Try our new research platform with insights from 80,000+ expert users
reviewer2004192 - PeerSpot reviewer
Lead Support Engineer at a tech vendor with 11-50 employees
Real User
Good centralization of data with good integration but can be overwhelming at first
Pros and Cons
  • "The integration into AWS is key as well as our software is currently bound to AWS."
  • "The ability to find what you are looking for when starting out could be improved."

What is our primary use case?

Our use case is mainly deploying into our applications for monitoring/logging observability. We currently have our microservices feed into an actuator that exists in each instance of our application that extends to a local and central Grafana for client and internal visibility. The application we use is Grafana.

Logging captures application and system logs that are ported to each application instance for querying.

Whenever anything occurs that is considered unhealthy from a range of health checks, we have notification rules configured internally and externally for a prompt response time.

How has it helped my organization?

We have been able to be a more confident, knowledgeable, and capable team when everything is being ported into a centralized format. Beforehand, knowledge was isolated to individuals. Knowledge in terms of what information represented and where it was led to a lack of confidence. By having everything in one place, rules out that confusion and allows us to respond better to issues.

It also allows for personal growth as our team is learning the application from the ground up, and each person is enhancing their own skills.

What is most valuable?

The valuable features include the following: 

  • We are currently utilizing a decentralized distributed framework for our deployment, including our monitoring/logging observability capabilities. Centralizing them, if contingent on our company privacy guidelines, will be a big help in tracking and responding to issues that come up and have the means to understand the origin of the log management tools that were demonstrated.
  • The ability to fiddle around and manipulate how logs are outputted.
  • The ability to track AWS Lambda functions, Cloudformation, and Cloudwatch allow someone that is not savvy to dip their toe into understanding their own product.
  • The integration into AWS is key as well as our software is currently bound to AWS.

What needs improvement?

The ability to find what you are looking for when starting out could be improved. It was a bit overwhelming trying to figure out what is the best solution. It led to many prototypes or time spent just perusing documentation. If we were able to select bundles or template use cases, we would hit the ground running quicker.

Buyer's Guide
Datadog
January 2025
Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: January 2025.
825,609 professionals have used our research since 2012.

For how long have I used the solution?

I've used the solution for one year.

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: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
reviewer2003286 - PeerSpot reviewer
Software engineer at a marketing services firm with 501-1,000 employees
Real User
Helps catch bugs, easy for non-technical users, and useful for tracking issues
Pros and Cons
  • "This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."
  • "Datadog could make their use cases more visible either through their docs or tutorial videos."

What is our primary use case?

We use metrics to track the metrics of our application. We use logging to log any errors or erroneous application behavior as well as successful behavior. We use events to log successful steps in our pipeline or failed steps in our deployment. We use a combination of all these features to diagnose bugs. 

It makes it much more efficient to look at all the data in one place. This speeds up our development speed so that we can be agile.

How has it helped my organization?

This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime. 

It also allows us to accurately record and project current and future revenue by measuring the application's metrics. This way, my team can accurately and rapidly create reports for upper management that are easy to read and understand. 

Datadog is also easy to read by non-technical personnel. This way, if there are any erroneous readings, everybody has a chance to find them.

What is most valuable?

We use metrics to track the metrics of our application. We use logging to log any errors or erroneous application behavior as well as successful behavior. We use events to log successful steps in our pipeline or failed steps in our deployment. 

We use a combination of all these features to diagnose bugs. It makes it much more efficient to look at all the data in one place. This speeds up our development speed so that we can be agile.

These features are the features that I use the most since it is incredibly difficult to track down intermittent bugs if I were to look directly under the hood in a CLI.

What needs improvement?

Datadog could make their use cases more visible either through their docs or tutorial videos. There are different implementations of certain features that we utilize to customize Datadog functionality and in that way, we sometimes get results that are not conducive to what Datadog thinks their features' use cases are.

For how long have I used the solution?

I've used the solution for at least one year.

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

We have only used Datadog. We did not previously use a different product.

