--- title: Reader weight: 2 menu: docs: parent: "vmanomaly-components" weight: 2 tags: - metrics - enterprise aliases: - /anomaly-detection/components/reader.html --- 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/victoriametrics/metricsql/) expressions for aggregating, filtering and grouping your data, ensuring seamless integration and efficient data handling. Future updates will introduce additional readers, expanding the range of data sources `vmanomaly` can work with. ## VM reader > There is backward-compatible change{{% available_from "v1.13.0" anomaly %}} 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. Old format like ```yaml # other config sections ... reader: class: 'vm' datasource_url: 'http://localhost:8428' # source victoriametrics/prometheus sampling_period: "10s" # set it <= min(infer_every) in schedulers section queries: # old format {query_alias: query_expr}, prior to 1.13, will be converted to a new format automatically vmb: 'avg(vm_blocks)' ``` will be converted to a new one with a warning raised in logs: ```yaml # other config sections ... reader: class: 'vm' datasource_url: 'http://localhost:8428' # source victoriametrics/prometheus sampling_period: '10s' queries: # old format {query_alias: query_expr}, prior to 1.13, will be converted to a new format automatically vmb: expr: 'avg(vm_blocks)' # initial MetricsQL expression step: '10s' # individual step for this query, will be filled with `sampling_period` from the root level data_range: ['-inf', 'inf'] # by default, no constraints applied on data range tz: 'UTC' # by default, tz-free data is used throughout the model lifecycle # new query-level arguments will be added in backward-compatible way in future releases ``` ### Per-query parameters There is change{{% available_from "v1.13.0" anomaly %}} 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, which *override reader-level parameters*, if set: - `expr` (string): MetricsQL/PromQL expression that defines an input for VmReader. As accepted by `/query_range?query=%s`. i.e. `avg(vm_blocks)` - `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. > 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. > 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`{{% available_from "v1.15.1" anomaly %}} (list[float | string]): 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 range constraint violation (e.g. improperly configured metricsQL query, sensor malfunction, overflows in underlying metrics, etc.). Anomaly scores can be set to a specific value, like `5`, to indicate a strong violation, using the `anomaly_score_outside_data_range` [arg](https://docs.victoriametrics.com/anomaly-detection/components/models/#score-outside-data-range) of a respective model this query is used in. - **Lowest anomaly scores** (=0) when the *model's predictions (`yhat`) fall outside the expected range*, meaning uncertain predictions that does not really aligh with the data. Works together with `anomaly_score_outside_data_range` [arg](https://docs.victoriametrics.com/anomaly-detection/components/models/#score-outside-data-range) of a model to determine the anomaly score for such cases as well as with `clip_predictions` [arg](https://docs.victoriametrics.com/anomaly-detection/components/models/#clip-predictions) of a model to clip the predictions to the expected range. > 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 `data_range` arg{{% available_from "v1.18.1" anomaly %}} - `max_points_per_query`{{% available_from "v1.17.0" anomaly %}} (int): Optional arg, overrides how `search.maxPointsPerTimeseries` flag{{% available_from "v1.14.1" anomaly %}} 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`{{% available_from "v1.18.0" anomaly %}} (string): 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)). - `tenant_id` {{% available_from "v1.19.0" anomaly %}} (string): this optional argument enables tenant-level separation for queries (e.g. `query1` to get the data from tenant "0:0", `query2` - from tenant "1:0"). It works as follows: - if *not set, inherits* reader-level `tenant_id` - if *set, overrides* reader-level `tenant_id` - *raises config validation error*, if *reader-level is not set* and *query-level is found* (mixing of VictoriaMetrics [single-node](https://docs.victoriametrics.com/victoriametrics/single-server-victoriametrics/) and [cluster](https://docs.victoriametrics.com/victoriametrics/cluster-victoriametrics/) is prohibited in a single config) - *raises config validation warning*, if `writer.tenant_id` is not explicitly set to `multitenant` when reader uses tenants, meaning [VictoriaMetrics cluster](https://docs.victoriametrics.com/victoriametrics/cluster-victoriametrics/) will be used for data querying. - also *raises config validation error* if a set of `reader.queries` for [multivariate models](https://docs.victoriametrics.com/anomaly-detection/components/models/#multivariate-models) has *different* tenant_ids (meaning tenant data is mixed, and special labels like `vm_project_id`, `vm_account_id` will have [ambiguous values](https://docs.victoriametrics.com/victoriametrics/cluster-victoriametrics/#multitenancy-via-labels)) > The recommended approach for using per-query `tenant_id`s is to set both `reader.tenant_id` and `writer.tenant_id` to `multitenant`. See [this section](https://docs.victoriametrics.com/anomaly-detection/components/writer/#multitenancy-support) for more details. Configurations where `reader.tenant_id` equals `writer.tenant_id` and is not `multitenant` are also considered safe, provided there is a single, DISTINCT `tenant_id` defined in the reader (either at the reader level or the query level, if set). ### Per-query config example ```yaml reader: class: 'vm' sampling_period: '1m' max_points_per_query: 10000 data_range: [0, 'inf'] tenant_id: 'multitenant' # other reader params ... queries: ingestion_rate_t1: expr: 'sum(rate(vm_rows_inserted_total[5m])) by (type) > 0' step: '2m' # overrides global `sampling_period` of 1m data_range: [10, 'inf'] # meaning only positive values > 10 are expected, i.e. a value `y` < 10 will trigger anomaly score > 1 max_points_per_query: 5000 # overrides reader-level value of 10000 for `ingestion_rate` query tz: 'America/New_York' # to override reader-wise `tz` tenant_id: '1:0' # overriding tenant_id to isolate data ingestion_rate_t2: expr: 'sum(rate(vm_rows_inserted_total[5m])) by (type) > 0' step: '2m' # overrides global `sampling_period` of 1m data_range: [10, 'inf'] # meaning only positive values > 10 are expected, i.e. a value `y` < 10 will trigger anomaly score > 1 max_points_per_query: 5000 # overrides reader-level value of 10000 for `ingestion_rate` query tz: 'America/New_York' # to override reader-wise `tz` tenant_id: '2:0' # overriding tenant_id to isolate data ``` ### Config parameters
Parameter Example Description
`class` `reader.vm.VmReader` (or `vm`{{% available_from "v1.13.0" anomaly %}}) Name of the class needed to enable reading from VictoriaMetrics or Prometheus. VmReader is the default option, if not specified.
