VictoriaMetrics provides a rich set of public playgrounds that allow you to explore the full observability stack - metrics, logs, traces - and even query migration tools without installing or configuring anything locally. These playgrounds are backed by real VictoriaMetrics components and real data, making them ideal for:
Learning VictoriaMetrics query languages
Trying dashboards and queries interactively
Validating migration paths
Demonstrating features in talks or workshops
Experimenting with AI-driven observability via MCP
In this post, we’ll walk through each available playground, explain what it does and link to the relevant GitHub repositories behind it.
VictoriaMetrics Playground (VMUI)
🔗 https://play.victoriametrics.com/
This is the primary playground for VictoriaMetrics metrics, powered by VMUI and backed by a VictoriaMetrics cluster installation. It is available for testing the query engine, relabeling debugger, other tools and pages provided by VMUI.
This playground is the best starting point for understanding how VictoriaMetrics stores and queries metrics at scale.
GitHub repository:
https://github.com/VictoriaMetrics/VictoriaMetrics
Grafana VictoriaMetrics Playground
🔗 https://play-grafana.victoriametrics.com/
This playground provides a hosted Grafana instance preconfigured with:
VictoriaMetrics as a metrics data source
VictoriaLogs as a logs data source
Here you can:
Explore real dashboards built on top of VictoriaMetrics
See how MetricsQL and LogsQL are used in Grafana panels
Learn dashboard design and visualization best practices
It’s particularly useful if you already use Grafana and want to see how VictoriaMetrics integrates into existing workflows.
Relevant repositories:
VictoriaMetrics Grafana datasource: https://github.com/VictoriaMetrics/victoriametrics-datasource
VictoriaLogs Grafana datasource: https://github.com/VictoriaMetrics/victorialogs-datasource
VictoriaLogs Playground (LogsQL)
🔗 https://play-vmlogs.victoriametrics.com/
This playground focuses on VictoriaLogs and it is available for testing the query engine on demo logs set.
The playground demonstrates how VictoriaLogs handles high-volume log data with predictable performance and low operational overhead.
GitHub repository:
https://github.com/VictoriaMetrics/VictoriaLogs
LogQL → LogsQL Playground (Migration Assistant)
🔗 https://play-logql.victoriametrics.com/
For teams migrating from Grafana Loki, this playground provides a LogQL to LogsQL, the VictoriaLogs query language, translation tool, which automatically converts Loki queries to VictoriaLogs queries.
This significantly reduces friction when adopting VictoriaLogs in environments already using Loki.
GitHub repository:
https://github.com/VictoriaMetrics-Community/logql-to-logsql
Documentation:
https://docs.victoriametrics.com/victorialogs/logql-to-logsql/
VictoriaTraces Playground
🔗 https://play-vtraces.victoriametrics.com/
This playground showcases VictoriaTraces, the VictoriaMetrics backend for distributed tracing and it is available for testing the query engine on demo traces set.
GitHub repository:
https://github.com/VictoriaMetrics/VictoriaTraces
VMAnomaly Playground (Anomaly Detection)
🔗 https://play-vmanomaly.victoriametrics.com/metrics/vmui/
The VMAnomaly playground demonstrates automatic anomaly detection on time-series data using VictoriaMetrics. It allows you to:
Explore metrics enriched with an anomaly_score
Visualize anomalies directly in VMUI
Understand how anomaly detection integrates with MetricsQL
Learn how anomaly scores can be used for alerting (for example with vmalert)
VMAnomaly continuously analyzes metric behavior and produces anomaly scores that behave like any other time series in VictoriaMetrics.
Distribution & setup:
VMAnomaly container: https://hub.docker.com/r/victoriametrics/vmanomaly
Helm charts (including anomaly setups): https://github.com/VictoriaMetrics/helm-charts
Bonus point: VictoriaMetrics MCP server
If you are a fan of using MCP servers then you should definitely try the official VictoriaMetrics MCP Server, which enables AI-driven interaction with observability data. This MCP server allows you to use almost all read-only APIs of VictoriaMetrics, basically all the functions available in VMUI:
- Querying metrics and exploring data (even drawing graphs if your client supports it)
- Listing and exporting available metrics, labels, labels values and entire series
- Analyzing and testing your alerting and recording rules and alerts
- Showing parameters of your VictoriaMetrics instance
- Exploring cardinality of your data and metrics usage statistics
- Analyzing, tracing, prettifying and explaining your queries
- Debugging your relabeling rules, downsampling and retention policy configurations
- Integration with VictoriaMetrics Cloud
This makes it possible for MCP-compatible tools (such as Cursor, Claude Desktop, or VS Code integrations) to query and reason about observability data conversationally.
GitHub repository:
https://github.com/VictoriaMetrics-Community/mcp-victoriametrics
Video how to use VictoriaMetrics MCP server: https://www.youtube.com/watch?v=1k7xgbRi1k0
Run Your Own Local Playgrounds
In addition to these hosted playgrounds, VictoriaMetrics provides Docker and Helm-based resources you can run locally and start playing with the ecosystem:
https://hub.docker.com/u/victoriametrics
https://github.com/VictoriaMetrics/helm-charts
https://docs.victoriametrics.com/victoriametrics/quick-start/
Let me know which one was your favorite playground or if you have any feedback for improvement, ping me a comment here or you can find me on LinkedIn or GitHub.
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