We use Datadog to assess logs and rum sessions & review the scope of our code. It's a fascinating tool, to be very honest; we switched over to it after using other services. Datadog is superior to its competitors, offering a one-stop shop for all your needs. Now, we're used to the platform and can't move forward without it.
Pros
Rum sessions.
Error logs.
Client preference views.
Cons
Firebase scoop.
Parallel automation testing.
Local pipeline runs.
Likelihood to Recommend
A one-stop solution for everything you need. Multiple functionalities are tailored to meet specific business needs. Logs are essential for any business, and Datadog manages logs effectively. Rum sessions are something new to me and have given us a new perspective on how to reverse engineer issues that we see for our customers.
VU
Verified User
Team Lead in Quality Assurance (Computer Software company, 11-50 employees)
At our small startup of seven engineers, we use Datadog to centralize observability across our stack. For logging, we aggregate application and infrastructure logs to quickly debug issues with contextual insights. Metrics help us monitor system performance in real time, from server CPU to application-specific KPIs. We’ve created tailored dashboards to visualize key data points for different services, enabling faster decision-making during incidents or deployments. For alerting, we’ve set up threshold- and anomaly-based alerts that notify us via Slack when something goes wrong, allowing us to respond proactively. Datadog keeps our team aligned and efficient without needing a dedicated ops team.
Pros
Tracking and grouping errors, with comment history across time
Searching and retaining logs
Creating custom dashboards and alert monitors
Cons
Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
I would appreciate more supportive examples for how to filter and view metrics in the explorer
I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Likelihood to Recommend
Datadog excels in microservices environments where visibility across distributed systems is critical. For example, we use it to trace latency spikes across services, correlate logs during outages, and monitor deployments with custom metrics. It’s ideal for real-time alerting—catching memory leaks or sudden traffic drops. However, for large-scale log ingestion, it becomes expensive quickly, making it less ideal for storing high-volume debug logs long-term. Also, Datadog’s UI can be overwhelming for new users, requiring training to navigate effectively. For simpler apps or teams needing only basic monitoring, lighter-weight or open-source tools like Prometheus and Grafana might be more appropriate.
VU
Verified User
Engineer in Engineering (Computer Software company, 11-50 employees)
We use Datadog to monitor our SaaS offering from Cloud Infrastructure to Real User Monitoring with Session Recording with correlated APM and application logs. We also have Product Analytics and the SIEM. What I like best about Datadog is that one company with a common UX offers all of this in a way our most technical to least technical staff can use. The integration is automatic because it's all one platform from one company. Why buy different products and try to make them work together when you can buy from one company and know that the aspect of their portfolio you wish to implement is compatible and ready to go.
Pros
Session Recording
Application Performance Monitoring
Application Logs
Product Analytics
Cons
There are so many ways to set it up you'll spend more time trying to pick which will work best for your goals.
They are always upselling and looking for contracts, but the discount for committing to a level of consumption is usually eroded or exceeded by the unused portion of the committed allocation
They offer EU data residency, but you can't store your data in the EU and pay for it through the AWS Marketplace.
Likelihood to Recommend
Datadog is a great tool for a Product-driven SaaS company, because if offers the data and metrics Product, Sales, & Marketing all want while providing your developers and engineers the data they need to make the improvements that are brought to light from the Product Analytics offering. There is also plenty of troubleshooting and monitoring tools to spot problems and implement solutions. I chose Datadog to replace Elastic, FullStory, Sentry while getting more overall functionality.
VU
Verified User
Engineer in Engineering (Computer Software company, 51-200 employees)
Use Datadog for error tracking, along with insight management with logs and apm traces. Apm traces is really helpful with nodejs opentelemtry as it allows us to track each of the function calls associated with the lifecycle of a specific trace (say an http requests lifecycle) which helps debug easier.
Pros
APM Traces
Watchdog
Logs
Error states
Cons
Expensive
Lack of easy facet management
Hard to query certain values
Likelihood to Recommend
Sentry might be better for something like error tracking honestly I feel like, because Datadog loses a lot of stack traces. Maybe this is a case of the Datadog client and / or agent not being that great at relaying the information from the originating context to the client to ingest.
VU
Verified User
C-Level Executive in Engineering (Computer Software company, 1-10 employees)
We use Datadog as the main observability tool in my organization and across the company. We use logs, metrics, and traces for monitoring and investigation of historical performance. We also started to try out some of the new capabilities, such as error tracking, CI performance tracking, and Kubernetes monitoring.
Pros
UI is simple to use and understand
Query is blazingly fast
Little configuration is needed
Cons
Some small bugs that are basic and have been in place for years
Pricing is high
Support is slow and sometimes not helpful
Likelihood to Recommend
It is the go-to option if I am looking for a good level of monitoring that is easy to set up and immediately satisfies my fundamental needs. It is good for early/mid stage companies who don't want to spend too much efforts on observability. However, one should pay extra attention to costs.
