Datadog vs. VictoriaMetrics Community

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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Best suited, where your data is highly cardinal since it does a better job at maintaining it than other competitors. It is also well suited if you are using Prometheus and are looking for something that is less hungry for resources in comparison since the migration would be easier. But in case the company is small and wants a solution which is cheap and relies on built-in visualizations, it is not something that is suited. Although it takes fewer resources than Prometheus, it is still resource-intensive and attracts a high cost for maintenance.

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• 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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• Easy to configure and manage
• Ready to be configured at cloud and microservices
• Easy to scale vertically and horizontally

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• 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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• Community and Eco system -> Although it supports the ecosystem of Prometheus, it is still troublesome for someone who's not using Prometheus
• Configuration is not so easy, especially if you are a beginner, you will struggle a bit. Even the documentation is not so welcoming for beginners
• Built-in Visualisation is bare minimal, leading almost everyone to use some other extension/tool

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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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Prometheus only support PromQL and it is very complex with different exporter required for different requirement like Windowsexporter,linixexporter,sqlexporter etc but VictoriaMetrics is very simple comapred to it. VictoriaMetrics support both PromQL and MetricQL and can be integrated with Graphana easily. It is very easy to setup and learn compared to mutiple Prometheus exporters

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• 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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• Lowered our infra costs in comparison with our older tools
• Need minimal effort for migration since it already supports Prometheus ecosystem
• Saved on Storage costs

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