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.
PeerSpot user
Buyer's Guide
Datadog
January 2025
Learn what your peers think about Datadog. Get advice and tips from experienced pros sharing their opinions. Updated: January 2025.
825,609 professionals have used our research since 2012.
reviewer2004183 - PeerSpot reviewer
Principal Software Engineer at a insurance company with 10,001+ employees
Real User
Good for testing and multistep API tests with a straightforward setup
Pros and Cons
  • "We enjoy the multistep API tests."
  • "They need to implement template variables into the message response body."

What is our primary use case?

We use the solution for testing all of our application's endpoints. It is making sure that they work on a consistent basis.

What is most valuable?

We enjoy the multistep API tests.

What needs improvement?

They need to implement template variables into the message response body. They could be injected in the subsequent calls. However, they fail to be able to use those variables anywhere in the alert body message that is sent out.

For how long have I used the solution?

We've been using the solution for a year.

What do I think about the stability of the solution?

I've never thought about stability and have no insights.

How are customer service and support?

I find we are getting tossed from engineer to engineer. It is not fun when you have an ongoing problem. That is something from the customer resolution team that needs to be addressed.

How would you rate customer service and support?

Positive

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

We previously used Selenium. I was forced to use it. However, Datadog was a way simpler solution to setting up browser and API tests quickly.

How was the initial setup?

The solution is very straightforward since it has a good GUI.

What about the implementation team?

The initial setup was handled in-house.

What was our ROI?

It is not my job to track the ROI.

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

I have no details about the pricing. 

Which other solutions did I evaluate?

We did not evaluate other solutions. 

What other advice do I have?

The solution is a SaaS.

Disclosure: My company has a business relationship with this vendor other than being a customer: partner
PeerSpot user
reviewer2003478 - PeerSpot reviewer
Data Engineer II at a comms service provider with 10,001+ employees
Real User
Ingests data from various sources, integrates well, and offers a helpful alert mechanism
Pros and Cons
  • "Datadog agents act as an integration to different services, providing easy access and management."
  • "Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted."

What is our primary use case?

Ingesting data from various sources to monitor the log metrics of the system and enabling an alert mechanism to notify the teammates if something goes wrong.

More specifically, having Datadog agents as integration to different services provides easy access and management.

How has it helped my organization?

The solution has helped out organization by allowing us to ingest data from various sources to monitor log metrics and enabling alert mechanisms to notify teams if something goes wrong.

Datadog agents act as an integration to different services, providing easy access and management.

What is most valuable?

The solution is useful for ingesting data from various sources. This helps to monitor the log metrics of the system. It has alert mechanisms that can be enabled to notify the teams if something goes wrong.

Datadog offers good integration to different services. It provides for easy access and management.

What needs improvement?

Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted. 

For how long have I used the solution?

We've used the solution for close to 1.5 years.

What other advice do I have?

We use a SaaS deployment.

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.
PeerSpot user
reviewer2003214 - PeerSpot reviewer
Sr. Director of Software Engineering at a tech consulting company with 1,001-5,000 employees
Real User
Helpful support, good incident management, and helps triage faster
Pros and Cons
  • "The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support."
  • "The pricing is a bit confusing."

What is our primary use case?

The RUM is implemented for customer support session replays to quickly route, triage, and troubleshoot support issues which can be sent to our engineering teams directly. 

Customer Support will log in directly after receiving a customer request and work on the issue. Engineers will utilize the replay along with RUM to pinpoint the issue combined with APM and Infra trace to be able to look for signals to find the direct cause of the customer impact. 

Incident management will be utilized to open a Jira ticket for engineering, and it integrates with ITSM systems and on-call as needed.

How has it helped my organization?

The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support.

The RUM is implemented for customer support. It can quickly route, triage, and troubleshoot support issues that are sent to our engineering teams. 

Customer support can log in and start troubleshooting after receiving a customer request. The replay and RUM help pinpoint the issue. This functionality is combined with APM and Infra trace to be able to look for the cause of the issue. Incident management is leveraged to open a Jira ticket for engineering, and it can integrate with ITSM systems and on-call as needed.

What is most valuable?

RUM with session replay combined with a future use case to support synthetics will help to identify issues earlier in our process. We have not rolled this out yet but plan for it as a future use case for our customer support process. This, combined with integrated automation for incident management, will drive down our MTTR and time spent working through tickets. Overall, we are hoping to use this to look at our data and perfection rate over time in a BI-like way to reduce our customer support headcount by saving on time spent.

