Case Study: Dig Security

“Amazing speed, easy to use, easy to set-up, cost effective, highly recommended!”

Industry:

Cloud Security

Location:

Israel

Dig Security is a cloud data security startup of 50+ employees that provides real-time visibility, control, and protection of data assets.

Main Benefits of Using VictoriaMetrics

Cost-effective: Savings of $5K / month

Storage efficiency

Support with a great community

Easy to use & maintain
The ability to handle billions of time series events at any point of time
Multiple K8s clusters to monitor

Consistent monitoring infrastructure for each cluster across multiple regions and clouds
Secure communication and data storage
Easy Retention

Challenge

We started with a Prometheus server on EKS. That worked until it didn't.

We then spent time scaling it, maintaining it, throwing more $ at it, until we stumbled across VictoriaMetrics.

What we looked for:

Reducing costs by not using a managed solution of one of the big clouds
Support HA / High Availability & fast recovery
No downtime
Having our main Prometheus using too much RAM and causing too many restarts

Solution

With VictoriaMetrics we found the following solution:

The API is compatible with Prometheus & all standard PromQL queries work well out of the box
Handles storage well
Available to use in Grafana easily
Single & small executable
Easy & fast backups
Better benchmarks than all the competitors
Open source & maintained with good community

Why VictoriaMetrics Was Chosen Over Other Solutions

Blazing Fast

Easy to Set Up, Maintain & Upgrade

Works Quickly Out-of-the-Box

Usage in High Scale for HA
Fast Performance
Highly Efficient
Cost effective, Highly recommended!

Can serve us in the future in even bigger scales
It’s seamless and doesn't cause override-complications for our Infrastructure Team

Next up: Collect more and more metrics, we will grow lots more still to-do

Technical Stats

Median memory usage during the last 24h

sum(median_over_time(process_resident_memory_bytes[24h]))

11810058240

The average number of cpu cores used during the last 24h

sum(rate(process_cpu_seconds_total[24h]))

The maximum number of active time series during the last 24 hours

sum(max_over_time(vm_cache_entries{type="storage/hour_metric_ids"}[24h]))

105385942

Daily time series churn rate

sum(increase(vm_new_timeseries_created_total[24h]))

21387174

The average ingestion rate over the last 24h

sum(rate(vm_rows_inserted_total[24h]))

153659

The total number of datapoints

sum(vm_rows{type=~"storage/.+"})

226842200313

The total number of entries in inverted index

sum(vm_rows{type="indexdb"}))

18795635692

Data size on disk

sum(vm_data_size_bytes{type=~"storage/.+"})

290057995509

Index size on disk:

sum(vm_data_size_bytes{type="indexdb"})

686073579091

The average datapoint size on disk

sum(vm_data_size_bytes) / sum(vm_rows{type=~"storage/.+"})

3.9

The average range query rate over the last 24h

sum(rate(vm_http_requests_total{path=~".*/api/v1/query_range"}[24h]))

1.45