Performance
Comparing Performance and Resource Usage: Grafana Agent vs. Prometheus Agent Mode vs. VictoriaMetrics vmagent
We compared the performance and resource usage of Grafana Agent, Prometheus Agent Mode, and VictoriaMetrics vmagent to help readers make informed decisions when choosing an agent for their monitoring needs.
How to reduce expenses on monitoring: Swapping in VictoriaMetrics for Prometheus
This blog post is the first in the series of the blog posts based on the talk about ‘How to reduce expenses on monitoring’, stackconf 2023. It is about open-source instruments and techniques from theVictoriaMetrics ecosystem for improving cost-efficiency of monitoring.
Performance optimization techniques in time series databases: sync.Pool for CPU-bound operations
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.
Performance optimization techniques in time series databases: Limiting concurrency
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.
Performance optimization techniques in time series databases: function caching
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.
Performance optimization techniques in time series databases: strings interning
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.
Save network costs with VictoriaMetrics remote write protocol
Save network bandwidth costs when transferring data to VictoriaMetrics starting from v1.88
Monitoring benchmark: how to generate 100 million samples/s of production-like data
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.
Cardinality explorer
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.
Grafana Mimir and VictoriaMetrics: performance tests
Benchmarking VictoriaMetrics and Grafana Mimir on the same hardware