docs/CaseStudies.md: update Grammarly case study with the newly published article https://www.grammarly.com/blog/engineering/monitoring-with-victoriametrics/

Follow-up c0246b2e17

docs/CaseStudies.md

@@ -336,36 +336,7 @@ Numbers:
 
 [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
+See [this blogpost on how Grammarly reduces costs and maintenance burden for their observability solution by 10x after switching to VistoriaMetrics](https://www.grammarly.com/blog/engineering/monitoring-with-victoriametrics/).
 
 ## Groove X