The VictoriaMetrics Observability Blog
Read Our Technical & Business Content on Monitoring Solutions & Time Series Databases
Category:

Performance

Performance optimization techniques in time series databases: sync.Pool for CPU-bound operations

by Roman Khavronenko / Aliaksandr Valialkin on Dec 8, 2023

This blog post is the fourth in the series of blog posts based on the talk about ‘Performance optimizations in Go’, GopherCon 2023. It is dedicated to various optimization techniques used in VictoriaMetrics for improving performance and resource usage.

Read

Performance optimization techniques in time series databases: Limiting concurrency

by Roman Khavronenko / Aliaksandr Valialkin on Nov 24, 2023

This blog post is a third in the series of the blog posts based on the talk about ‘Performance optimizations in Go’, GopherCon 2023. It is dedicated to various optimization techniques used in VictoriaMetrics for improving performance and resource usage.

Read

Performance optimization techniques in time series databases: function caching

by Roman Khavronenko / Aliaksandr Valialkin on Nov 17, 2023

This blog post is a second in the series of the blog posts based on the talk about ‘Performance optimizations in Go’, GopherCon 2023. It is dedicated to various optimization techniques used in VictoriaMetrics for improving performance and resource usage.

Read

Performance optimization techniques in time series databases: strings interning

by Roman Khavronenko / Aliaksandr Valialkin on Nov 7, 2023

This blog post is a first in the series of the blog posts based on the talk about ‘Performance optimizations in Go’, GopherCon 2023. It is dedicated to various optimization techniques used in VictoriaMetrics for improving performance and resource usage.

Read

Save network costs with VictoriaMetrics remote write protocol

by Aliaksandr Valialkin on Mar 8, 2023

Save network bandwidth costs when transferring data to VictoriaMetrics starting from v1.88

Read

Monitoring benchmark: how to generate 100 million samples/s of production-like data

by Roman Khavronenko on Jan 16, 2023

One of the latest benchmarks we made was ‘VictoriaMetrics: scaling to 100 million metrics per second’. While the fact of such scale for VictoriaMetrics is noteworthy on its own, the benchmark tool used to generate that load is usually overlooked. In this blog post I’ll explain in more details the challenge of running such benchmarks.

Read

Cardinality explorer

by Dmytro Kozlov on Oct 4, 2022

In monitoring, the term cardinality defines the number of unique time series stored in TSDB. The higher is cardinality, the more resources are usually required for metrics processing and querying. Let’s see how Cardinality explorer can help us here.

Read

Grafana Mimir and VictoriaMetrics: performance tests

by Roman Khavronenko / Nikolay Khramchikhin on Sep 9, 2022

Benchmarking VictoriaMetrics and Grafana Mimir on the same hardware

Read

How to Choose a Scalable Open Source Time Series Database: The Cost of Scale

by Jean-Jerome Schmidt-Soisson / Roman Khavronenko on May 16, 2022

When looking for a most scalable open source time series database, what are the criteria to care about? Read this blog to get our recommendations.

Read

Running VictoriaMetrics on ARM-based processors

by Nikolay Khramchikhin on Mar 11, 2022

VictoriaMetrics has new production ready builds for ARM

Read

Watch Your Monitoring SkyRocket With VictoriaMetrics!