diff --git a/docs/CaseStudies.md b/docs/CaseStudies.md index 1d46b05f0..3ab0d3279 100644 --- a/docs/CaseStudies.md +++ b/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