There are 4 sources available to read data into VM Anomaly Detection from: VictoriaMetrics, (ND)JSON file, QueryRange, or CSV file. Depending on the data source, different parameters should be specified in the config file in the `reader` section.
VictoriaMetrics Anomaly Detection (`vmanomaly`) primarily uses [VmReader](#vm-reader) to ingest data. This reader focuses on fetching time-series data directly from VictoriaMetrics with the help of powerful [MetricsQL](https://docs.victoriametrics.com/metricsql/) expressions for aggregating, filtering and grouping your data, ensuring seamless integration and efficient data handling.
> **Note**: Starting from [v1.13.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1130) there is backward-compatible change of [`queries`](https://docs.victoriametrics.com/anomaly-detection/components/reader?highlight=queries#vm-reader) arg of [VmReader](#vm-reader). New format allows to specify per-query parameters, like `step` to reduce amount of data read from VictoriaMetrics TSDB and to allow config flexibility. Please see [per-query parameters](#per-query-parameters) section for the details.
Starting from [v1.13.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1130) there is change of [`queries`](https://docs.victoriametrics.com/anomaly-detection/components/reader?highlight=queries#vm-reader) arg format. Now each query alias supports the next (sub)fields:
-`step` (string): query-level frequency of the points returned, i.e. `30s`. Will be converted to `/query_range?step=%s` param (in seconds). Useful to optimize total amount of data read from VictoriaMetrics, where different queries may have **different frequencies for different [machine learning models](https://docs.victoriametrics.com/anomaly-detection/components/models)** to run on.
> **Note**: if not set explicitly (or if older config style prior to [v1.13.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1130)) is used, then it is set to reader-level `sampling_period` arg.
> **Note**: having **different** individual `step` args for queries (i.e. `30s` for `q1` and `2m` for `q2`) is not yet supported for [multivariate model](https://docs.victoriametrics.com/anomaly-detection/components/models/#multivariate-models) if you want to run it on several queries simultaneously (i.e. setting [`queries`](https://docs.victoriametrics.com/anomaly-detection/components/models/#queries) arg of a model to [`q1`, `q2`]).
-`data_range` (list[float | string]): Introduced in [v1.15.1](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1151), it allows defining **valid** data ranges for input per individual query in `queries`, resulting in:
- **High anomaly scores** (>1) when the *data falls outside the expected range*, indicating a data constraint violation.
- **Lowest anomaly scores** (=0) when the *model's predictions (`yhat`) fall outside the expected range*, meaning uncertain predictions.
-`max_points_per_query` (int): Introduced in [v1.17.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1170), optional arg overrides how `search.maxPointsPerTimeseries` flag (available since [v1.14.1](#v1141)) impacts `vmanomaly` on splitting long `fit_window` [queries](https://docs.victoriametrics.com/anomaly-detection/components/reader/?highlight=queries#vm-reader) into smaller sub-intervals. This helps users avoid hitting the `search.maxQueryDuration` limit for individual queries by distributing initial query across multiple subquery requests with minimal overhead. Set less than `search.maxPointsPerTimeseries` if hitting `maxQueryDuration` limits. If set on a query-level, it overrides the global `max_points_per_query` (reader-level).
-`tz` (string): Introduced in [v1.18.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1180), this optional argument enables timezone specification per query, overriding the reader’s default `tz`. This setting helps to account for local timezone shifts, such as [DST](https://en.wikipedia.org/wiki/Daylight_saving_time), in models that are sensitive to seasonal variations (e.g., [`ProphetModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#prophet) or [`OnlineQuantileModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#online-seasonal-quantile)).
For VictoriaMetrics Cluster version only, tenants are identified by `accountID` or `accountID:projectID`. Starting from [v1.16.2](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1162), `multitenant` [endpoint](https://docs.victoriametrics.com/cluster-victoriametrics/?highlight=reads#multitenancy-via-labels) is supported, to execute queries over multiple [tenants](https://docs.victoriametrics.com/cluster-victoriametrics/#multitenancy). See VictoriaMetrics Cluster [multitenancy docs](https://docs.victoriametrics.com/cluster-victoriametrics/#multitenancy)
Frequency of the points returned. Will be converted to `/query_range?step=%s` param (in seconds). **Required** since [v1.9.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v190).
Verify TLS certificate. If `False`, it will not verify the TLS certificate.