VU
Verified User
Engineer in Engineering (Computer Software company, 1001-5000 employees)
DataDog is used as directional monitoring tool for all the applications. It is used for full stack monitoring from backend to frontend as well as end user. It helps in keeping tabs on the performance of application and also help in troubleshooting at times of any outages. It also helps in identifying the the area that can we worked upon to improve application performance.
Pros
Application Performance Monitoring
Browser and end user monitoring
Infrastructure monitoring
Third-party integrations
Cons
Synthetic Monitoring
Integration with IDE tools
Root access needed for agent installation
Likelihood to Recommend
This is best suited for monitoring web applications. One will be able to monitor all the components be it infrastructure monitoring for servers or application or end user monitoring, all can be achieved though installation of a single agent on your server. Only drawback is that you need to have root access to the server to onboard a server to datadog.
VU
Verified User
Engineer in Engineering (Telecommunications company, 5001-10,000 employees)
We use Datadog to trace and monitor our whole infrastructure. The APM feature is a blessing. Also, the log stream is way better than the same features of similar products. We used it to gather and centralize data from AWS into an easy-to-understand dashboard. For example, we created dashboards with the data per environment about availability, error rates, error quotas & network traffic.
Pros
APM
Log streaming
Playbooks, which are a collection of "views" that you can aggregate into a single dashboard.
Cons
JSON parsing on logs
Documentation
Likelihood to Recommend
If you want to get the most insightful data from your infrastructure, and being able to take one dashboard which is easily understandable by engineers and managers, then Datadog should be your way to go.
VU
Verified User
Engineer in Engineering (Telecommunications company, 51-200 employees)
We use Datadog to monitor all kinds of application metrics: errors, network stats, response times, queues, and a bunch of application-specific metrics. We also have alerts set up that notify us of changes in production application performance. We also get a lot of metrics "for free" from all kinds of third-party tools (e.g. ElasticSearch, GitHub, Heroku, Cloudflare, etc).
Pros
Thanks to the tool's versatility and a huge ecosystem around it, you can use it to track virtually anything.
Powerful alert and warning configuration let you drastically reduce false positives.
Runbooks give your team members guidance on how to act on alerts.
Powerful data analysis features: you can slice and dice your data, almost the same way you can do it in a behavioral analytics tool. This means you can efficiently refine your metrics as your business grows.
Cons
Overwhelming to use for newcomers.
Even when you're familiar with the tool, finding the right metric or dashboard can be challenging unless you know exactly what you're looking for.
Likelihood to Recommend
If you're a cloud-based software company, you should use Datadog, period. They're a strong leader in the space for a reason. Datadog will scale with your company's data needs, and if there's something it can't do today, it probably will in the next few months or a year. It might be an overkill if your product/business is very small.
We use Datadog on almost all of our production systems to give us granularity into how systems are running, and additionally, use Datadog's logging feature to aggregate all of our logs across systems in real time. Datadog's simple dashboards enable visibility from different providers to be displayed all in one place, even if systems are not from the same vendor.
Pros
Does a good job at log management with full search, live-access, and automatic archiving to S3 is also simple.
APM is fantastic and gives great insights into production machines, but is not cheap.
Cons
Because APM is billed by instance, it can be very expensive -- perhaps even more than the cost of the underlying instances depending on the kinds of systems you are running.
While it's not difficult to deploy, it certainly has quirks owing to the limits of cloud platforms -- we wish it was easier to set up for some services.
Likelihood to Recommend
For organizations that understand and require the value-add of Datadog, it's a great choice for log management, APM, and system visibility. Because of its costs, it's not well suited to smaller organizations, or organizations running lots of small workloads on inexpensive VMs, where you are stuck paying the same price that an organization would pay for a server 100x the size.
VU
Verified User
Director in Engineering (Computer Software company, 51-200 employees)
The engineering/dev-ops teams use DataDog as the tool of choice for monitoring our applications/servers, and for aggregating logs. All of our applications and micro-services use the DataDog Rest API to send metrics to, so that we can monitor performance and CPU usage, and setup alerts in case any issues arise.
Pros
Great UX. Good looking dashboards and advanced graphs.
Simple Rest API allowing integration with basically any service/application. Allows for the creation of a centralized source of data.
Good API documentation and very responsive customer service.
Good pricing model for micro-services. Can handle getting data from many sources without having to pay as much as alternatives.
Cons
Limitation on what you can do with reporting and analytics. If you need to do very advanced mathematical/graphing operations, might need to use data in another BI Tool to accomplish.
Good amount of upfront work to install and configure across your entire application/software stack. Heavy learning curve.
Logging capabilities not as robust as alternatives like Splunk.
Likelihood to Recommend
Datadog is great when you have a complex software system, with multiple applications and micro-services. If you have the resources to do the upfront work of integrating with your platform(s), it will be a great tool to handle monitoring/alerts. It also has nice features for log aggregation. The graphs and dashboards also make Datadog a useful tool to others, such as Managers and non-Engineers, not only for Dev-Ops and Engineers directly using it. If you want something to use quicker out-of-the-box or don't want to spend any money there are quicker/cheaper options.