What needs improvement?

I would like to see retention options greater than 30-days for session replay. I'd also like to see forwarding options for retention to custom solutions, and a greater ability to event and export data from the tooling overall to BI/DW solutions for reporting across the long term and to see trends as needed.

For how long have I used the solution?

I've used the solution for about nine months.

What do I think about the stability of the solution?

So far, stability has been great.

What do I think about the scalability of the solution?

I'd like to see more bells and whistles added over time. Widgets are coming soon to help with RUM.

How are customer service and support?

Support is very good. They are responsive and gave us the help we need.

How would you rate customer service and support?

Positive

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

We have utilized New Relic, however, not for RUM. We went with Datadog to potentially switch the entire platform into an all-in-one solution that makes sense for a company of our size.

How was the initial setup?

We started on the beta, and the documentation was lagging behind. We also needed direct instructions and links from the customer support/account representative that was not immediately available by searching online.

What about the implementation team?

We implemented the solution ourselves.

What was our ROI?

Ideally, this will inform our strategy to not increase our customer support headcount as significantly into 2023 and beyond.

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

The pricing is a bit confusing. However, the RUM session replay, in general, is very inexpensive compared to whole solutions.

Which other solutions did I evaluate?

We looked into LogRocket and New Relic.

What other advice do I have?

I'd advise other users to try it out.

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.
PeerSpot user
reviewer1994826 - PeerSpot reviewer
Senior Software Engineer at Grata
User
Great charts and visualizations with good debugging
Pros and Cons
  • "We really like the charts and visualization."
  • "Sometimes, it takes a long time to load the dashboard if we have many charts."

What is our primary use case?

We primarily use the dashboard/metric with many tags.

How has it helped my organization?

It makes the system easier to debug. 

What is most valuable?

We really like the charts and visualization.

What needs improvement?

Sometimes, it takes a long time to load the dashboard if we have many charts.

For how long have I used the solution?

I've used the solution for five years.

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
SeniorSofcae - PeerSpot reviewer
Senior Solutions Architect at a tech services company with 11-50 employees
MSP
It lacks consistency in the APIs. However, It has saved us a lot of trouble in implementation.
Pros and Cons
  • "It provides more cloud data. They tend to just get the way a service would be designed on the cloud."
  • "It has saved us a lot of trouble in implementation."
  • "The ease with which we can filter, use metrics, and give accounts to customers, then let the customer filter, set up metrics, and alerts. This has been a big win for us."
  • "It does not have the best interface."
  • "Stability of the product has been a concern for us outside of the primary monitoring agents."
  • "It lacks consistency in the APIs."

What is our primary use case?

We are using the infrastructure and app monitoring side, such as process monitoring. We are using it in a very traditional way. We are not using the APM capabilities. When it comes to something like containers, we will generally use it on the host but not inside the container itself. 

We are using it with our customers and in-house day-to-day.

How has it helped my organization?

It provides more cloud data. They tend to just get the way a service would be designed on the cloud. Datadog can handle a server disappearing and account for it, but they will kick somebody out. 

The ease with which we can filter, use metrics, and give accounts to customers, then let the customer filter, set up metrics, and alerts. This has been a big win for us. This can't be done with a lot of the other platforms. This has made things considerably easier. Where we used to get "What's my performance?" Here, have access. Go nuts. Tell us if you need it. Now, our customers no longer ask us for all that, as they want to go do it themselves. This has made our lives infinitely easier.

What needs improvement?

The only thing that they were missing that has throw us from the beginning (they are still missing it) is consistency in the APIs. There are a couple of guys on the automation side who complain rightfully over how hard it is because every new feature which comes out has a new way of interfacing with the API. This was our big, red flag in the beginning, but given the price and other features, it wasn't enough for us to discount. We said "That we would live with this one red flag", but it is still a red flag.

Stability of the product has been a concern for us outside of the primary monitoring agents.

It does not have the best interface.

For how long have I used the solution?

Three to five years.

What do I think about the stability of the solution?

We haven't noticed any issues in the primary use case for which we are using it. 