If `True`, it will verify the certificate using the system's CA store.
If a path to a CA bundle file (like `ca.crt`), it will verify the certificate using the provided CA bundle.
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`tls_cert_file`
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`path/to/cert.crt`
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Path to a file with the client certificate, i.e. `client.crt`. Available since [v1.16.3](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1163).
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`tls_key_file`
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`path/to/key.crt`
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Path to a file with the client certificate key, i.e. `client.key`. Available since [v1.16.3](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1163).
Path to a file, which contains token, that is passed in the standard format with header: `Authorization: bearer {token}`. Available since [v1.15.9](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1159)
List of strings with series selector. See: [Prometheus querying API enhancements](https://docs.victoriametrics.com/##prometheus-querying-api-enhancements)
If True, then query will be performed from the last seen timestamp for a given series. If False, then query will be performed from the start timestamp, based on a schedule period. Defaults to `False`. Useful for `infer` stages in case there were skipped `infer` calls prior to given.
Introduced in [v1.15.1](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1151), it allows overriding the default `-search.latencyOffset` [flag of VictoriaMetrics](https://docs.victoriametrics.com/?highlight=search.latencyOffset#list-of-command-line-flags) (30s). The default value is set to 1ms, which should help in cases where `sampling_frequency` is low (10-60s) and `sampling_frequency` equals `infer_every` in the [PeriodicScheduler](https://docs.victoriametrics.com/anomaly-detection/components/scheduler/?highlight=infer_every#periodic-scheduler). This prevents users from receiving `service - WARNING - [Scheduler [scheduler_alias]] No data available for inference.` warnings in logs and allows for consecutive `infer` calls without gaps. To restore the old behavior, set it equal to your `-search.latencyOffset` [flag value]((https://docs.victoriametrics.com/?highlight=search.latencyOffset#list-of-command-line-flags)).
Introduced in [v1.17.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1170), optional arg overrides how `search.maxPointsPerTimeseries` flag (available since [v1.14.1](#v1141)) impacts `vmanomaly` on splitting long `fit_window` [queries](https://docs.victoriametrics.com/anomaly-detection/components/reader/?highlight=queries#vm-reader) into smaller sub-intervals. This helps users avoid hitting the `search.maxQueryDuration` limit for individual queries by distributing initial query across multiple subquery requests with minimal overhead. Set less than `search.maxPointsPerTimeseries` if hitting `maxQueryDuration` limits. You can also set it on [per-query](#per-query-parameters) basis to override this global one.
Introduced in [v1.18.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1180), this optional argument specifies the [IANA](https://nodatime.org/TimeZones) timezone to account for local shifts, like [DST](https://en.wikipedia.org/wiki/Daylight_saving_time), in models sensitive to seasonal patterns (e.g., [`ProphetModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#prophet) or [`OnlineQuantileModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#online-seasonal-quantile)). Defaults to `UTC` if not set and can be overridden on a [per-query basis](#per-query-parameters).
As of [v1.16.3](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1163), `vmanomaly` supports [mutual TLS (mTLS)](https://en.wikipedia.org/wiki/Mutual_authentication) for secure communication across its components, including [VmReader](https://docs.victoriametrics.com/anomaly-detection/components/reader/#vm-reader), [VmWriter](https://docs.victoriametrics.com/anomaly-detection/components/writer/#vm-writer), and [Monitoring/Push](https://docs.victoriametrics.com/anomaly-detection/components/monitoring/#push-config-parameters). This allows for mutual authentication between the client and server when querying or writing data to [VictoriaMetrics Enterprise, configured for mTLS](https://docs.victoriametrics.com/#mtls-protection).
mTLS ensures that both the client and server verify each other's identity using certificates, which enhances security by preventing unauthorized access.
To configure mTLS, the following parameters can be set in the [config](#config-parameters):
-`verify_tls`: If set to a string, it functions like the `-mtlsCAFile` command-line argument of VictoriaMetrics, specifying the CA bundle to use. Set to `True` to use the system's default certificate store.
-`tls_cert_file`: Specifies the path to the client certificate, analogous to the `-tlsCertFile` argument of VictoriaMetrics.
-`tls_key_file`: Specifies the path to the client certificate key, similar to the `-tlsKeyFile` argument of VictoriaMetrics.
These options allow you to securely interact with mTLS-enabled VictoriaMetrics endpoints.
Example configuration to enable mTLS with custom certificates: