Spotify needed to replace its legacy in-house time series database to overcome stability and performance limitations, which would bring about query delays and timeouts. The Spotify observability team chose VictoriaMetrics to support efficient metric ingestion, querying, and alerting at scale.
VictoriaMetrics Enterprise is now available as a free trial - start yours today! Read the announcement for details.
This blog post series centers on Anomaly Detection (AD) and Root Cause Analysis (RCA) within time-series data. In Chapter 3, we delve into a variety of advanced anomaly detection techniques, encompassing supervised, semi-supervised, and unsupervised approaches, each tailored to different data scenarios and challenges in time-series analysis.
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.
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.
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 this momentum release to learn more about VictoriaMetrics achieving 320% growth in 2023 & hitting 268 million downloads of our open source time series database and monitoring solution.
This blog post series centers on Anomaly Detection (AD) and Root Cause Analysis (RCA) within time-series data. In this second part, we explore the distinct anomaly types inherent to time-series and offer insights on how to tackle them effectively.
This blog post series focuses on Anomaly Detection (AD) and Root Cause Analysis (RCA) within the context of time-series data. The inaugural chapter lays the groundwork by introducing the role of AD in end-to-end observability systems, discussing domain-specific terminology, and addressing the challenges inherent to the time-series nature of the data.
Overview of LTS releases, deprecation of 1.79, review of the most recent LTS 1.93
Read how to set up Kubernetes costs monitoring with VictoriaMetrics.