Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. It is now a standalone open source project and maintained independently of any company. Prometheus collects metrics from configured targets at given intervals, evaluates rule expressions, displays results, and triggers alerts if some condition is observed to be true.
For more information, you can visit the official Prometheus website.
One common issue users encounter with Prometheus is the 'Metric type conflict'. This occurs when you see errors or warnings in your Prometheus logs indicating that there is a conflict in metric types. This can lead to incorrect data being collected or displayed, and potentially cause alerts to trigger incorrectly.
The 'Metric type conflict' arises when different exporters use the same metric name but define it with different types. For example, one exporter might define a metric as a counter, while another defines it as a gauge. Prometheus requires that each metric name be associated with a single type, and conflicts can cause data collection issues.
For a deeper dive into how Prometheus handles metrics, you can check out the Prometheus Metric Types documentation.
First, you need to identify which metrics are causing the conflict. Check your Prometheus logs for warnings or errors related to metric types. You can use the following command to filter logs:
grep 'error' /var/log/prometheus/prometheus.log
Look for lines that mention 'metric type' or similar phrases.
Once you've identified the conflicting metrics, verify their types in each exporter. You can do this by querying each exporter directly. For example, if you're using a Node Exporter, you can access its metrics endpoint:
curl http://:/metrics
Check the type of the metric in question and compare it across all exporters.
To resolve the conflict, ensure that all exporters use the same type for the conflicting metric. This might involve modifying the exporter configuration or updating the exporter itself. If you have control over the exporters, update them to use consistent metric types.
If standardizing the metric type is not feasible, consider renaming the conflicting metrics in one or more exporters. This will prevent Prometheus from seeing them as the same metric. Ensure that the new metric names are unique and descriptive.
Resolving metric type conflicts in Prometheus is crucial for accurate monitoring and alerting. By identifying conflicting metrics, verifying their types, and standardizing or renaming them, you can ensure that Prometheus functions correctly. For further reading, you can explore the Prometheus Naming Best Practices.
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