The VictoriaMetrics Observability Blog
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Observability

The Rise of Open Source Time Series Databases

by Aliaksandr Valialkin on Sep 11, 2024

Time series databases are essential tools in any software engineer’s toolbelt. Their development has been shaped by user needs and countless open source contributors, leading to the healthy ecosystem of options we see today. In this article, you’ll see how time series databases came about, and why so many are open source.

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Troubleshooting Time Series Databases: Where Did My Metrics Go?

by Zhu Jiekun on Aug 9, 2024

I have already recorded metrics in the application, why can’t I see my metrics on Grafana?

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VictoriaMetrics Anomaly Detection: What's New in H1 2024?

by Fred Navruzov on Jul 17, 2024

Explore the latest improvements in VictoriaMetrics Anomaly Detection (vmanomaly), including presets, new models, enhanced tuning, and better resource management

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Introduction to Managed Monitoring

by Ivan Yatskevich on Jun 12, 2024

Learn about the different types of managed monitoring services available on the market, and why you might consider picking one of them to manage your monitoring infrastructure.

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Anomaly Detection for Time Series Data: Techniques and Models

by Fred Navruzov on Nov 29, 2023

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.

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Anomaly Detection for Time Series Data: Anomaly Types

by Fred Navruzov on Oct 27, 2023

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.

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Anomaly Detection for Time Series Data: An Introduction

by Fred Navruzov on Oct 18, 2023

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.

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Why we generate & collect logs: About the usability & cost of modern logging systems

by Aliaksandr Valialkin on Aug 1, 2023

This blog post looks at what logs are and why they matter, why logs are generated and collected as well as at the costs associated with that. It also provides details on why VictoriaLogs should be considered over similar solutions.

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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.

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