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Fred Navruzov
61916650ca
## Motivation Reduce the learning curve for VictoriaMetrics Anomaly Detection, especially for engineers without an ML background. Give readers clearer entry points and a practical path from the behavior of their metrics to a model, a playground example, and a configuration they can adapt. ## Summary Add **Choose a model for your metrics**, organized around three questions: has one metric changed, have related signals changed together, or is one entity different from its peers? ## Solution Use concise explanations and illustrations to introduce each comparison, then provide six expandable recipes covering Online Z-score, Online MAD, Online Seasonal Quantile, Temporal Envelope, multivariate Temporal Envelope, and Peer Outlier. Each recipe includes when to use it, alternatives, a complete reader/model/scheduler example, a reproducible playground state, expected results, and tuning hints. ## Changes - Add the guide and three chart illustrations. Include steady CPU, latency spikes and a level change, seasonal plateaus, evolving traffic, job mix versus CPU, and an unusual replica among changing peers. - Compare the multivariate recipe with independent envelopes, CPU per total job rate, and a known-cost residual rule. Explain when the simpler rule is enough. - Link the guide from the main page, Quickstart, FAQ, model overview, model-type introductions, UI playgrounds, and guides index. Place model selection before alerting setup. - Add green tips at the relevant entry points and matching descriptions in the guides index. Move **Tune a model** after the UI example workflow and link it from model configuration. - Render UI availability badges as HTML shortcodes to preserve headings and anchors in the current Hugo build. ## Validation - PASS: full local vmdocs build with Hugo 0.166.0, 452 pages. - PASS: all six recipe schemas, production periodic schedulers, one-fit historical replays, and shared URL settings. - PASS: deterministic public query/API checks. The new three-channel recipe flags 5/6 incident observations with no healthy flags. Standard independent envelopes and CPU/total-job rate flag none. The known-cost residual flags 6/6, as documented. - PASS: public UI restoration and execution for the new multivariate recipe and ratio baseline. Desktop and 390-pixel mobile rendering checked. - PASS: 44 guide destinations/anchors, all six incoming page links, and whitespace checks. The focused native Linkinator crawl of the new guide also passes, including image and fragment checks. - Full-site Linkinator crawl: 14 findings across 11 URLs outside the guide's outgoing links, including existing Helm/operator assets, local-service example URLs, and a malformed changelog URL. These are separate from the passing guide link check. - Backend/frontend runtime suites were not run because this PR changes documentation only. ## Diff size Full PR against VictoriaMetrics master at `3fec2f72414d00d1acda807c8818d7af90cc966d`. | Area | Core | Else/tests | | --- | --- | --- | | Backend | +0 / -0 | +0 / -0 | | Frontend | +0 / -0 | +0 / -0 | | Repository else | +0 / -0 | +1064 / -52 | | Total | +0 / -0 | +1064 / -52 | Net text change: +1012 lines across nine Markdown files. Three WebP assets total 179,236 bytes. ## Changelog [external] Documentation only. No runtime behavior or release changelog change. ## Caveats Playground examples use fixed historical dates and require network access. Their results illustrate the selected data and settings rather than guaranteeing detection quality for other workloads.
VictoriaMetrics
VictoriaMetrics is a fast, cost-effective, and scalable solution for monitoring and managing time series data. It delivers high performance and reliability, making it an ideal choice for businesses of all sizes.
Here are some resources and information about VictoriaMetrics:
- Case studies: Grammarly, Roblox, Wix, Spotify,....
- Available: Binary releases, Docker images on Docker Hub and Quay, Source code.
- Deployment types: Single-node version and Cluster version under Apache License 2.0.
- Getting started: Read key concepts and follow the quick start guide.
- Community: Slack (join via Slack Inviter), X (Twitter), YouTube. See full list here.
- Changelog: Project evolves fast - check the CHANGELOG, and How to upgrade.
- Enterprise support: Contact us for commercial support with additional enterprise features.
- Enterprise releases: Enterprise and long-term support releases (LTS) are publicly available and can be evaluated for free using a free trial license.
- Security: we achieved security certifications for Database Software Development and Software-Based Monitoring Services.
Yes, we open-source both the single-node VictoriaMetrics and the cluster version.
