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docs: udpate playground page (#10754)

Browse Source 
This change reverts part of the changes in
https://github.com/VictoriaMetrics/VictoriaMetrics/pull/10686

Motivation: docs added https://github.com/VictoriaMetrics/VictoriaMetrics/pull/10686 in most cases are too verbose, ai-generated and bringing low practical sense.

The improvement goal: remove bloat from the docs and keep them practical and useful.

What it does:
- Completely removes items from the sidebar
- Moves the content of the most important playground pages to the
`/playground/` stub (README.md). Use H2s for each playground.
- Updates and cleans the text.
- Removes the individual children pages in the playground category (keep
only the `/playgrounds/` page/stub and remove the children).
- Removes items as these don't really need much introduction or aren't
playgrounds:
  - log to logsql: a conversion tool
  - sql to logsql: same
- adds Grafana playground section

Links of child pages will become invalid. We don't preserve them as this is pretty new doc (1w on prod) and is unlikely to have already persisted links somewhere.

---------

Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
This commit is contained in:
Pablo (Tomas) Fernandez
2026-04-09 11:08:48 +01:00
committed by GitHub
parent 52f4d0f055
commit cd3d297a3d
29 changed files with 123 additions and 351 deletions
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VictoriaMetrics provides a rich set of public playgrounds that let you explore the full observability stack — metrics, logs, and traces — and even use migration tools without installing or configuring anything locally.
VictoriaMetrics offers public playgrounds where you can try the full observability stack online.
These playgrounds are backed by real VictoriaMetrics components and data, making them ideal for:
Some playgrounds are based on the [OpenTelemetry Astronomy Shop demo](https://github.com/open-telemetry/opentelemetry-demo), a sample microservices application that generates realistic metrics, logs, and traces. Other playgrounds use benchmark workloads such as [prometheus-benchmark](https://github.com/VictoriaMetrics/prometheus-benchmark) to demonstrate ingestion and query performance for Prometheus-compatible systems.
- Learning VictoriaMetrics query languages
- Trying dashboards and queries interactively
- Validating migration paths
These playgrounds are ideal for:
- Learning [MetricsQL](https://docs.victoriametrics.com/victoriametrics/metricsql/) and [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/)
- Trying out dashboards and queries interactively
- Demonstrating features in talks or workshops
In this section, we'll walk through each available playground, explain what it does, and link to the relevant GitHub repositories.
In the following sections, we'll walk through each playground, explain its purpose, and link to the corresponding GitHub repositories.
## Docker Compose Demo
## VictoriaMetrics Playground
A fast, cost-effective, and scalable monitoring solution and time series database designed for collecting, storing, querying, and alerting on metrics.
- Try it: <https://play.victoriametrics.com/>
- Documentation: <https://docs.victoriametrics.com/victoriametrics/>
The playground is represented by [cluster version of VictoriaMetrics](https://docs.victoriametrics.com/victoriametrics/cluster-victoriametrics/).
It collects metrics from [OpenTelemetry Astronomy Shop demo](https://github.com/open-telemetry/opentelemetry-demo) and
various services in our Kubernetes playground namespace.
VictoriaMetrics web UI is represented via [VMUI](https://docs.victoriametrics.com/victoriametrics/single-server-victoriametrics/#vmui).
It allows querying metrics, plotting graphs, exploring cardinality, viewing alerting and recording rules, debugging relabeling rules, etc.
The best place to get started is with the [Cardinality Explorer](https://play.victoriametrics.com/select/0/prometheus/graph/#/cardinality) page, found under **Explore** > **Explore Cardinality**.
This view shows what's stored in the database for the specified day, lets you browse top metrics and labels in the dataset, and lets you drill down into them without writing a single line of MetricsQL.
![Screenshot of VMUI](vmui-cardinality-explorer.webp)
<figcaption style="text-align: center; font-style: italic;">Cardinality Explorer in VictoriaMetrics</figcaption>
Try plotting graphs on the **Query** tab - [`sum(rate(vm_http_requests_total[5m])) by(path) > 0`](https://play.victoriametrics.com/select/0/prometheus/graph/#/?g0.range_input=30m&g0.relative_time=last_30_minutes&g0.tab=0&g0.expr=sum%28rate%28vm_http_requests_total%5B5m%5D%29%29+by%28path%29+%3E+0):
![Screenshot of VMUI](vmui-rate-http-requests-total.webp)
> VictoriaMetrics is also represented as a datasource in [Grafana playground](#grafana-playground).
## VictoriaLogs Playground
High-performance, lightweight, zero-config, schema-free database for logs that is easy to use and scales both vertically and horizontally,
from very small setups to large-scale deployments handling terabytes per day.
- Try it: <https://play-vmlogs.victoriametrics.com/>
- Documentation: <https://docs.victoriametrics.com/victorialogs/>
