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"description":"Shows the number of active time series with new data points inserted during the last hour. High value may result in ingestion slowdown. \n\nSee following link for details:",
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"description":"Percentage of used RSS memory (resident).\nThe RSS memory shows the amount of memory recently accessed by the application. It includes anonymous memory and data from recently accessed files (aka page cache).\nThe application's performance will significantly degrade when memory usage is close to 100%.\n\nClick on the line and choose Drilldown to show memory usage per instance",
"description":"Share for memory allocated by the process itself. When memory usage reaches 100% it will be likely OOM-killed.\nSafe memory usage % considered to be below 80%\n\nClick on the line and choose Drilldown to show memory usage per instance",
"description":"Shows the percentage of open file descriptors compared to the limit set in the OS.\nReaching the limit of open files can cause various issues and must be prevented.\n\nSee how to change limits here https://medium.com/@muhammadtriwibowo/set-permanently-ulimit-n-open-files-in-ubuntu-4d61064429a",
"description":"Shows the rate and total number of new series created over last 24h.\n\nHigh churn rate tightly connected with database performance and may result in unexpected OOM's or slow queries. It is recommended to always keep an eye on this metric to avoid unexpected cardinality \"explosions\".\n\nThe higher churn rate is, the more resources required to handle it. Consider to keep the churn rate as low as possible.\n\nGood references to read:\n* https://www.robustperception.io/cardinality-is-key\n* https://www.robustperception.io/using-tsdb-analyze-to-investigate-churn-and-cardinality",
"description":"The percentage of slow inserts comparing to total insertion rate during the last 5 minutes. \n\nThe less value is better. If percentage remains high (>10%) during extended periods of time, then it is likely more RAM is needed for optimal handling of the current number of active time series. \n\nIn general, VictoriaMetrics requires ~1KB or RAM per active time series, so it should be easy calculating the required amounts of RAM for the current workload according to capacity planning docs. But the resulting number may be far from the real number because the required amounts of memory depends on many other factors such as the number of labels per time series and the length of label values. See also https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3976#issuecomment-1476883183",
"description":"Shows the percentage of used cache size from the allowed size by type. \nValues close to 100% show the maximum potential utilization.\nValues close to 0% show that cache is underutilized.",
"description":"VictoriaMetrics limits the number of labels per each metric with `-maxLabelsPerTimeseries` command-line flag.\n\nThis prevents from ingesting metrics with too many labels. The value of `maxLabelsPerTimeseries` must be adjusted for your workload.\n\nWhen limit is exceeded (graph is > 0) - extra labels are dropped, which could result in unexpected identical time series.",
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"description":"Shows the time needed to reach the 100% of disk capacity based on the following params:\n* free disk space;\n* row ingestion rate;\n* dedup rate;\n* compression.\n\nUse this panel for capacity planning in order to estimate the time remaining for running out of the disk space.\n\n",
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