Datadog review
What do you like best about the product?
Datadog provides detailed monitoring, collecting data from different sources, such as servers, DBs and others. It's a complex tool with many different features, but UI helps users to navigate and find relevant information.
What do you dislike about the product?
It has quite a steep learning curve, and takes time to get experience.
What problems is the product solving and how is that benefiting you?
It provides detailed information about the infrastructure of the system, gives insights on the performance bottlenecks and many more.
Ultimate tool for Log Management
What do you like best about the product?
Datadog does particularly well in Incident Detection. Datadog enables real-time monitoring of service health, with alerting configured via integrations like PagerDuty. This helps us quickly detect production issues, minimise downtime, and maintain SLA/SLO commitments.
At Indeed, we use Datadog extensively across our engineering organisation for monitoring, incident detection, observability, and SLO management. It plays a critical role in ensuring the reliability and performance of our services, especially those with high user impact like the IRL Sign-In Tool and our GraphQL APIs. I use Datadog very frequently because it is easy to use and easy to integrate.
What do you dislike about the product?
The Datadog UI is powerful but can be intimidating and cluttered especially when building complex queries or nested monitors. There is a learning curve for everyone.
What problems is the product solving and how is that benefiting you?
Datadog does particularly well in Incident Detection. Datadog enables real-time monitoring of service health, with alerting configured via integrations like PagerDuty. This helps us quickly detect production issues, minimise downtime, and maintain SLA/SLO commitments.
At Indeed, we use Datadog extensively across our engineering organisation for monitoring, incident detection, observability, and SLO management. It plays a critical role in ensuring the reliability and performance of our services, especially those with high user impact like the IRL Sign-In Tool and our GraphQL APIs. Datadog addresses several business problems at Indeed company like, 1. Incident Detection and Response Datadog enables real-time monitoring of service health, with alerting configured via integrations like PagerDuty. This helps us quickly detect production issues, minimise downtime, and maintain SLA/SLO commitments. 2. End-to-End Observability With distributed tracing, log correlation, & metrics, we can pinpoint bottlenecks or failures across our micro services particularly valuable in our Envoy mesh based architecture and coroutine heavy services.
Datadog :A Powerhouse Monitoring Tool
What do you like best about the product?
As an explorer who uses several monitoring solutions for cloud based applications, Datadog standout with its unique features. A key advantage of Datadog is its capacity to give a complete tech stack which is its core strength.
What do you dislike about the product?
Actually, I have no complaint of this product and I am fully satisfied.
What problems is the product solving and how is that benefiting you?
Datadog makes it easy to visualize the infrastructure. It is easy to monitor easily you can analyze with logs. It can create custom alerts or automate them to give alerts. It helps to reduce complexity of cloud infrastructure and services. It also helps in log management and enables trouble shooting.
Best observability platform for infrastructure ,APM and RU
What do you like best about the product?
We can create real time dashboards for better observability
Best tool for infrastructure,APM and Rummonitoring purpose
What do you dislike about the product?
Cost-i think it is too much costly,it should be less costly
What problems is the product solving and how is that benefiting you?
We are using here for application performance monitoring,real user monitoring and infrastructure monitoring so we dont need to use multiple tools for each monitoring
Datadog is a great monitoring and observability tool
What do you like best about the product?
Is a tool that provides many services like infrastructure monitoring, logging, database monitoring, etc. The great about this is that all services are interconnected, so when a problem ocuurs in your systems you can configure Datadog to have end 2 end visibility of your platform, helping the engineers to debug and find problems easy and fast enough.
What do you dislike about the product?
Sometimes the ui is very overwhelming, specially at the beginning, so many buttons and features makes the platform very complex to use, so the leraning curve is a bit hard at the beginnning, once you learn to use it is really simple and intuitive
What problems is the product solving and how is that benefiting you?
The monitoring and alerting systems we have in AWS and GCP are good to identify problems, but when it comes to review an end 2 end problem that there is no clue when the error is happening, datadog is providing the tools to follow step by step with full visibility of our systems. This is increasing the productivity of the engineering team a lot. We are right now finalizing our trial version but I can tell that not even getting the full potentil of it yet, is really promising what we achieved in just a few weeks. Very excited of what is coming with the new discoveries of this platform features
Amazing UX
What do you like best about the product?
The user experience of DataDog is amazing. The granuality and flexibility of filters and charts makes it easy to quickly sift through large amounts of data and find what you need. This is especially useful when trying to quickly troubleshoot an incidents.
What do you dislike about the product?
One annoying thing about DataDog is working with IoC configurations that are defined in Terraform.
It's tough to make changes to your configurations because you need to deploy them in order to see if you did it correctly. It's also not possible to lock down resources defined with IoC, so sometimes people will edit something via the web UI that was conficuged in Terraform and then their changes will get reverted when Terraform re-deploys and they won't know why.
What problems is the product solving and how is that benefiting you?
System observability and incident response.
One Stop Solution (360 degree Monitoring)
What do you like best about the product?
Ecosystem and integration!
Effective communication between different Datadog products, such as APM and Infrastructure, shows detailed traces that I can drill down into to pinpoint the issue.
What do you dislike about the product?
There is a need for more improvements and features in the Datadog security lineup. A centralized SCA and SAST is lacking. Additionally, easier integration with MS Teams and other third-party software is necessary.
Flutter support in Real User Monitoring (it is not fully supported yet).
What problems is the product solving and how is that benefiting you?
1. At one glance I can see status of my production environment.
2. If there is issue in midnight then watchdog given me exact context on where is the failure and which all microservices were involved along with CPU and RAM usage of given period.
3. If there is crash for mobile application then it directly reports and create errors error tracking which I can assign it to team.