`queries` See [per-query config example](#per-query-config-example) above See [per-query config section](#per-query-parameters) above
`datasource_url` `http://localhost:8481/` Datasource URL address
`tenant_id` `0:0`, `multitenant` 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/victoriametrics/cluster-victoriametrics/?highlight=reads#multitenancy-via-labels) is supported, to execute queries over multiple [tenants](https://docs.victoriametrics.com/victoriametrics/cluster-victoriametrics/#multitenancy). See VictoriaMetrics Cluster [multitenancy docs](https://docs.victoriametrics.com/victoriametrics/cluster-victoriametrics/#multitenancy)
`sampling_period` `1h` 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).
`query_range_path` `/api/v1/query_range` Performs PromQL/MetricsQL range query
`health_path` `health` Absolute or relative URL address where to check availability of the datasource.
`user` `USERNAME` BasicAuth username
`password` `PASSWORD` BasicAuth password
`timeout` `30s` Timeout for the requests, passed as a string
`verify_tls` `false` 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.
`tls_cert_file` `path/to/cert.crt` Path to a file with the client certificate, i.e. `client.crt`{{% available_from "v1.16.3" anomaly %}}.
`tls_key_file` `path/to/key.crt` Path to a file with the client certificate key, i.e. `client.key`{{% available_from "v1.16.3" anomaly %}}.
`bearer_token` `token` Token is passed in the standard format with header: `Authorization: bearer {token}`
`bearer_token_file` `path_to_file` Path to a file, which contains token, that is passed in the standard format with header: `Authorization: bearer {token}`{{% available_from "v1.15.9" anomaly %}}.
`extra_filters` `[]` List of strings with series selector. See: [Prometheus querying API enhancements](https://docs.victoriametrics.com/victoriametrics/single-server-victoriametrics/##prometheus-querying-api-enhancements)
`query_from_last_seen_timestamp` `False` 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.
`latency_offset` `1ms` It allows overriding the default `-search.latencyOffset`{{% available_from "v1.15.1" anomaly %}} [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).
`max_points_per_query` `10000` Optional arg{{% available_from "v1.17.0" anomaly %}} overrides how `search.maxPointsPerTimeseries` flag{{% available_from "v1.14.1" anomaly %}} 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.
`tz` `UTC` Optional argument{{% available_from "v1.18.0" anomaly %}} 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).
`data_range` `["-inf", "inf"]` Optional argument{{% available_from "v1.18.1" anomaly %}} allows defining **valid** data ranges for input of all the queries in `queries`. Defaults to `["-inf", "inf"]` if not set and can be overridden on a [per-query basis](#per-query-parameters).
Config file example: ```yaml reader: class: "vm" # or "reader.vm.VmReader" until v1.13.0 datasource_url: "https://play.victoriametrics.com/" tenant_id: '0:0' tz: 'America/New_York' data_range: [1, 'inf'] # reader-level queries: ingestion_rate: expr: 'sum(rate(vm_rows_inserted_total[5m])) by (type) > 0' step: '1m' # can override reader-level `sampling_period` on per-query level data_range: [0, 'inf'] # if set, overrides reader-level data_range tz: 'Australia/Sydney' # if set, overrides reader-level tz # tenant_id: '1:0' # if set, overrides reader-level tenant_id sampling_period: '1m' query_from_last_seen_timestamp: True # false by default latency_offset: '1ms' ``` ### mTLS protection `vmanomaly` supports [mutual TLS (mTLS)](https://en.wikipedia.org/wiki/Mutual_authentication){{% available_from "v1.16.3" anomaly %}} 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/victoriametrics/single-server-victoriametrics/#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: ```yaml reader: class: "vm" datasource_url: "https://your-victoriametrics-instance-with-mtls" # tenant_id: "0:0" uncomment and set for cluster version queries: vm_blocks_example: expr: 'avg(rate(vm_blocks[5m]))' step: 30s sampling_period: 30s verify_tls: "path/to/ca.crt" # path to CA bundle for TLS verification tls_cert_file: "path/to/client.crt" # path to the client certificate tls_key_file: "path/to/client.key" # path to the client certificate key # additional reader parameters ... # other config sections, like models, schedulers, writer, ... ``` ### Healthcheck metrics `VmReader` exposes [several healthchecks metrics](https://docs.victoriametrics.com/anomaly-detection/components/monitoring/#reader-behaviour-metrics).