The playground is represented by [cluster version of VictoriaLogs](https://docs.victoriametrics.com/victorialogs/cluster/).
It stores logs from [OpenTelemetry Astronomy Shop demo](https://github.com/open-telemetry/opentelemetry-demo) and various
other services that run in our k8s playground namespace.
VictoriaLogs [web UI](https://docs.victoriametrics.com/victorialogs/querying/#web-ui) allows querying log entries, plotting graphs,
exploring stored datasets, live tailing.
To start exploring the data, look at the sidebar. It shows the stream fields available in the dataset,
and clicking any field or value automatically applies a filter, so you can browse the logs before writing your own query.
![Screenshot of VictoriaLogs VMUI](vl-vmui.webp)
On the `Query` tab, click on the `Query examples` button to see examples of the most common search queries to start with.
> VictoriaLogs is also represented as a datasource in [Grafana playground](#grafana-playground).
## VictoriaTraces Playground
VictoriaTraces is a fast and scalable database for traces, built on top of VictoriaLogs.
- Try it: <https://play-grafana.victoriametrics.com/explore> (choose `Jaeger` datasource)
- Documentation: <https://docs.victoriametrics.com/victoriatraces/>
> [!NOTE]
> VictoriaTraces doesn't have its own web UI. Instead, it implements Jaeger API for [integrating with Jaeger UI or Grafana](https://docs.victoriametrics.com/victoriatraces/querying/).
VictoriaTraces playground stores traces from [OpenTelemetry Astronomy Shop demo](https://github.com/open-telemetry/opentelemetry-demo).
To view trace data, follow these steps:
1. On the [Grafana Playground](https://play-grafana.victoriametrics.com/), select **Explore** in the sidebar
2. Select VictoriaTraces / Jaeger in the combo box near the top-left corner
3. In **Query Type** select "Search"
4. Select one of the services and press **Run Query**
![Screenshot of Grafana](vt-grafana.webp)
> VictoriaTraces is also represented as a datasource in [Grafana playground](#grafana-playground).
## Grafana Playground
- Try it: <https://play-grafana.victoriametrics.com>
Grafana playground contains examples of dashboards and datasources for VictoriaMetrics, VictoriaLogs, and VictoriaTraces.
It allows viewing metrics, logs, and traces generated by [OpenTelemetry Astronomy Shop demo](https://github.com/open-telemetry/opentelemetry-demo).
Try viewing available dashboards or just browse via Grafana's explore page to query and [correlate signals](https://docs.victoriametrics.com/opentelemetry/#correlations).
![Screenshot of Grafana Dashboard](grafana-node-exporter.webp)
## VMAnomaly Playground
VMAnomaly analyzes metrics, logs, or traces using VictoriaMetrics' built-in anomaly detection model to generate an [anomaly score](https://docs.victoriametrics.com/anomaly-detection/faq/#what-is-anomaly-score). An `anomaly_score > 1` indicates an anomalous condition that deserves attention.
The [anomaly metrics playground](https://play-vmanomaly.victoriametrics.com/metrics/) shows anomalies in CPU utilization.
![Screenshot of VMUI](vmanomaly-metrics.webp)
<figcaption style="text-align: center; font-style: italic;">Exploring anomalies on metric data on CPU utilization</figcaption>
The [anomaly logs playground](https://play-vmanomaly.victoriametrics.com/logs/) shows by default anomalies in log ingestion.
![Screenshot of VMUI](vmanomaly-logs.webp)
<figcaption style="text-align: center; font-style: italic;">Finding anomalies in log ingestion</figcaption>
And the [anomaly trace playground](https://play-vmanomaly.victoriametrics.com/traces/) analyzes spans with error status.
![Screenshot of VMUI](vmanomaly-traces.webp)
<figcaption style="text-align: center; font-style: italic;">Analyzing traces for service error anomalies</figcaption>
## Docker Compose Playgrounds
We provide Docker Compose examples for:
We provide Docker Compose files for:
- [VictoriaMetrics](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/master/deployment/docker/README.md)
- [VictoriaLogs](https://github.com/VictoriaMetrics/VictoriaLogs/blob/master/deployment/docker/README.md)
- [VictoriaTraces](https://github.com/VictoriaMetrics/VictoriaTraces/blob/master/deployment/docker/README.md).
- [VictoriaTraces](https://github.com/VictoriaMetrics/VictoriaTraces/blob/master/deployment/docker/README.md)
The Docker Compose examples demonstrate how various components could be configured, provisioned, and interconnected.
These examples aren't intended for production use.
## VictoriaMetrics Cloud
VictoriaMetrics UIs are also included in the [Explore](https://docs.victoriametrics.com/victoriametrics-cloud/exploring-data/) section of VictoriaMetrics and VictoriaLogs deployments, embedded in VictoriaMetrics Cloud.
You can experiment with your own data during the month‑long trial without deploying VictoriaStack in your infrastructure. To get started, follow [this guide](https://docs.victoriametrics.com/victoriametrics-cloud/get-started/quickstart/).
The compose files are already configured, provisioned, and interconnected. They can be used to quickly set up a demo environment, suitable for a [quick start](https://docs.victoriametrics.com/victoriametrics/quick-start/).

