
    • "The error traceability is an area that can be improved."

    What is our primary use case?

    We use Datadog for application monitoring, to help identify errors. It is also used to monitor application performance.

    It helps organizations to understand User Experience with user behaviour pattern

    How has it helped my organization?

    Helped to reduce production issues in a defined timeframe

    Helped to refine UX

    What is most valuable?

    Datadog has a very good visualization for my complete infrastructure and network traffic, which enabled me to create a capacity plan.

    This product is great because it shows you the SQL and your application request in a single view.

    What needs improvement?

    The error traceability is an area that can be improved. This is something that helps us to pinpoint the area where a problem is occurring. It is a function stack, and it should be showing us how each function is defined.

    For how long have I used the solution?

    We have been using Datadog for the past couple of Years.

    What do I think about the stability of the solution?

    I have not worked on it long enough to properly comment on stability, yet, because it has to be tested across my other platforms.

    What do I think about the scalability of the solution?

    We have not done a full evaluation yet, but given that it is cloud-based, DataDog has to be scalable.

    How are customer service and support?

    I have not needed to contact technical support.

    How would you rate customer service and support?

    Positive

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

    We were using New Relic prior to implementing Datadog. In terms of application monitoring, Datadog is not up to the level that New Relic is. It is a better product but the price is too high, which is why we switched.

    How was the initial setup?

    Yes. It is not complex. It allows you to get a certification of DataDog prior deployment of associates to administration and configuration

    What about the implementation team?

    Inhouse. We got our Admin team certified.

    What was our ROI?

    Time to resolution production issue

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

    The price is better than some competing products.

    Which other solutions did I evaluate?

    NewRelic

    What other advice do I have?

    This is a good product and I can recommend it to others, although New Relic is still my first choice. Datadog is my second choice.

    Overall, it is a good product and my main complaint is that it needs better error traceability.

    I would rate this solution a nine out of ten.

    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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    Pablo Albornoz - PeerSpot reviewer
    Co-Founder at Exeo IT
    Real User
    Easy to use with good stability and very good monitoring capabilities
    Pros and Cons
    • "We find they have a very helpful alert system."
    • "It would be ideal if the product offered a bit more monitoring from our dashboard."

    What is our primary use case?

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

    What is most valuable?

    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.

    What needs improvement?

    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

    What do I think about the stability of the solution?

    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.

    How are customer service and technical support?

    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. 

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

    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

    How was the initial setup?

    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.

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

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

    What other advice do I have?

    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.

    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.
    AWS Cloud Architect Consultant at a transportation company with 10,001+ employees
    Real User
    Top 10
    Gives us integrated monitoring insights across multiple cloud providers
    Pros and Cons
    • "They have a very good foundation in capturing metrics, logs, and traces. It's a very nice tool for that and it allows you to apply these monitoring tools in almost any technology."
    • "I'm not sure what kind of features are in the roadmap right now, but I encourage the development of features for defining your organization, and allowing the visibility of what kind of metrics you can get. Those features would be really useful for us."

    What is our primary use case?

    We are evaluating Datadog for observability and monitoring requirements that we have in our company. In our use case, our intention is to provide some kind of framework for multiple app teams to use the tool for our cyber ability and engineering practices.

    What is most valuable?

    They have a very good foundation in capturing metrics, logs, and traces. It's a very nice tool for that and it allows you to apply these monitoring tools in almost any technology.

    Even if you have several layers, containers, EC2 instances, build machines or whatever you need in your infrastructure, Datadog can integrate with all of them across multiple cloud providers. It's a great product.

    What needs improvement?

    One of the improvement opportunities that we have identified in my project concerns how hard it is to manage an organizational structure when you have multiple things in one organization, and you want to provide some kind of isolation between them. At the same time, from the management perspective, you want to see an overall overview of what is happening in your business unit, or as a whole division. This is the kind of limitation we're facing.

    I'm not sure what kind of features are in the roadmap right now, but I encourage the development of features for defining your organization, and allowing the visibility of what kind of metrics you can get. Those features would be really useful for us. 

    For how long have I used the solution?

    I have been using Datadog for about six months.

    What do I think about the scalability of the solution?

    It's a very scalable product. Right now we are using the SaaS version, so we don't need to worry about the infrastructure or whatever is needed for the platform it is running on. All the capturing of data is sent to the SaaS product and that can be as scaled as needed.

    How are customer service and support?

    So far their support is pretty nice. They have established many meetings and training sessions, and they are supporting our requirements very well. I don't have any complaints with Datadog support.

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

    While it is an expensive product, I would rate the pricing level at four out of five. 

    What other advice do I have?

    Normally, the primary reason why people use these kind of tools is observability, but right from the beginning you have to understand what observability is, what it means for your company, and how the tool is going to help you to capture the proper metrics for making your applications observable.

    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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    Project Director at a tech services company with 501-1,000 employees
    Real User
    Valuable logs, pretty stable, and provides a single tool for architecture and infrastructure
    Pros and Cons
    • "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 the usage. For example, if there is 20% more increase from one week to another, the customer should get an alert."

    What is our primary use case?

    We use it for our infrastructure network and servers.

    How has it helped my organization?

    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.

    What is most valuable?

    Its logs are most valuable.

    What needs improvement?

    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.

    For how long have I used the solution?

    I have been using this solution for two years.

    What do I think about the stability of the solution?

    It is pretty stable.

    What do I think about the scalability of the solution?

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

    How are customer service and technical support?

    Their technical support is fine.

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

    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.

    How was the initial setup?

    Its initial setup is complex.

    What about the implementation team?

    We installed it ourselves.

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

    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.

    Which other solutions did I evaluate?

    We evaluated various in-house and external options.

    What other advice do I have?

    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.

    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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