VictoriaMetrics/docs/anomaly-detection/components/reader.md

title	weight	menu	aliases
Reader	2	docs parent weight vmanomaly-components 2	/anomaly-detection/components/reader.html

VictoriaMetrics Anomaly Detection (vmanomaly) primarily uses VmReader to ingest data. This reader focuses on fetching time-series data directly from VictoriaMetrics with the help of powerful 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

Note

: Starting from v1.13.0 there is backward-compatible change of queries arg of VmReader. 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 section for the details.

Old format like

# 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:

# 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
      # new query-level arguments will be added in backward-compatible way in future releases

Per-query parameters

Starting from v1.13.0 there is change of queries arg format. Now each query alias supports the next (sub)fields:

• 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 to run on.

  Note

  : if not set explicitly (or if older config style prior to v1.13.0) 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 if you want to run it on several queries simultaneously (i.e. setting queries arg of a model to [q1, q2]).

• data_range (list[float | string]): Introduced in v1.15.1, 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.

Per-query config example

reader:
  class: 'vm'
  sampling_period: '1m'
  # other reader params ...
  queries:
    ingestion_rate:
      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

Config parameters

Parameter	Example	Description
class	reader.vm.VmReader (or vm starting from v1.13.0)	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 above	See per-query config section above
datasource_url	http://localhost:8481/	Datasource URL address
tenant_id	0:0	For VictoriaMetrics Cluster version only, tenants are identified by accountID or accountID:projectID. See VictoriaMetrics Cluster multitenancy docs
sampling_period	1h	Frequency of the points returned. Will be converted to /query_range?step=%s param (in seconds). Required since v1.9.0.
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	Allows disabling TLS verification of the remote certificate.
bearer_token	token	Token is passed in the standard format with header: Authorization: bearer {token}
extra_filters	[]	List of strings with series selector. See: Prometheus querying API enhancements
query_from_last_seen_timestamp	True	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 True. (False prior to v1.15.1). Useful for infer stages in case there were skipped infer calls prior to given.
latency_offset	1ms	Introduced in v1.15.1, it allows overriding the default -search.latencyOffset flag of VictoriaMetrics (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. 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.

Config file example:

reader:
  class: "vm"  # or "reader.vm.VmReader" until v1.13.0
  datasource_url: "http://localhost:8428/"
  tenant_id: "0:0"
  queries:
    ingestion_rate: 'sum(rate(vm_rows_inserted_total[5m])) by (type) > 0'
  sampling_period: '1m'

Healthcheck metrics

VmReader exposes several healthchecks metrics.