4. If there is vulnerability in the production then it scan and report.
5. If someone is trying to hijack the system then I can block those IPs.
6. Datadog detects unusual activities and reports it.
7. We have configured reports which get sends daily at 9AM to see previous day statics for review purpose so we are proactive if there are any issues.
Very useful custom matrics
Fair point about the open metrics integration. All metrics collected by that specific "integration" are considered custom. There are many ways to collect custom metrics. Through a open metrics endpoint, collecting metrics from logs, metrics from traces, custom check, or submitting metrics directly to the agent.
Debugs slow performance with good support and a straightforward setup
What is our primary use case?
We use Datadog for monitoring the performance of our infrastructure across multiple types of hosts in multiple environments. We also use APM to monitor our applications in production.
We have some Kubernetes clusters and multi-cloud hosts with Datadog agents installed. We have recently added RUM to monitoring our application from the user side, including replay sessions, and are hoping to use those to replace existing monitoring for errors and session replay for debugging issues in the application.
How has it helped my organization?
We have been using Datadog since I started working at the company ten years ago and it has been used for many reasons over the years. Datadog across our services has helped debug slow performance on specific parts of our application, which, in turn, allows us to provide a snappier and more performant application for our customers.
The monitoring and alerting system has allowed our team to be aware of the issues that have come up in our production system and react faster with more tools to debug and view to keep the system online for our customers.
What is most valuable?
Datadog infrastructure monitoring has helped us identify health issues with our virtual machines, such as high load, CPU, and disk usage, as well as monitoring uptime and alerting when Kubernetes containers have a bad time staying up. Our use of Datadog's Application Monitoring, APM over the last six years or so has been crucial to identifying performance and bottleneck issues as well as alerting us when services are seeing high error rates, which have made it easier to debug when specific services may be going down.
What needs improvement?
We have found that some of the different options for filtering for logs ingestion, APM traces and span ingestion, and RUM sessions vs replay settings can be hard to discover and tough to determine how to adjust and tweak for both optimal performance and monitoring as well as for billing within the console.
It can sometimes be difficult to determine which information is documented, as we have found inconsistencies with deprecated information, such as environment variables within the documentation.
For how long have I used the solution?
I've been using the solution for ten years.
What do I think about the stability of the solution?
The solution seems pretty stable, as we've been using it for more than a decade.
What do I think about the scalability of the solution?
The solution seems quite scalable, especially within Kubernetes. Costs are a factor.
How are customer service and support?
SUpport has been very helpful whenever we need it.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
We had tried some other APM monitoring in the past, however, it was too expensive, and then we added it to Datadog since we were already using Datadog and it seemed like a good value add.
How was the initial setup?
The solution is straightforward to set up. Sometimes, it is complex to find the correct documentation.
What about the implementation team?
We handled the setup in-house.
What was our ROI?
Our ROI is ease of mind with alerts and monitoring, as well as the ability to review and debug issues for our customers.
What's my experience with pricing, setup cost, and licensing?
Getting settled on pricing is something you want to keep an eye on, as things seem to change regularly.
Which other solutions did I evaluate?
We used New Relic previously.
What other advice do I have?
Datadog is a great service that is continually growing its solution for monitoring and security. It is easy to set up and turn on and off its features once you have instrumented agents and tailored solutions to your needs.
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?
Other
Easy to configure with synthetic testing and offers a consolidated approach to monitoring
What is our primary use case?
We use this solution for enterprise monitoring across a large number of applications in multiple environments like production, development, and testing. It helps us track application performance, uptime, and resource usage in real time, providing alerts for issues like downtime or performance bottlenecks.
Our hybrid environment includes cloud and on-premise infrastructure. The solution is crucial for ensuring reliability, compliance, and high availability across our diverse application landscape.
How has it helped my organization?
Datadog has greatly improved our organization by centralizing all monitoring into one platform, allowing us to consolidate data from a wide range of sources.
From infrastructure metrics and application logs to end-user experience and device monitoring, everything is now collected and displayed in one place. This has simplified our monitoring processes, improved visibility, and allowed for faster issue detection and resolution.
By streamlining these operations, Datadog has enhanced both efficiency and collaboration across teams.
What is most valuable?
Synthetic testing is by far the most valuable feature in our organization. It’s highly requested since the setup process is both quick and straightforward, allowing us to simulate user interactions across our applications with minimal effort.
The ease of configuring tests and interpreting the results makes it accessible even to non-technical team members. This feature provides valuable insights into user experience, helps identify performance bottlenecks, and ensures that our critical workflows are functioning as expected, enhancing reliability and uptime.
What needs improvement?
One area where the product could be improved is Application Performance Monitoring (APM). While it's a powerful feature, many in our organization find it difficult to fully understand and utilize to its maximum potential.
The data provided is comprehensive, yet it can sometimes be overwhelming, especially for those who are less familiar with the intricacies of application performance metrics.
Simplifying the interface, offering clearer guidance, or providing more intuitive visualizations would make it easier for users to extract valuable insights quickly and efficiently.
For how long have I used the solution?
I've used the solution for four years.
What do I think about the stability of the solution?
The solution is very stable. Issues happen once or twice a year and are usually solved before we have any real impact on the service.
What do I think about the scalability of the solution?
Scalability has never been a bottleneck for us; we've never felt any issues here.
How are customer service and support?
Support is slow at the beginning, however, they are much better and responsive now.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
Datadog offered the most consolidated approach to our monitoring needs.
How was the initial setup?
This was a migration project, so it was rather complex.
What about the implementation team?
We implemented the solution with our in-house team.
What's my experience with pricing, setup cost, and licensing?
I'd recommend new users look down the road and decide on at least a three-year plan.
Which other solutions did I evaluate?