Prominent features
VictoriaMetrics is optimized for timeseries data, even when old time series are constantly replaced by new ones at a high rate, it offers a lot of features:
- Long-term storage for Prometheus or as a drop-in replacement for Prometheus and Graphite in Grafana.
- Powerful stream aggregation: Can be used as a StatsD alternative.
- Ideal for big data: Works well with large amounts of time series data from APM, Kubernetes, IoT sensors, connected cars, industrial telemetry, financial data and various Enterprise workloads.
- Query language: Supports both PromQL and the more performant MetricsQL.
- Easy to setup: No dependencies, single small binary, configuration through command-line flags, but the default is also fine-tuned; backup and restore with instant snapshots.
- Global query view: Multiple Prometheus instances or any other data sources may ingest data into VictoriaMetrics and be queried via a single query.
- Various Protocols: Support metric scraping, ingestion and backfilling in various protocols.
- Prometheus exporters, Prometheus remote write API, Prometheus exposition format.
- InfluxDB line protocol over HTTP, TCP and UDP.
- Graphite plaintext protocol with tags.
- OpenTSDB put message.
- HTTP OpenTSDB /api/put requests.
- JSON line format.
- Arbitrary CSV data.
- Native binary format.
- DataDog agent or DogStatsD.
- NewRelic infrastructure agent.
- OpenTelemetry metrics format.
- NFS-based storages: Supports storing data on NFS-based storages such as Amazon EFS, Google Filestore.
- And many other features such as metrics relabeling, cardinality limiter, etc.
Enterprise version
In addition, the Enterprise version includes extra features:
- Anomaly detection: Automation and simplification of your alerting rules, covering complex anomalies found in metrics data.
- Backup automation: Automates regular backup procedures.
- Multiple retentions: Reducing storage costs by specifying different retentions for different datasets.
- Downsampling: Reducing storage costs and increasing performance for queries over historical data.
- Stable releases with long-term support lines (LTS).
- Comprehensive support: First-class consulting, feature requests and technical support provided by the core VictoriaMetrics dev team.
- Many other features, which you can read about on the Enterprise page.
Contact us if you need enterprise support for VictoriaMetrics. Or you can request a free trial license here, downloaded Enterprise binaries are available at Github Releases.
We strictly apply security measures in everything we do. VictoriaMetrics has achieved security certifications for Database Software Development and Software-Based Monitoring Services. See Security page for more details.
Benchmarks
Some good benchmarks VictoriaMetrics achieved:
- Minimal memory footprint: handling millions of unique timeseries with 10x less RAM than InfluxDB, up to 7x less RAM than Prometheus, Thanos or Cortex.
- Highly scalable and performant for data ingestion and querying, 20x outperforms InfluxDB and TimescaleDB.
- High data compression: 70x more data points may be stored into limited storage than TimescaleDB, 7x less storage space is required than Prometheus, Thanos or Cortex.
- Reducing storage costs: 10x more effective than Graphite according to the Grammarly case study.
- A single-node VictoriaMetrics can replace medium-sized clusters built with competing solutions such as Thanos, M3DB, Cortex, InfluxDB or TimescaleDB. See VictoriaMetrics vs Thanos, Measuring vertical scalability, Remote write storage wars - PromCon 2019.
- Optimized for storage: Works well with high-latency IO and low IOPS (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc.).
Community and contributions
Feel free to ask any questions regarding VictoriaMetrics:
If you like VictoriaMetrics and want to contribute, then please read these docs.
VictoriaMetrics Logo
The provided ZIP file contains three folders with different logo orientations. Each folder includes the following file types:
- JPEG: Preview files
- PNG: Preview files with transparent background
- AI: Adobe Illustrator files
VictoriaMetrics Logo Usage Guidelines
Font
- Font Used: Lato Black
- Download here: Lato Font
Color Palette
Logo Usage Rules
- Only use the Lato Black font as specified.
- Maintain sufficient clear space around the logo for visibility.
- Do not modify the spacing, alignment, or positioning of design elements.
- You may resize the logo as needed, but ensure all proportions remain intact.
Thank you for your cooperation!
Join the team
We're hiring engineers who share the same development goals as we do: practical improvements, simple solutions, and happy users.
Already contributing to VictoriaMetrics? We'd be especially happy to hear from you.