This product assessment is based on a synthesis of 12 recent reviews covering overall satisfaction and return on investment. Datadog is primarily used for monitoring and alerting, with 7 of 12 reviewers citing this as a core use case. The platform provides real-time insights into system performance and health, often incorporating logs and traces (6 of 12 reviewers) for debugging and historical analysis. Datadog also supports incident management, playing a role in maintaining responsive strategies for 2 of 12 reviewers. Reviewers appreciate Datadog's ability to proactively identify and address issues through threshold- and anomaly-based alerts. Datadog's strengths lie in log management (7 of 12 reviewers) and APM capabilities (4 of 12 reviewers). Dashboards and monitoring functionalities are also well-regarded, with 3 of 12 reviewers appreciating the ability to create custom dashboards. However, a notable concern is the high cost and pricing, mentioned by 3 of 12 reviewers, which can potentially escalate expenses. Overall, Datadog offers value in issue management and platform optimization, with 6 of 12 reviewers highlighting improvements in issue detection and resolution, including faster debugging and issue diagnosis within minutes.

Pros

Effective logs and log management capabilities
Strong Application Performance Monitoring (APM) and tracing features
Customizable dashboards and monitoring functionalities
Improved issue detection and faster resolution times
Proactive alerting based on thresholds and anomalies

Cons

High costs and potentially escalating pricing
Cost considerations need careful management

Why it matters:

Datadog is frequently used for monitoring and alerting, with 7 of 12 reviewers mentioning its importance in gaining real-time insights into performance, health, and errors within their infrastructure. Reviewers set up monitoring and alerting with SLOs to track service health, using metrics to monitor system performance in real time, from server CPU to application-specific KPIs. Threshold- and anomaly-based alerts notify teams via Slack when issues arise, enabling proactive responses.

“Datadog is used as a monitoring and observability platform to gain real-time insights into performance, health, and errors within our infrastructure.”

Why it matters:

A significant portion of reviewers, 7 out of 12, praised Datadog's log management capabilities. Reviewers specifically value the ability to aggregate, search, and retain logs efficiently. The user interface for searching logs and traces also received positive feedback.

“Log aggregation with seamless search indexes”

Why it matters:

Half of the reviewers (6 of 12) cited that Datadog improved their ability to detect and resolve issues. Reviewers specifically mentioned faster detection and resolution of errors, quicker debugging, and the ability to diagnose issues within minutes. One reviewer noted that Datadog helped them avoid hundreds or thousands of potential incidents.

“Faster detection and resolution of errors/issues”

What positive or negative impact (i.e. Return on Investment or ROI) has Datadog had on your overall business objectives?

From 12 reviews

Summary

This report analyzes 12 recent reviews to assess Datadog's impact on business objectives. A significant portion of reviewers, 6 of 12, highlight improvements in issue detection and resolution. For example, reviewers cite faster debugging and the ability to detect and diagnose issues within minutes. Improved platform performance was also noted by 2 reviewers, who mentioned enhanced availability and alerting capabilities. However, 3 of 12 reviewers expressed concerns regarding high costs and pricing, noting the potential for expenses to escalate. While the tool appears to offer benefits in terms of issue management and platform optimization, potential customers should consider the cost implications.

Reviews

45 Reviews

Top notch product with cutting edge features

Rating: 8 out of 10

Incentivized

June 10, 2025

Use Cases and Deployment Scope

Datadog serves as our primary observability platform and helps us to maintain responsive incident management strategy for our product. Datadog covers many use cases which includes generating key custom metrics for top-level analytics of our data, APM traces that tracks fine-grained microservices communication with continuous log aggregation and multiple test suites for our product.

Pros

Log aggregation with seamless search indexes
APM traces that describes each call to every microservice and their communication
All out-of-the box and third party integrations within Datadog
Keeping with the AI trends with LLM monitoring assistance

Cons

Datadog on-call service

Likelihood to Recommend

Datadog SDK is well equipped for to any framework. This helps organizations to define custom metrics, log aggregation and APM trailing. Datadog's monitors help to ensure high availability of any product with rapid response rate to any application. The product is well integrated with all the third-party softwares available in the market.