The reason we're not using or looking at the APM space right now is due to platform availability. Datadog doesn't support enough platforms, which they know. Every customer that we have is running PHP, and we cannot use APM with any of our customers because of that. Even if they are 95 percent running Java, if Datadog doesn't have PHP, we can't use it because it won't integrate.

What do I think about the scalability of the solution?

Scalability has not been a concern at all. We have had customers with steady state loads: low and high. Our smallest customer is a friends and family startup which has about three instances. We have steady state loads which are more than 500. Then, we have customers with two instances all summer, but do seasonal work in the winter and can scale to more than 1000 instances. 

We have never noticed a hiccup on Datadog with any of our scaling. It has always grown to meet our program.

How are customer service and technical support?

We have used technical support for certain integrations. We use a lot of Ansible and Chef, and we have had a lot of problems with both of these automating components. Technical support was helpful within their limitations.

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

We switched when we started getting heavy into the cloud. We used to use ScienceLogic, New Relic, AppDynamics, Zabbix, etc. It was hodgepodge. 

We were very strong in the APM space. We had all of our APMs going through AppDynamics, which suited a lot of our customer use cases in the cloud. However, when our customers started to get more specific, they wanted traditional core monitoring and the other on-premise traditional vendors, like ScienceLogic, weren't cutting it. That is when we started to look at Datadog. We went back and forth for a while between Zabbix and Datadog. In the end, Datadog won out based on feature price and everything together.

How was the initial setup?

The integration with the AWS environment has been pretty seamless. There have been a few services that we don't use that they don't have book support for. However, usually that happens when it is a new service which is really unpopular. Most of the time, our customers shouldn't have been using that service to begin with, since it's a legacy thing that we inherited. I can't think of a single case where we haven't told the customer "You have to get off of that." 

What was our ROI?

It has saved us a lot of trouble in implementation.

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

The pricing came up a bit compared to their competitors. It is not that the price has risen, but that the competitors have gone down. They keep adding more features that I would have expected to be baked in at a more nominal price. I have been increasingly dissatisfied with the pricing, but not enough to jump ship. It is still pretty good.

What other advice do I have?

Check the APIs very carefully. Without fail, this is the single biggest complaint for automation and operations. It is not that it can't be done. Just make sure that you have the technical expertise to work around it.

We use a mixture of both AWS and on-premise. There are actually three scenarios: 

  1. Some of our customers purchase it for AWS. 
  2. Some of them were accounts that we set up directly on Datadog for our customers. 
  3. In some cases, customers already have a relationship with Datadog. 

Those are the three scenarios. Some have a mixture of scenarios due to regulatory reasons.

Disclosure: My company has a business relationship with this vendor other than being a customer: Reseller.
PeerSpot user
reviewer2045049 - PeerSpot reviewer
Product Manager, Delivery Engineering at a media company with 1,001-5,000 employees
Real User
Intuitive to set up with great dashboards and dashboards and APM
Pros and Cons
  • "The tools are powerful and intuitive to set up."
  • "Billing should be more transparent."

What is our primary use case?

The main use case is observability and reliability as part of a platform/delivery engineering solution. We use the product to assist tenants and clients within the company to get more ramped up on SRE/DevOps.

How has it helped my organization?

The solution has provided us with a lot more insight into service-level metrics, which is especially useful with APM/tracing. It gives us all-up dashboards and alerts to assist with incident management.

What is most valuable?

The most useful aspects of the product are the dashboards and APM/tracing. The tools are powerful and intuitive to set up as well.

What needs improvement?

Custom-level metrics could be improved.

Billing should be more transparent.

For how long have I used the solution?

I've used the solution for three to four years at multiple companies.

What do I think about the stability of the solution?

The solution is very stable.

What do I think about the scalability of the solution?

The scalability is fantastic so far.

How are customer service and support?

Technical support has been great so far.

How was the initial setup?

The initial setup is straightforward. The documentation we use is very clean and concise.

What about the implementation team?

We handled the initial setup in-house.

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

I would advise others to be cautious around custom metrics and be picky when setting them up.

Which deployment model are you using for this solution?

Hybrid Cloud

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

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
Buyer's Guide
Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.
Updated: January 2025
Buyer's Guide
Download our free Datadog Report and get advice and tips from experienced pros sharing their opinions.