README.md: stylistic updates

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Aliaksandr Valialkin 2019-07-02 15:57:45 +03:00
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VictoriaMetrics is fast, cost-effective and scalable time series database. It can be used as a long-term remote storage for Prometheus.
We'd recommend using [single-node version](https://github.com/VictoriaMetrics/VictoriaMetrics) instead of cluster version
It is recommended using [single-node version](https://github.com/VictoriaMetrics/VictoriaMetrics) instead of cluster version
for ingestion rates lower than 10 million of data points per second.
Single-node version [scales perfectly](https://medium.com/@valyala/measuring-vertical-scalability-for-time-series-databases-in-google-cloud-92550d78d8ae)
with the number of CPU cores, RAM and available storage space.
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### Replication and data safety
VictoriaMetrics offloads replication to the underlying storage pointed by `-storageDataPath`.
We recommend storing data on [Google Compute Engine persistent disks](https://cloud.google.com/compute/docs/disks/#pdspecs),
It is recommended storing data on [Google Compute Engine persistent disks](https://cloud.google.com/compute/docs/disks/#pdspecs),
since they are protected from data loss and data corruption. They also provide consistently high performance
and [may be resized](https://cloud.google.com/compute/docs/disks/add-persistent-disk) without downtime.
HDD-based persistent disks should be enough for the majority of use cases.
It is recommended using durable replicated persistent volumes in Kubernetes.
### Backups
We'd recommend performing periodical backups from [instant snapshots](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282)
It is recommended performing periodical backups from [instant snapshots](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282)
for protecting from user errors such as accidental data deletion.
The following steps must be performed for each `vmstorage` node for creating a backup: