Please find the changelog for VictoriaMetrics Anomaly Detection below.

Important note: Users are strongly encouraged to upgrade to vmanomaly v1.9.2 or later versions for optimal performance and accuracy.

This recommendation is crucial for configurations with a low infer_every parameter in your scheduler, and in scenarios where data exhibits significant high-order seasonality patterns (such as hourly or daily cycles). Previous versions from v1.5.1 to v1.8.0 were identified to contain a critical issue impacting model training, where models were inadvertently trained on limited data subsets, leading to suboptimal fits, affecting the accuracy of anomaly detection.

Upgrading to v1.9.2 addresses this issue, ensuring proper model training and enhanced reliability. For users utilizing Helm charts, it is recommended to upgrade to version 1.0.0 or newer.


Released: 2024-02-22

  • FEATURE: Multi-scheduler support. Now users can use multiple model specs in a single config (via aliasing), each spec can be run with its own (even multiple) schedulers.
    • Introduction of schedulers arg in model spec:
      • It allows each model to be managed by 1 (or more) schedulers, so overall resource usage is optimized and flexibility is preserved.
      • Passing an empty list or not specifying this param implies that each model is run in all the schedulers, which is a backward-compatible behavior.
      • Please find more details in docs on Model section
  • DEPRECATION: slight refactor of a scheduler config section
    • Now schedulers are passed as a mapping of scheduler_alias: scheduler_spec under scheduler sections. Using old format (< 1.11.0) will produce warnings for now and will be removed in future versions.
  • DEPRECATION: The --watch CLI option for config file reloads is deprecated and will be ignored in the future.


Released: 2024-02-15

  • FEATURE: Multi-model support. Now users can specify multiple model specs in a single config (via aliasing), as well as to reference what queries from VmReader it should be run on.

    • Introduction of queries arg in model spec:
      • It allows the model to be executed only on a particular query subset from reader section.
      • Passing an empty list or not specifying this param implies that each model is run on results from all queries, which is a backward-compatible behavior.
      • Please find more details in docs on Model section
  • DEPRECATION: slight refactor of a model config section

    • Now models are passed as a mapping of model_alias: model_spec under model sections. Using old format (<= 1.9.2) will produce warnings for now and will be removed in future versions.
    • Please find more details in docs on Model section
  • IMPROVEMENT: now logs from monitoring.pull GET requests to /metrics endpoint are shown only in DEBUG mode

  • IMPROVEMENT: labelset for multivariate models is deduplicated and cleaned, resulting in better UX

Note: These updates support more flexible setup and effective resource management in service, as now it’s not longer needed to spawn several instances of vmanomaly to split queries/models context across.


Released: 2024-01-29


Released: 2024-01-27

  • IMPROVEMENT: Updated the offline license verification backbone to mitigate a critical vulnerability identified in the ecdsa library, ensuring enhanced security despite initial non-impact.
  • IMPROVEMENT: bump 3rd-party dependencies for Python 3.12.1


Released: 2024-01-26

  • BUGFIX: The query_from_last_seen_timestamp internal logic in VmReader, first introduced in v1.5.1, now functions correctly. This fix ensures that the input data shape remains consistent for subsequent fit-based model calls in the service.
  • BREAKING CHANGE: The sampling_period parameter is now mandatory in VmReader. This change aims to clarify and standardize the frequency of input/output in vmanomaly, thereby reducing uncertainty and aligning with user expectations.

Note: The majority of users, who have been proactively specifying the sampling_period parameter in their configurations, will experience no disruption from this update. This transition formalizes a practice that was already prevalent and expected among our user base.


Released: 2024-01-15

  • FEATURE: Added Univariate MAD (median absolute deviation) model support.
  • IMPROVEMENT: Update Python to 3.12.1 and all the dependencies.
  • IMPROVEMENT: Don’t check /health endpoint, check the real /query_range or /import endpoints directly. Users kept getting problems with /health.
  • DEPRECATION: “health_path” param is deprecated and doesn’t do anything in config (reader, writer, monitoring.push).