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---
weight: 6
title: Cloud Playground
menu:
docs:
parent: "playgrounds"
weight: 6
tags:
- victoriametrics
- cloud
- playground
- monitoring
---
- Try it: <https://console.victoriametrics.cloud/explore>
VictoriaMetrics UIs are included in the explore section of VictoriaMetrics and VictoriaLogs deployments embedded in VictoriaMetrics Cloud.
You can experiment with your own data without the need to deploy the VictoriaMetrics Stack in your local environment for free for a month by following this guide: [VictoriaMetrics Cloud Quickstart](https://docs.victoriametrics.com/victoriametrics-cloud/get-started/quickstart/).
Once set up, follow this guide to explore your data: <https://docs.victoriametrics.com/victoriametrics-cloud/exploring-data/>

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---
weight: 4
title: Grafana Playground
menu:
docs:
parent: "playgrounds"
weight: 4
tags:
- grafana
- playground
- metrics
- logs
- traces
---
- Try it: <https://play-grafana.victoriametrics.com/>
This playground is particularly useful if you already use Grafana and want to see how VictoriaMetrics integrates into existing workflows. It provides a hosted Grafana instance preconfigured with:
- [VictoriaMetrics](https://docs.victoriametrics.com/victoriametrics/) as a metrics data source
- [VictoriaLogs](https://docs.victoriametrics.com/victorialogs/) as a logs data source
- [VictoriaTraces](https://docs.victoriametrics.com/victoriatraces/) as a Jaeger data source for traces
## What can you do here?
- Explore [real dashboards](https://play-grafana.victoriametrics.com/dashboards) built on top of VictoriaMetrics
- See how [MetricsQL](https://docs.victoriametrics.com/victoriametrics/metricsql/) and [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/) are used in Grafana panels
- Explore correlation with the help of the [OpenTelemetry Collector dashboard](https://play-grafana.victoriametrics.com/d/BKf2sowmj/opentelemetry-collector)
- Learn dashboard design and visualization best practices
![Screenshot of VMUI](grafana.webp)
<figcaption style="text-align: center; font-style: italic;">Grafana dashboard in the playground</figcaption>
The OpenTelemetry Collector dashboard is built on the official [OpenTelemetry Astronomy Shop demo](https://github.com/VictoriaMetrics-Community/opentelemetry-demo). It lets you visualize and understand telemetry data alongside VictoriaMetrics Stack observability signals, using VictoriaMetrics for metrics, VictoriaLogs for logs, and VictoriaTraces for traces.
For an always-updated list of dashboards, bookmark this playground.
## Distribution
Relevant GitHub:
- VictoriaMetrics Grafana datasource: <https://github.com/VictoriaMetrics/victoriametrics-datasource>
- VictoriaLogs Grafana datasource: <https://github.com/VictoriaMetrics/victorialogs-datasource>

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---
weight: 8
title: LogQL to LogsQL Playground
menu:
docs:
parent: "playgrounds"
weight: 8
tags:
- logsql
- loki
- victorialogs
- playground
- monitoring
---
- Try it: <https://play-logql.victoriametrics.com/>
For teams migrating from Grafana Loki, this simple UI provides a useful [translator from LogQL to LogsQL](https://docs.victoriametrics.com/victorialogs/logql-to-logsql/).
![Screenshot of LogQL to LogsQL](logql-to-logsql.webp)
## What can you do here?
The query-language translation tool automatically converts Loki queries into VictoriaLogs queries, reducing friction when adopting VictoriaLogs in environments already using Loki.
Type your LogQL query and press **Execute**.
For example, this LogQL query:
```text
{collector="otel-collector"} |= "POST"
```
Translates into the equivalent [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/)
```text
{collector="otel-collector"} "POST"
```
## Distribution
- GitHub: <https://github.com/VictoriaMetrics-Community/logql-to-logsql>

