diff --git a/README.md b/README.md index 2e2f40d4b..3386b7a4c 100644 --- a/README.md +++ b/README.md @@ -49,17 +49,22 @@ Click on a link in order to read the corresponding case study * VictoriaMetrics can be used as long-term storage for Prometheus or for [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md). See [these docs](#prometheus-setup) for details. -* Supports [Prometheus querying API](https://prometheus.io/docs/prometheus/latest/querying/api/), so it can be used as Prometheus drop-in replacement in Grafana. - VictoriaMetrics implements [MetricsQL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/MetricsQL) query language, which inspired by PromQL. MetricsQL is backwards-compatible with PromQL. -* Supports global query view. Multiple Prometheus instances or any other data sources may write data into VictoriaMetrics. Later this data may be queried in a single query. +* VictoriaMetrics supports [Prometheus querying API](https://prometheus.io/docs/prometheus/latest/querying/api/), so it can be used as Prometheus drop-in replacement in Grafana. +* VictoriaMetrics implements [MetricsQL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/MetricsQL) query language backwards compatible with PromQL. +* VictoriaMetrics provides global query view. Multiple Prometheus instances or any other data sources may ingest data into VictoriaMetrics. + Later this data may be queried via a single query. * High performance and good scalability for both [inserts](https://medium.com/@valyala/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b) and [selects](https://medium.com/@valyala/when-size-matters-benchmarking-victoriametrics-vs-timescale-and-influxdb-6035811952d4). [Outperforms InfluxDB and TimescaleDB by up to 20x](https://medium.com/@valyala/measuring-vertical-scalability-for-time-series-databases-in-google-cloud-92550d78d8ae). -* [Uses 10x less RAM than InfluxDB](https://medium.com/@valyala/insert-benchmarks-with-inch-influxdb-vs-victoriametrics-e31a41ae2893) when working with millions of unique time series (aka high cardinality). +* [Uses 10x less RAM than InfluxDB](https://medium.com/@valyala/insert-benchmarks-with-inch-influxdb-vs-victoriametrics-e31a41ae2893) + and [up to 7x less RAM than Prometheus, Thanos or Cortex](https://valyala.medium.com/prometheus-vs-victoriametrics-benchmark-on-node-exporter-metrics-4ca29c75590f) + when dealing with millions of unique time series (aka high cardinality). * Optimized for time series with high churn rate. Think about [prometheus-operator](https://github.com/coreos/prometheus-operator) metrics from frequent deployments in Kubernetes. * High data compression, so [up to 70x more data points](https://medium.com/@valyala/when-size-matters-benchmarking-victoriametrics-vs-timescale-and-influxdb-6035811952d4) - may be crammed into limited storage comparing to TimescaleDB. -* Optimized for storage with high-latency IO and low IOPS (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc). See [graphs from these benchmarks](https://medium.com/@valyala/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b). + may be crammed into limited storage comparing to TimescaleDB + and [up to 7x less storage space is required comparing to Prometheus, Thanos or Cortex](https://valyala.medium.com/prometheus-vs-victoriametrics-benchmark-on-node-exporter-metrics-4ca29c75590f). +* Optimized for storage with high-latency IO and low IOPS (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc). + See [graphs from these benchmarks](https://medium.com/@valyala/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b). * A single-node VictoriaMetrics may substitute moderately sized clusters built with competing solutions such as Thanos, M3DB, Cortex, InfluxDB or TimescaleDB. See [vertical scalability benchmarks](https://medium.com/@valyala/measuring-vertical-scalability-for-time-series-databases-in-google-cloud-92550d78d8ae), [comparing Thanos to VictoriaMetrics cluster](https://medium.com/@valyala/comparing-thanos-to-victoriametrics-cluster-b193bea1683) @@ -68,7 +73,7 @@ Click on a link in order to read the corresponding case study * Easy operation: * VictoriaMetrics consists of a single [small executable](https://medium.com/@valyala/stripping-dependency-bloat-in-victoriametrics-docker-image-983fb5912b0d) without external dependencies. * All the configuration is done via explicit command-line flags with reasonable defaults. - * All the data is stored in a single directory pointed by `-storageDataPath` flag. + * All the data is stored in a single directory pointed by `-storageDataPath` command-line