docs/CaseStudies.md: add a case study for Grammarly

README.md

@@ -36,6 +36,7 @@ Case studies:
 * [COLOPL](https://docs.victoriametrics.com/CaseStudies.html#colopl)
 * [Dreamteam](https://docs.victoriametrics.com/CaseStudies.html#dreamteam)
 * [German Research Center for Artificial Intelligence](https://docs.victoriametrics.com/CaseStudies.html#german-research-center-for-artificial-intelligence)
+* [Grammarly](https://docs.victoriametrics.com/CaseStudies.html#grammarly)
 * [Groove X](https://docs.victoriametrics.com/CaseStudies.html#groove-x)
 * [Idealo.de](https://docs.victoriametrics.com/CaseStudies.html#idealode)
 * [MHI Vestas Offshore Wind](https://docs.victoriametrics.com/CaseStudies.html#mhi-vestas-offshore-wind)

docs/CaseStudies.md

@@ -15,6 +15,7 @@ where you can chat with VictoriaMetrics users to get additional references, revi
 * [COLOPL](#colopl)
 * [Dreamteam](#dreamteam)
 * [German Research Center for Artificial Intelligence](#german-research-center-for-artificial-intelligence)
+* [Grammarly](#grammarly)
 * [Groove X](#groove-x)
 * [Idealo.de](#idealode)
 * [MHI Vestas Offshore Wind](#mhi-vestas-offshore-wind)
@@ -259,6 +260,42 @@ Numbers:
 - RAM usage: 2.8 GB
 
 
+## Grammarly
+
+[Grammarly](https://www.grammarly.com/) provides digital writing assistant that helps 30 million people and 30 thousand teams write more clearly and effectively every day. In building a product that scales across multiple platforms and devices, Grammarly works to empower users whenever and wherever they communicate.
+
+> Maintenance and scaling for our previous on-premise monitoring system was hard and required a lot of effort from our side. The previous system was not optimized for storing frequently changing metrics (moderate [churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate) was a concern). The costs of the previous solution were not optimal.
+
+> We evaluated various cloud-based and on-premise monitoring solutions: Sumo Logic, DataDog, SignalFX, Amazon CloudWatch, Prometheus, M3DB, Thanos, Graphite, etc. PoC results were sufficient for us to move forward with VictoriaMetrics due to the following reasons:
+
+- High performance
+- Support for Graphite and OpenMetrics data ingestion types
+- Good documentation and easy bootstrap
+- Responsiveness of VictoriaMetrics support team during research and afterward
+
+> Switching from our previous on-premise monitoring system to VictoriaMetrics allowed reducing infrastructure costs by an order of magnitude while improving DevOps experience and developer experience.
+
+Numbers:
+
+- [Cluster version](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html) of VictoriaMetrics
+- Active time series: 35M
+- Ingestion rate: 950K new samples per second
+- Total number of datapoints: 44 trillions
+- Churn rate: 27M new time series per day
+- Data size on disk: 23 TB
+- Index size on disk: 700 GB
+- The average datapoint size on disk: 0.5 bytes
+- Query rate:
+  - `/api/v1/query_range`: 350 queries per second
+  - `/api/v1/query`: 24 queries per second
+- Query duration:
+  - 99th percentile: 500 milliseconds
+  - 90th percentile: 70 milliseconds
+  - median: 2 milliseconds
+- CPU usage: 12 CPU cores
+- RAM usage: 250 GB
+
+
 ## Groove X
 
 [Groove X](https://groove-x.com/en/) designs and produces robotics solutions. Its mission is to bring out humanity’s full potential through robotics.

docs/README.md

@@ -36,6 +36,7 @@ Case studies:
 * [COLOPL](https://docs.victoriametrics.com/CaseStudies.html#colopl)
 * [Dreamteam](https://docs.victoriametrics.com/CaseStudies.html#dreamteam)
 * [German Research Center for Artificial Intelligence](https://docs.victoriametrics.com/CaseStudies.html#german-research-center-for-artificial-intelligence)
+* [Grammarly](https://docs.victoriametrics.com/CaseStudies.html#grammarly)
 * [Groove X](https://docs.victoriametrics.com/CaseStudies.html#groove-x)
 * [Idealo.de](https://docs.victoriametrics.com/CaseStudies.html#idealode)
 * [MHI Vestas Offshore Wind](https://docs.victoriametrics.com/CaseStudies.html#mhi-vestas-offshore-wind)
@@ -517,7 +518,7 @@ and it is easier to use when migrating from Graphite to VictoriaMetrics.
 
 [VictoriaMetrics Enterprise](https://victoriametrics.com/enterprise.html) supports [Graphite Render API](https://graphite.readthedocs.io/en/stable/render_api.html) subset
 at `/render` endpoint, which is used by [Graphite datasource in Grafana](https://grafana.com/docs/grafana/latest/datasources/graphite/).
-It supports `Storage-Step` http request header, which must be set to a step between data points stored in VictoriaMetrics when configuring Graphite datasource in Grafana.
+When configuring Graphite datasource in Grafana, the `Storage-Step` http request header must be set to a step between Graphite data points stored in VictoriaMetrics. For example, `Storage-Step: 10s` would mean 10 seconds distance between Graphite datapoints stored in VictoriaMetrics.
 Enterprise binaries can be downloaded and evaluated for free from [the releases page](https://github.com/VictoriaMetrics/VictoriaMetrics/releases).
 
 

docs/Single-server-VictoriaMetrics.md

@@ -40,6 +40,7 @@ Case studies:
 * [COLOPL](https://docs.victoriametrics.com/CaseStudies.html#colopl)
 * [Dreamteam](https://docs.victoriametrics.com/CaseStudies.html#dreamteam)
 * [German Research Center for Artificial Intelligence](https://docs.victoriametrics.com/CaseStudies.html#german-research-center-for-artificial-intelligence)
+* [Grammarly](https://docs.victoriametrics.com/CaseStudies.html#grammarly)
 * [Groove X](https://docs.victoriametrics.com/CaseStudies.html#groove-x)
 * [Idealo.de](https://docs.victoriametrics.com/CaseStudies.html#idealode)
 * [MHI Vestas Offshore Wind](https://docs.victoriametrics.com/CaseStudies.html#mhi-vestas-offshore-wind)