From the article
VictoriaMetrics Observability Blog
Author
- Adam Yates
- Aditya Kulkarni
- Adrian Bridgwater
- Agustín Gallego
- Alex Woodie
- Alexander Marshalov
- Aliaksandr Valialkin
- Aman Agarwal
- Antony Savvas
- Artem Navoiev
- Bill Tanner
- Cer6erus
- Claudio Masolo
- David Marshall
- Denys Holius
- Derek Foster
- Diana Todea
- Dima Lazerka
- Dmytro Kozlov
- Emily Foster
- Fintech Herald
- Fred Navruzov
- Gary Flood
- Gonzalo García Labat
- Ivan Yatskevich
- Jaime Hampton
- Jan Sokol
- Jason Bloomberg
- Jason English
- Jean-Jerome Schmidt-Soisson
- Jesús Espino
- Joab Jackson
- John Seekins
- Jose Gomez-Selles
- Julien Menan
- Karan Virdi
- Laveesh Kocher
- Leigh McGowran
- Lindsay Clark
- Marc Sherwood
- Mark Baker
- Martijn Van Best
- Martin Veitch
- Mathias Palmersheim
- Michelle Sebek
- Nick Gibson
- Nikolay Khramchikhin
- Pablo Fernandez
- Phuong Le
- Rafal Szypulka
- Renato Losio
- Richard Speed
- Roman Khavronenko
- Vadim Alekseev
- Vadim Rutkovsky
- Yurii Kravets
- Zakhar Bessarab
- Zhu Jiekun
No matching authors found.
Category
- Benchmark
- Community
- Company News
- Customer Stories
- Developer Experience
- Distributed Tracing
- Events
- Go
- Go @ VictoriaMetrics
- High Cardinality
- Kubernetes
- Monitoring
- Observability
- Open Source Tech
- OpenTelemetry
- OTLP
- Performance
- PostgreSQL
- Product News
- Tech Talk
- Time Series Database
- VictoriaLogs
- VictoriaMetrics
- VictoriaTraces
No matching categories found.
Filter: Time Series
Blog posts
The Life of a Metric
Follow a single metric through its whole life inside VictoriaMetrics: born as a counter in your process, exported over the wire, given an identity and an inverted-index entry, written through an LSM tree, compressed into columnar blocks on disk, read back by a rate() query, downsampled as it ages, and finally deleted when retention runs out.
VictoriaMetrics Components: Getting Started
VictoriaMetrics is a fast, scalable monitoring system made of modular components like vminsert, vmstorage, and vmselect. It supports both single-node and clustered setups, along with tools for backup, restore, alerting, access control, and data migration. Data can be ingested, stored, queried, backed up, and restored with high performance and minimal resource use.
Prometheus Alerting 101: Rules, Recording Rules, and Alertmanager
Recording rules can transform complex PromQL queries into pre-computed metrics, eliminating repeated calculation overhead. When organized in groups, these alerting and recording rules can be precisely scheduled to run at specific times like 01:30, 02:30, and even execute in parallel for maximum efficiency.
Inside vmselect: The Query Processing Engine of VictoriaMetrics
The article explains vmselect’s core functionalities: concurrent request processing, query parsing and validation, data fetching and merging from vmstorage nodes, and memory-efficient result caching.
How vmstorage Handles Query Requests From vmselect
When vmselect asks vmstorage for data, there’s actually quite a bit happening behind the scenes. This article breaks down the process of how vmstorage locates and retrieves your metrics, from finding the right TSIDs to sending back the actual data points.
How vmstorage's IndexDB Works
IndexDB acts as vmstorage’s memory - it remembers which numbers (TSIDs) belong to which metrics, making sure your queries get answered fast. This article walks through how this system works, from the way it organizes data to how it keeps track of millions of timeseries.
How vmstorage Processes Data: Retention, Merging, Deduplication,...
vmstorage takes data from vminsert through a concurrency limiter, creates TSIDs for each row, and puts them in memory buffers. Every few seconds, it moves data to storage parts on disk. The system merges parts, removes duplicates, and cleans old data. This turns raw metrics into data users can search.
The Rise of Open Source Time Series Databases
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.
VictoriaMetrics Cloud reduces monitoring costs by 5x
We’re happy to announce VictoriaMetrics Cloud, a hosted monitoring platform and managed service for metrics that allows organizations to monitor and store large amounts of time-series data, without having to run the underlying infrastructure.