Jaswanth Banavathu

DevOps Engineer in Engineering at Alkymi (11-50 employees)

Vetted Review

3 years of experience

View profile

Great tool and industry standard

Rating: 7 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

In our organization, Datadog is a core observability tool used across the platform and application teams to ensure the reliability, performance, and scalability of our systems. As a platform team, we leverage Datadog to provide standardized monitoring, alerting, and visibility for both infrastructure and services used by multiple engineering teams.

Pros

Metrics dashboards
APM
Service health metrics

Cons

The search dialog and conventions around naming services, resources, etc.

Likelihood to Recommend

Where Datadog is good: - Real-time Visibility During Incidents: During high-severity incidents, Datadog dashboards, coupled with real-time logging and APM traces, provide immediate insight into system health and enable fast triage. For example, we’ve used trace ID correlation between logs and APM to quickly identify downstream service failures due to network degradation during a major outage. - Service Ownership at Scale: With over 50 engineering teams, providing self-service monitoring is essential. We use Datadog monitors, SLO dashboards, and templates so teams can track their own service health without reinventing the wheel. Tagging and RBAC features help us scope data access appropriately. Where Datadog can improve: While Datadog’s logging capabilities are powerful, storing all application logs in Datadog can become cost-prohibitive at high volumes.

Verified User

Engineer in Engineering (1001-5000 employees)

Vetted Review

7 years of experience

Datadog

Rating: 8 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

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.

Verified User

Engineer in Engineering (11-50 employees)

Vetted Review

4 years of experience

Great tool

Rating: 9 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

Datadog provides us valuable insights to metrics and trends that help us make informed decisions. We also heavily use logging, along with traces, which provides full context of the request in case something goes wrong, and helps to debug. Monitoring and alerting is another feature that we heavily rely on. Our pagerduty alerts are triggered by Datadog monitors.

Pros

Logging
Metrics
Dashboards and visualizations

Cons

Monitoring provides false alarms sometimes, so it could be tweaked
More examples on website for product usage e.g. query syntax
Visualization generation using AI

Likelihood to Recommend

Datadog is a great tool for logging and metrics. It also provides out of the box dashboards for infrastructure e.g. Kubernetes. Based on the logs and metrics, various visualizations can be created and aggregated in dashboards, which provides valuable insights, and many of our key decisions are made based on the insights. Also, our alerts are leveraging Datadog monitors, which again, are based on logs and metrics.

Verified User

Engineer in Engineering (1001-5000 employees)

Vetted Review

3 years of experience

Datadog - a powerful all inclusive tool

Rating: 8 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

Datadog is used as a monitoring and observability platform to gain real-time insights into performance, health, and errors within our infrastructure. We use infrastructure monitoring, application performance monitoring, database monitoring, and real user monitoring on a daily basis to check the status of our web and mobile applications. Datadog integration is at the front of any new application that we build and use.

Pros

Unified monitoring - it is easy to find errors and issues from the database all the way to the user experience and vice versa.
Easy integration - set up was quick and painless and there are many out of the box integrations that require just a few button clicks.
Dashboards/monitoring - easy to build complex monitors and dashboards to account for the smallest of details.

Cons

Pricing - pricing is complex and can become expensive if you don't keep an eye on it.
Logs - equally as complex and not easy to manage when you have high log volume.
Mobile app - hard to use and doesn't have a lot of items.

Likelihood to Recommend

Datadog is great on modern applications and will serve users well when adding monitoring, logging, and other integrations into these applications. Datadog is not as easy on legacy (or monolith) applications that have years of tech debt. These older, monolithic applications are often hard for engineers to work with, so adding in modern monitoring solutions into something that is already challenging is a challenge itself.

Verified User

Team Lead in Engineering (51-200 employees)

Vetted Review

2 years of experience

Practical review.

Rating: 10 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

We are using Datadog to review logs for customer, their RUM sessions. It is very helpful at times when we have to see what customers actually did and then claims otherwise. It is very helpful in checking the ip address so that we know for sure that not some other person tried to access the website as sometime same url is accessible by multiple people for one customer.