Released: 2023-12-21

  • FIX: fit/infer calls are now skipped if we have insufficient valid data to run on.
  • FIX: proper handling of inf and NaN in fit/infer calls.
  • FEATURE: add counter of skipped model runs vmanomaly_model_runs_skipped to healthcheck metrics.
  • FEATURE: add exponential retries wrapper to VmReader’s read_metrics().
  • FEATURE: add BacktestingScheduler for consecutive retrospective fit/infer calls.
  • FEATURE: add improved & numerically stable anomaly scores.
  • IMPROVEMENT: add full config validation. The probability of getting errors in later stages (say, model fit) is greatly reduced now. All the config validation errors that needs to be fixed are now a part of logging.

    note: this is an backward-incompatible change, as model config section now expects key-value args for internal model defined in nested args.

  • IMPROVEMENT: add explicit support of gzip-ed responses from vmselect in VmReader.


Released: 2023-10-30

    • now all the produced healthcheck metrics have vmanomaly_ prefix for easier accessing.
    • updated docs for monitoring.

    note: this is an backward-incompatible change, as metric names will be changed, resulting in new metrics creation, i.e. model_datapoints_produced will become vmanomaly_model_datapoints_produced

  • IMPROVEMENT: Set default value for --log_level from DEBUG to INFO to reduce logs verbosity.
  • IMPROVEMENT: Add alias --log-level to --log_level.
  • FEATURE: Added extra_filters parameter to reader. It allows to apply global filters to all queries.
  • FEATURE: Added verify_tls parameter to reader and writer. It allows to disable TLS verification for remote endpoint.
  • FEATURE: Added bearer_token parameter to reader and writer. It allows to pass bearer token for remote endpoint for authentication.
  • BUGFIX: Fixed passing workers parameter for reader. Previously it would throw a runtime error if workers was specified.


Released: 2023-09-18

  • IMPROVEMENT: Infer from the latest seen datapoint for each query. Handles the case datapoints arrive late.


Released: 2023-08-11

  • FEATURE: add --license and --license-file command-line flags for license code verification.
  • IMPROVEMENT: Updated Python to 3.11.4 and updated dependencies.
  • IMPROVEMENT: Guide documentation for Custom Model usage.


Released: 2023-06-09

  • FIX: Fix case with received metric labels overriding generated.


Released: 2023-06-09

  • IMPROVEMENT: Update dependencies.


Released: 2023-05-06

  • FEATURE: Reworked self-monitoring grafana dashboard for vmanomaly.
  • IMPROVEMENT: Update python version and dependencies.


Released: 2023-03-21

  • FEATURE: Parallelized queries. See reader.workers param to control parallelism. By default it’s value is equal to number of queries (sends all the queries at once).
  • IMPROVEMENT: Updated self-monitoring dashboard.
  • IMPROVEMENT: Reverted back default bind address for /metrics server to, as vmanomaly is distributed in Docker images.
  • IMPROVEMENT: Silenced Prophet INFO logs about yearly seasonality.


Released: 2023-03-19

  • FIX: Fix for metric label to pass QUERY_KEY.
  • FEATURE: Added timeout config param to reader, writer, monitoring.push.
  • FIX: Don’t hang if scheduler-model thread exits.
  • FEATURE: Now reader, writer and monitoring.push will not halt the process if endpoint is inaccessible or times out, instead they will increment metrics *_response_count{code=~"timeout|connection_error"}.


Released: 2023-02-18

  • FIX: Fixed scheduler thread starting.
  • FIX: Fix rolling model fit+infer.
  • BREAKING CHANGE: monitoring.pull server now binds by default on instead of Please specify explicitly in monitoring.pull.addr what IP address it should bind to for serving /metrics.


Released: 2023-02-04

  • FEATURE: With arg --watch watches for config(s) changes and reloads the service automatically.
  • IMPROVEMENT: Remove “provide_series” from HoltWinters model. Only Prophet model now has it, because it may produce a lot of series if “holidays” is on.
  • IMPROVEMENT: if Prophet’s “provide_series” is omitted, then all series are returned.
  • DEPRECATION: Config monitoring.endpount_url is deprecated in favor of monitoring.url.
  • DEPRECATION: Remove ’enable’ param from config monitoring.pull. Now /metrics server is started whenever monitoring.pull is present.
  • IMPROVEMENT: include example configs into the docker image at /vmanomaly/config/*
  • IMPROVEMENT: include self-monitoring grafana dashboard into the docker image under /vmanomaly/dashboard/vmanomaly_grafana_dashboard.json


Released: 2023-01-23

  • IMPROVEMENT: update Python dependencies
  • FEATURE: Add multivariate IsolationForest model.


Released: 2023-01-06

  • FIX: prophet model incorrectly predicted two points in case of only one


Released: 2022-12-08

  • First public release is available