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docs/CaseStudies.md: add Zerodha case based on monitoring K8s with VictoriaMetrics slides at https://docs.google.com/presentation/d/1g7yUyVEaAp4tPuRy-MZbPXKqJ1z78_5VKuV841aQfsg/edit

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* [Billy: how VictoriaMetrics deals with more than 500 billion rows](https://medium.com/@valyala/billy-how-victoriametrics-deals-with-more-than-500-billion-rows-e82ff8f725da)
## Third-party articles
## Third-party articles and slides
* [Better Prometheus rate() function with VictoriaMetrics](https://www.percona.com/blog/2020/02/28/better-prometheus-rate-function-with-victoriametrics/)
* [Infrastructure monitoring with Prometheus at Zerodha](https://zerodha.tech/blog/infra-monitoring-at-zerodha/)
* [Monitoring K8S with VictoriaMetrics](https://docs.google.com/presentation/d/1g7yUyVEaAp4tPuRy-MZbPXKqJ1z78_5VKuV841aQfsg/edit)
* [CMS monitoring R&D: Real-time monitoring and alerts](https://indico.cern.ch/event/877333/contributions/3696707/attachments/1972189/3281133/CMS_mon_RD_for_opInt.pdf)
* [Disk usage: VictoriaMetrics vs Prometheus](https://stas.starikevich.com/posts/disk-usage-for-vm-versus-prometheus/)
* [Benchmarking time series workloads on Apache Kudu using TSBS](https://blog.cloudera.com/benchmarking-time-series-workloads-on-apache-kudu-using-tsbs/)

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from `Large-scale, super-load system monitoring platform built with VictoriaMetrics` talk at [Prometheus Meetup Tokyo #3](https://prometheus.connpass.com/event/157721/).
## Zerodha
[Zerodha](https://zerodha.com/) is India's largest stock broker. Monitoring team at Zerodha faced with the following requirements:
* Multiple K8s clusters to monitor
* Consistent monitoring infra for each cluster across the fleet
* Ability to handle billions of timeseries events at any point of time
* Easier to operate and cost effective
Thanos, Cortex and VictoriaMetrics were evaluated as a long-term storage for Prometheus. VictoriaMetrics has been selected due to the following reasons:
* Blazing fast benchmarks for a single node setup.
* Single binary mode. Easy to scale vertically, very less operational headache.
* Considerable improvements on creating Histograms.
* [MetricsQL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/MetricsQL) gives us the ability to extend PromQL with more aggregation operators.
* API is compatible with Prometheus, almost all standard PromQL queries just work out of the box.
* Handles storage well, with periodic compaction. Makes it easy to take snapshots.
See [Monitoring K8S with VictoriaMetrics](https://docs.google.com/presentation/d/1g7yUyVEaAp4tPuRy-MZbPXKqJ1z78_5VKuV841aQfsg/edit) slides and
[Infrastructure monitoring with Prometheus at Zerodha](https://zerodha.tech/blog/infra-monitoring-at-zerodha/) blog post for more details.
## Wix.com
[Wix.com](https://en.wikipedia.org/wiki/Wix.com) is the leading web development platform.

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* [Adidas](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#adidas)
* [CERN](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#cern)
* [COLOPL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#colopl)
* [Zerodha](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#zerodha)
* [Wix.com](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#wixcom)
* [Wedos.com](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#wedoscom)
* [Synthesio](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/CaseStudies#synthesio)