Pros

RUM session
Logs
Synthetic monitoring

Cons

Browser test may be improved

Likelihood to Recommend

Its is very detailed and provide all the information you need,

Verified User

Manager in Information Technology (51-200 employees)

Vetted Review

5 years of experience

Datadog - The Swiss Army Knife for SaaS

Rating: 8 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

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.

Verified User

Engineer in Engineering (51-200 employees)

Vetted Review

1 year of experience

Datadog - one stop monitoring with great visualizations

Rating: 10 out of 10

Incentivized

May 13, 2025

Use Cases and Deployment Scope

We have a number of various layers and integrations such as front ends, middleware, micro services, backends and databases. Datadog has allowed us to integrate monitoring across all these various systems. This helps us in many ways, particularly in tracking down which pieces are effected by problems, often to find the root of the problem. Performance bottlenecks also become much easier to find, by having one centralized monitoring solution. The visualizations we've been able to build provide a much appreciated way for even less technical people to understand.

Pros

High level monitoring of various our connected systems
Examining the very low level details of each individual system
Starting at the top level and "drilling" down deep, level by level.

Cons

Initial login shows many, many menu options. It can be daunting to know where to start.
Having a way to see which menu items are in use, or have data to "see" could help me find things my coworkers have set up.
Maybe "News" feed, a way to have "new data resources" that have been added by myself or my coworkers?

Likelihood to Recommend

Maybe it might not be appropriate for organizations that don't have much to monitor. It certainly seems ideal for any cases where there are various systems with logging and performance stats coming from different places, and in different forms. This has been especially helpful for us with the systems that are interconnected.

Verified User

Engineer in Engineering (501-1000 employees)

Vetted Review

1 year of experience

Possibly best on the market

Rating: 10 out of 10

Incentivized

May 13, 2025

Use Cases and Deployment Scope

We use Datadog primarily for monitoring and alerting, and debugging issues by viewing logs and traces.

Having several environments we need to look through logs often on Datadog to debug and understand where issues are coming from. Whether it be metrics related to kubernetes or logs from our actual services.

Monitoring and alerting is set up with SLOs to keep track of service health, following the software catalogue map of dependancies and traces/logs to root cause potential issues.

Pros

UI/UX of searching for logs/traces/general navigation
Features integrating with various infrastructure components including details kubernetes metrics
Dependancy graphs to show connections between services making it easy to figure out how systems are connected and what affects what and how
Granularity of errors and causes

Cons

Terraform intergration/documentation
Cleaner way to handle several monitors/alerts
Small thing but viewing larger time ranges without having to move a window around

Likelihood to Recommend

Datadog is a great near all in one monitoring tool for viewing logs and following an error through the whole stack to figure out what an issue is, possibly the best on the market. Ease of use and nice user experience with plenty of features makes it simple for even those with less technical knowledge to pick up and start using.

Verified User

Engineer in Engineering (51-200 employees)

Vetted Review

3 years of experience

Datadog review

Rating: 10 out of 10

Incentivized

May 13, 2025

Use Cases and Deployment Scope

I use Datadog to document and learn from incidents across all aspects of our business. From Engineering, to operational, to security incidents.

By using Datadog's Incident Management tools we've been able to document incident root causes, increase awareness and communication about incidents and their impact when they occur, and broadcast learnings during a postmortem to other teams across the business to help prevent a similar issue from occurring with a different team/application.

Pros

Incident Management
Realtime User Monitoring
Watchdog AI detection

Cons

Increased personalization
increased customization of Incident Management

Likelihood to Recommend

I highly recommend all companies that are looking to level up their visibility into their complex engineering systems to use Datadog.

Verified User

Manager in Engineering (10,001+ employees)

Vetted Review

3 years of experience

Loading Reviews List....

Datadog

Rating: 8 out of 10

Incentivized

May 14, 2025

Use Cases and Deployment Scope

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

Verified User

Engineer in Engineering (11-50 employees)

Vetted Review

4 years of experience