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---
weight: 7
title: SQL to LogsQL Playground
menu:
docs:
parent: "playgrounds"
weight: 7
tags:
- logsql
- SQL
- victorialogs
- playground
- monitoring
---
- Try it: <https://play-sql.victoriametrics.com/>
This playground enables you to query data from a VictoriaLogs instance or translate SQL to [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/) without querying.
![Screenshot of SQL to LogsQL](sql-to-logsql.webp)
## What can you do here?
First, run `SHOW TABLES;` to view all the existing tables in the SQL database and their equivalent query in [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/).
Then, type your SQL query and press **Execute**.
For example, this query:
```sql
SELECT _time, _msg
FROM logs
WHERE _msg LIKE 'error'
ORDER BY _time DESC
LIMIT 100
```
Translates into:
```text
_msg:error | fields _time, _msg | sort by (_time desc) | limit 100
```
## Distribution
- GitHub: <https://github.com/VictoriaMetrics/sql-to-logsql>

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---
weight: 2
title: VictoriaLogs Playground
menu:
docs:
parent: "playgrounds"
weight: 2
tags:
- victorialogs
- playground
- logs
---
- Try it: <https://play-vmlogs.victoriametrics.com/>
- Query language reference: [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/)
This playground focuses on VictoriaLogs and lets you test the query engine on a demo log set. The playground demonstrates how VictoriaLogs handles high-volume log data with predictable performance and low operational overhead.
![Screenshot of VMUI](vl-main-vmui.webp)
<figcaption style="text-align: center; font-style: italic;">VictoriaLogs playground</figcaption>
## What can you do here?
The WebUI provides the following modes for displaying query results:
- Group: results are displayed as a table with rows grouped by stream fields.
- Table: displays query results as a table.
- JSON: displays raw JSON response from `/select/logsql/query` HTTP API.
- Live: displays live tailing results for the given query.
As a starting point, you can type `collector: "otel-collector"` in the query field to search for entries collected by OpenTelemetry.
![Screenshot of VMUI](vl-otel-collector.webp)
<figcaption style="text-align: center; font-style: italic;">Log entries collected with the OpenTelemetry collector</figcaption>
Typing `error AND _time:24h` shows you the entries containing the text "error" during the last 24 hours.
![Screenshot of VMUI](vl-error.webp)
The **Overview** provides a quick, high-level look at the logs stored in VictoriaLogs. It helps you understand the volume and structure of your log data before diving into detailed queries. You can see log ingestion trends, identify the most common fields and values, and quickly spot noisy or unusual streams. From here, you can click on fields or values to automatically apply filters and start exploring your data with LogsQL.
![Screenshot of VMUI](vl-overview.webp)
## Distribution
- GitHub: <https://github.com/VictoriaMetrics/VictoriaLogs>

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---
weight: 1
title: VictoriaMetrics Playground
menu:
docs:
parent: "playgrounds"
weight: 1
tags:
- victoriametrics
---
- Try it: <https://play.victoriametrics.com/>
- Query language reference: [MetricsQL](https://docs.victoriametrics.com/victoriametrics/metricsql/)
This is the primary playground for VictoriaMetrics, powered by VMUI and backed by a VictoriaMetrics cluster installation. Use it to experiment with the query engine, see available pages, or try tools such as the relabeling debugger.
This playground is the best starting point for understanding how VictoriaMetrics stores and queries metrics at scale.
![Screenshot of VMUI](vm-main-vmui.webp)
<figcaption style="text-align: center; font-style: italic;">VictoriaMetrics playground</figcaption>
## What can you do here?
The query tab provides a sandbox to experiment with [MetricsQL](https://docs.victoriametrics.com/victoriametrics/metricsql/). Turn on Autocomplete and start typing to discover time series. You can add multiple queries and compare them.
You can try these to get started:
- Average CPU usage per job: `sum(rate(process_cpu_seconds_total[5m])) by (job)`
- HTTP requests per-second rate: `sum(rate(vm_http_requests_total[5m]))`
- Top 5 CPU intensive jobs `topk(5, sum(rate(process_cpu_seconds_total[5m])) by (job))`
Below is an example of average CPU usage per job:
```text
sum(rate(process_cpu_seconds_total[5m])) by (job)
```
![Screenshot of VMUI](vm-process-cpu.webp)
<figcaption style="text-align: center; font-style: italic;">Average CPU usage per job</figcaption>
Here, we are requesting the per-second rate of HTTP requests:
```text
sum(rate(vm_http_requests_total[5m]))
```
![Screenshot of VMUI](vm-http-requests.webp)
<figcaption style="text-align: center; font-style: italic;">HTTP requests per second</figcaption>
And here is an example for obtaining the top 5 high CPU jobs:
```text
topk(5, sum(rate(process_cpu_seconds_total[5m])) by (job))
```
![Screenshot of VMUI](vm-topk-process-cpu.webp)
<figcaption style="text-align: center; font-style: italic;">Top 5 CPU intensive jobs</figcaption>
For a deep dive into all the features of this playground, please visit the [VMUI](https://docs.victoriametrics.com/victoriametrics/single-server-victoriametrics/#vmui) page.
## Distribution
- GitHub: <https://github.com/VictoriaMetrics/VictoriaMetrics>

