Datadog vs. Request Metrics

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.

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Request Metrics is great for small web development teams that want to make fast web applications. It was quick for us to get started and we could use the reports right away without having to read through documentation. If you just need to get some performance metrics, Request Metrics is perfect. It would not be so good for a larger team or a complex backend application as it is pretty limited in what it can measure.

• 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.

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• Performance charts are really simple and easy for us to understand what is happening
• It was easy to get started and doesn't need administration or training
• It's affordable for our team
• It's fast

• 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

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• I wish that it could also do uptime checking of the site
• There is not enough detail to drill into individual users

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.

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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.

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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.

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We also consider Speedcurve and Calibre for monitoring. Speedcurve was really nice, but the reports were slow. We had to wait a lot to get information. It was also out of our budget and would require extra justification to use it. Calibre was also nice, but the numbers were based on synthetic rather than real user performance. We felt that this wasn't as helpful for us.

• 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.

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• The launch of our project dashboard was much smoother and more successful because we could fix problems earlier
• It fit without our existing operations budget