Datadog vs. Kemp Flowmon ADS

Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.

Incentivized

Flowmon ADS is a customizable anomaly detection solution with excellent scalability capabilities and quick integration into the organization environment. Flowmon ADS provides a large set of essential detections out of the box, which allows to quickly acquire an awareness of potential problems in the monitored network. Custom configuration, filters, and false-positive flagging make the system highly customizable for diverse environments. Powerful dashboards make summaries and reporting a breeze. We use the Flowmon Anomaly Detection System daily for event detection and incident handling. It provides high-quality detection methods with low false-positive rates.

• Create Dashboards as per application, environments, and Custom metrics in one panel.
• Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
• Playbooks, SLA definition, success and error quotas, request visualizations.
• DB monitoring, Serverless stack monitoring.
• Alerting of Production incidents so we can quickly resolve the issues on time.

Incentivized

• Kemp Flowmon ADS provides a large set of essential detections out of the box, which allows us to quickly acquire an awareness of potential problems in the monitored network.
• Custom configuration, filters, and false-positive flagging make the system highly customizable for diverse environments.
• Powerful dashboards make summaries and reporting a breeze.

• 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

Incentivized

• Multi-license policy
• Outdated GUI
• Limited use of AI methods

There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.

Incentivized

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

Incentivized

We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized

• Early detection of cyber security events and incidents.
• Processing a large number of network flows on input (which means more than 60K flows per second)
• Parameterization of detection methods.
• The possibility to decide on the false-positive rate within the output of each method.