flag. * Easy and fast backups from [instant snapshots](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282) to S3 or GCS with [vmbackup](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmbackup/README.md) / [vmrestore](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmrestore/README.md). See [this article](https://medium.com/@valyala/speeding-up-backups-for-big-time-series-databases-533c1a927883) for more details. @@ -91,6 +96,7 @@ Click on a link in order to read the corresponding case study * Has open source [cluster version](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/cluster). * See also technical [Articles about VictoriaMetrics](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/Articles). + ## Operation ### Table of contents @@ -175,7 +181,8 @@ The following command-line flags are used the most: Other flags have good enough default values, so set them only if you really need this. Pass `-help` to see all the available flags with description and default values. -See how to [ingest data to VictoriaMetrics](#how-to-import-time-series-data) and how to [query VictoriaMetrics](#grafana-setup). +See how to [ingest data to VictoriaMetrics](#how-to-import-time-series-data), how to [query VictoriaMetrics](#grafana-setup) +and how to [handle alerts](#alerting). VictoriaMetrics accepts [Prometheus querying API requests](#prometheus-querying-api-usage) on port `8428` by default. It is recommended setting up [monitoring](#monitoring) for VictoriaMetrics. @@ -242,8 +249,9 @@ Read more about tuning remote write for Prometheus [here](https://prometheus.io/ It is recommended upgrading Prometheus to [v2.12.0](https://github.com/prometheus/prometheus/releases) or newer, since previous versions may have issues with `remote_write`. -Take a look also at [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md), -which can be used as faster and less resource-hungry alternative to Prometheus in certain cases. +Take a look also at [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md) +and [vmalert](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmalert/README.md), +which can be used as faster and less resource-hungry alternative to Prometheus. ## Grafana setup diff --git a/docs/Single-server-VictoriaMetrics.md b/docs/Single-server-VictoriaMetrics.md index 2e2f40d4b..3386b7a4c 100644 --- a/docs/Single-server-VictoriaMetrics.md +++ b/docs/Single-server-VictoriaMetrics.md @@ -49,17 +49,22 @@ Click on a link in order to read the corresponding case study * VictoriaMetrics can be used as long-term storage for Prometheus or for [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md). See [these docs](#prometheus-setup) for details. -* Supports [Prometheus querying API](https://prometheus.io/docs/prometheus/latest/querying/api/), so it can be used as Prometheus drop-in replacement in Grafana. - VictoriaMetrics implements [MetricsQL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/MetricsQL) query language, which inspired by PromQL. MetricsQL is backwards-compatible with PromQL. -* Supports global query view. Multiple Prometheus instances or any other data sources may write data into VictoriaMetrics. Later this data may be queried in a single query. +* VictoriaMetrics supports [Prometheus querying API](https://prometheus.io/docs/prometheus/latest/querying/api/), so it can be used as Prometheus drop-in replacement in Grafana. +* VictoriaMetrics implements [MetricsQL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/MetricsQL) query language backwards compatible with PromQL. +* VictoriaMetrics provides global query view. Multiple Prometheus instances or any other data sources may ingest data into VictoriaMetrics. + Later this data may be queried via a single query. * High performance and good scalability for both [inserts](https://medium.com/@valyala/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b) and [selects](https://medium.com/@valyala/when-size-matters-benchmarking-victoriametrics-vs-timescale-and-influxdb-6035811952d4). [Outperforms InfluxDB and TimescaleDB by up to 20x](https://medium.com/@valyala/measuring-vertical-scalability-for-time-series-databases-in-google-cloud-92550d78d8ae). -* [Uses 10x less RAM than InfluxDB](https://medium.com/@valyala/insert-benchmarks-with-inch-influxdb-vs-victoriametrics-e31a41ae2893) when working with millions of unique time series (aka high cardinality). +* [Uses 10x less RAM than InfluxDB](https://medium.com/@valyala/insert-benchmarks-with-inch-influxdb-vs-victoriametrics-e31a41ae2893) + and [up to 7x less RAM than Prometheus, Thanos