For exporting data, VictoriaMetrics Anomaly Detection (`vmanomaly`) primarily employs the [VmWriter](#vm-writer), which writes produced anomaly scores **(preserving initial labelset and optionally applying additional ones)** back to VictoriaMetrics. This writer is tailored for smooth data export within the VictoriaMetrics ecosystem.
For VictoriaMetrics Cluster version only, tenants are identified by accountID or accountID:projectID. See VictoriaMetrics Cluster [multitenancy docs](https://docs.victoriametrics.com/cluster-victoriametrics/#multitenancy)
Metrics to save the output (in metric names or labels). Must have `__name__` key. Must have a value with `$VAR` placeholder in it to distinguish between resulting metrics. Supported placeholders:
`$VAR` -- Variables that model provides, all models provide the following set: {"anomaly_score", "y", "yhat", "yhat_lower", "yhat_upper"}. Description of standard output is [here](https://docs.victoriametrics.com/anomaly-detection/components/models/#vmanomaly-output). Depending on [model type](https://docs.victoriametrics.com/anomaly-detection/components/models/) it can provide more metrics, like "trend", "seasonality" etc.
* for `__name__` parameter it will name metrics returned by models as `PREFIX1_anomaly_score`, `PREFIX1_yhat_lower`, etc. Vmanomaly output metrics names described [here](https://docs.victoriametrics.com/anomaly-detection/components/models/#vmanomaly-output)
* for `for` parameter will add labels `PREFIX2_query_name_1`, `PREFIX2_query_name_2`, etc. Query names are set as aliases in config `reader` section in [`queries`](https://docs.victoriametrics.com/anomaly-detection/components/reader/#config-parameters) parameter.
Apart from specified labels, output metrics will return **labels inherited from input metrics returned by [queries](https://docs.victoriametrics.com/anomaly-detection/components/reader/#config-parameters)**.
For example if input data contains labels such as `cpu=1, device=eth0, instance=node-exporter:9100` all these labels will be present in vmanomaly output metrics.