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.
Customer Stories
- 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: Customer Stories
How Airbnb Built a High-Volume Metrics Pipeline with OpenTelemetry and vmagent
Learn how Airbnb rebuilt its observability pipeline with OpenTelemetry and vmagent to handle over 100 million samples per second, reduce cost by 10x, and simplify high-scale metrics aggregation.
How a US Software Provider Improved Traffic Alerting with VictoriaMetrics Anomaly Detection
VictoriaMetrics Anomaly Detection enables reliable alerting for highly variable, multi-domain traffic without relying on static thresholds. In this case study, fine-tuned models, backtesting, and clear visualization helped reduce alert noise, improve confidence in anomaly detection, and lower operational overhead.
Spotify’s performance & control across large monitoring environments with VictoriaMetrics
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.
How DreamHost Slashed Memory Usage by 80% and Scaled to 76 Million Time Series
VictoriaMetrics delivers a complete open-source observability stack, combining a highly scalable time series database with a powerful log management system. This streamlined, single-binary solution simplifies deployment while providing fast, cost-effective monitoring and logging at any scale.