or Cortex](https://valyala.medium.com/prometheus-vs-victoriametrics-benchmark-on-node-exporter-metrics-4ca29c75590f) + when dealing with millions of unique time series (aka high cardinality). * Optimized for time series with high churn rate. Think about [prometheus-operator](https://github.com/coreos/prometheus-operator) metrics from frequent deployments in Kubernetes. * High data compression, so [up to 70x more data points](https://medium.com/@valyala/when-size-matters-benchmarking-victoriametrics-vs-timescale-and-influxdb-6035811952d4) - may be crammed into limited storage comparing to TimescaleDB. -* Optimized for storage with high-latency IO and low IOPS (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc). See [graphs from these benchmarks](https://medium.com/@valyala/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b). + may be crammed into limited storage comparing to TimescaleDB + and [up to 7x less storage space is required comparing to Prometheus, Thanos or Cortex](https://valyala.medium.com/prometheus-vs-victoriametrics-benchmark-on-node-exporter-metrics-4ca29c75590f). +* Optimized for storage with high-latency IO and low IOPS (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc). + See [graphs from these benchmarks](https://medium.com/@valyala/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b). * A single-node VictoriaMetrics may substitute moderately sized clusters built with competing solutions such as Thanos, M3DB, Cortex, InfluxDB or TimescaleDB. See [vertical scalability benchmarks](https://medium.com/@valyala/measuring-vertical-scalability-for-time-series-databases-in-google-cloud-92550d78d8ae), [comparing Thanos to VictoriaMetrics cluster](https://medium.com/@valyala/comparing-thanos-to-victoriametrics-cluster-b193bea1683) @@ -68,7 +73,7 @@ Click on a link in order to read the corresponding case study * Easy operation: * VictoriaMetrics consists of a single [small executable](https://medium.com/@valyala/stripping-dependency-bloat-in-victoriametrics-docker-image-983fb5912b0d) without external dependencies. * All the configuration is done via explicit command-line flags with reasonable defaults. - * All the data is stored in a single directory pointed by `-storageDataPath` flag. + * All the data is stored in a single directory pointed by `-storageDataPath` command-line flag. * Easy and fast backups from [instant snapshots](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282) to S3 or GCS with [vmbackup](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmbackup/README.md) / [vmrestore](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmrestore/README.md). See [this article](https://medium.com/@valyala/speeding-up-backups-for-big-time-series-databases-533c1a927883) for more details. @@ -91,6 +96,7 @@ Click on a link in order to read the corresponding case study * Has open source [cluster version](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/cluster). * See also technical [Articles about VictoriaMetrics](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/Articles). + ## Operation ### Table of contents @@ -175,7 +181,8 @@ The following command-line flags are used the most: Other flags have good enough default values, so set them only if you really need this. Pass `-help` to see all the available flags with description and default values. -See how to [ingest data to VictoriaMetrics](#how-to-import-time-series-data) and how to [query VictoriaMetrics](#grafana-setup). +See how to [ingest data to VictoriaMetrics](#how-to-import-time-series-data), how to [query VictoriaMetrics](#grafana-setup) +and how to [handle alerts](#alerting). VictoriaMetrics accepts [Prometheus querying API requests](#prometheus-querying-api-usage) on port `8428` by default. It is recommended setting up [monitoring](#monitoring) for VictoriaMetrics. @@ -242,8 +249,9 @@ Read more about tuning remote write for Prometheus [here](https://prometheus.io/ It is recommended upgrading Prometheus to [v2.12.0](https://github.com/prometheus/prometheus/releases) or newer, since previous versions may have issues with `remote_write`. -Take a look also at [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md), -which can be used as faster and less resource-hungry alternative to Prometheus in certain cases. +Take a look also at [vmagent](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmagent/README.md) +and [vmalert](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/app/vmalert/README.md), +which can be used as faster and less resource-hungry alternative to Prometheus. ## Grafana setup