VictoriaMetrics Anomaly Detection
VictoriaMetrics Anomaly Detection is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real time. It does so by utilizing user-configurable machine learning models. In the dynamic and complex world of system monitoring, VictoriaMetrics Anomaly Detection, a part of our Enterprise offering, is a pivotal tool for achieving advanced observability. It empowers SREs and DevOps teams by automating the intricate task of identifying abnormal behavior in time-series data. It goes beyond traditional threshold-based alerting, utilizing machine learning techniques to detect anomalies and minimize false positives, thus reducing alert fatigue. Providing simplified alerting mechanisms atop unified anomaly scores enables teams to spot and address potential issues faster, ensuring system reliability and operational efficiency.
Learn more
VictoriaLogs
VictoriaLogs, an open-source log database from VictoriaMetrics, is designed to be user-friendly. It seamlessly integrates with widely used log collectors and offers a more straightforward setup process than Elasticsearch and Grafana Loki. The robust LogsQL query language provides full-text search capabilities across all log fields, simplifying log management. It scales impressively with CPU, RAM, disk IO, and space, running efficiently on Raspberry Pi and high-end servers. It handles data volumes up to 30 times larger than Elasticsearch and Grafana Loki on the same hardware, making it a powerful choice for various environments. VictoriaLogs supports fast full-text search over high-cardinality log fields like trace_id, user_id, and IP. It works seamlessly with traditional Unix log analysis tools like grep, less, sort, and jq. It also offers multi-tenancy support, accommodating diverse needs.
Learn more
VictoriaMetrics
VictoriaMetrics is a fast and scalable open source time series database and monitoring solution. It's designed to be user-friendly, allowing users to build a monitoring platform without scalability issues and with minimal operational burden.
VictoriaMetrics is ideal for solving use cases with large amounts of time series data for IT infrastructure, APM, Kubernetes, IoT sensors, automotive vehicles, industrial telemetry, financial data, and other enterprise-level workloads.
VictoriaMetrics is powered by several components, making it the perfect solution for collecting metrics (both push and pull models), running queries, and generating alerts.
With VictoriaMetrics, you can store millions of data points per second on a single instance or scale to a high-load monitoring system across multiple data centers. Plus, it's designed to store 10x more data using the same compute and storage resources as existing solutions, making it a highly efficient choice.
Learn more
VictoriaMetrics Enterprise
VictoriaMetrics Enterprise is a commercial solution designed by the creators of VictoriaMetrics for complex monitoring and observability setups. It's ideal for organizations with mission-critical, large, or rapidly scaling monitoring environments.
The Enterprise version includes all the features of the community edition plus additional enhancements such as Downsampling Automated Backups / Backup Manager Data Retention per Label/Tenant Multi-Tenant Statistic & Rate Limiting Anomaly Detection. It offers stable releases with long-term support, ensuring critical bug fixes and security patches. Enterprise security compliance and prioritized feature requests are also part of the package.
We help you to reduce storage costs and boost performance for historical data queries. Multiple retentions allow different storage durations for various datasets. Automatic discovery of storage nodes updates the list at insert and vmselect without restarting services.
Learn more