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---
weight: 3
title: VictoriaTraces Playground
menu:
docs:
parent: "playgrounds"
weight: 3
tags:
- victoriatraces
- playground
- monitoring
---
- Try it: <https://play-vtraces.victoriametrics.com/>
- Query language reference: [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/)
> [!NOTE] Note
> This playground is currently under development, as the main project it is correlated with, VictoriaTraces, is also under development.
VictoriaTraces provides a UI for browsing raw data and Jaeger APIs/Grafana data source for trace visualization. This playground showcases VictoriaTraces, the VictoriaMetrics backend for distributed tracing, and enables trace searching, visualization, and service graph/dependency analysis.
![Screenshot of Grafana](vt-grafana.webp)
<figcaption style="text-align: center; font-style: italic;">Grafana playground showing VictoriaTraces/Jaeger datasource</figcaption>
## What can you do here?
The WebUI provides the following modes for displaying query results:
- Group: results are displayed as a table with rows grouped by stream fields.
- Table: displays query results as a table.
- JSON: displays raw JSON response from the HTTP API.
- Live: displays live tailing results for the given query.
## Distribution
- GitHub: <https://github.com/VictoriaMetrics/VictoriaTraces>

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---
weight: 5
title: Anomaly Detection Playground
menu:
docs:
parent: "playgrounds"
weight: 5
tags:
- vmanomaly
- playground
- monitoring
---
- Try it: <https://play-vmanomaly.victoriametrics.com/metrics/vmui/>
- UI Guide: <https://docs.victoriametrics.com/anomaly-detection/ui/#example-usage>
The playground demonstrates automatic [anomaly detection](https://docs.victoriametrics.com/anomaly-detection/).
![Screenshot of VMUI](vmanomaly.webp)
<figcaption style="text-align: center; font-style: italic;">Exploring model fit for CPU usage series</figcaption>
The playground showcases anomaly detection data (native timeseries or converted to timeseries) using VictoriaMetrics, VictoriaLogs, or VictoriaTraces datasources, respectively:
- <https://play-vmanomaly.victoriametrics.com/metrics/>
- <https://play-vmanomaly.victoriametrics.com/logs/>
- <https://play-vmanomaly.victoriametrics.com/traces/>
## What can you do here?
The Anomaly Detection playground lets you:
- Understand how [MetricsQL](https://docs.victoriametrics.com/victoriametrics/metricsql/) and [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/) are used to generate input data for anomaly detection.
- Explore metrics data enriched with anomaly scores, predictions, and confidence intervals.
- Visualize anomalies directly in VMUI, including consecutive anomalies that last over time rather than being a single point, to imitate how alerting rules trigger on such data.
- Learn how anomaly scores can be used for alerting purposes by exploring generated alerting rules.
## Distribution & setup
VMAnomaly is distributed through various channels:
- [Installation guide](https://docs.victoriametrics.com/anomaly-detection/quickstart/)
- Docker containers available in [Docker Hub](https://hub.docker.com/r/victoriametrics/vmanomaly) and [Quay.io](https://quay.io/repository/victoriametrics/vmanomaly)
- [Helm charts](https://github.com/VictoriaMetrics/helm-charts) (including anomaly setups)
- [VM Operator](https://docs.victoriametrics.com/operator/resources/vmanomaly/)

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