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README.md: add more information to rough estimation of the required resources
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@ -393,14 +393,19 @@ Rough estimation of the required resources:
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* RAM size: less than 1KB per active time series. So, ~1GB of RAM is required for 1M active time series.
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Time series is considered active if new data points have been added to it recently or if it has been recently queried.
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VictoriaMetrics stores various caches in RAM. Memory size for these caches may be limited with `-memory.allowedPercent` flag.
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VictoriaMetrics stores various caches in RAM. Memory size for these caches may be limited by `-memory.allowedPercent` flag.
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* CPU cores: a CPU core per 300K inserted data points per second. So, ~4 CPU cores are required for processing
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the insert stream of 1M data points per second.
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the insert stream of 1M data points per second. The ingestion rate may be lower for high cardinality data.
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See [this article](https://medium.com/@valyala/insert-benchmarks-with-inch-influxdb-vs-victoriametrics-e31a41ae2893) for details.
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If you see lower numbers per CPU core, then it is likely active time series info doesn't fit caches,
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so you need more RAM for lowering CPU usage.
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* Storage size: less than a byte per data point on average. So, ~260GB is required for storing a month-long insert stream
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of 100K data points per second.
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The actual storage size heavily depends on data randomness (entropy). Higher randomness means higher storage size requirements.
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Read [this article](https://medium.com/faun/victoriametrics-achieving-better-compression-for-time-series-data-than-gorilla-317bc1f95932)
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for details.
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### High availability
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