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docs: vmanomaly - release v1.15.2 (#6802)
### Describe Your Changes update vmanomaly docs to forthcoming release v1.15.2 ### Checklist The following checks are **mandatory**: - [x] My change adheres [VictoriaMetrics contributing guidelines](https://docs.victoriametrics.com/contributing/).
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@ -13,6 +13,13 @@ Please find the changelog for VictoriaMetrics Anomaly Detection below.
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> **Important note: Users are strongly encouraged to upgrade to `vmanomaly` [v1.9.2](https://hub.docker.com/repository/docker/victoriametrics/vmanomaly/tags?page=1&ordering=name) or newer for optimal performance and accuracy. <br><br> This recommendation is crucial for configurations with a low `infer_every` parameter [in your scheduler](./components/scheduler.md#parameters-1), 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. <br><br> 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](https://github.com/VictoriaMetrics/helm-charts/blob/master/charts/victoria-metrics-anomaly/CHANGELOG.md#100) or newer.**
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## v1.15.2
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Released: 2024-08-13
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- IMPROVEMENT: Enhanced [online models](https://docs.victoriametrics.com/anomaly-detection/components/models/#online-models) (e.g., [`OnlineQuantileModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#online-seasonal-quantile)) to automatically create model instances for unseen time series during `infer` calls, eliminating the need to wait for the next `fit` call. This ensures no inferences are skipped **when using online models**.
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- FIX: Corrected an issue with the [`OnlineMADModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#online-mad) to ensure proper functionality when used in combination with [on-disk model dump mode](https://docs.victoriametrics.com/anomaly-detection/faq/#resource-consumption-of-vmanomaly).
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- FIX: Addressed numerical instability in the [`OnlineQuantileModel`](https://docs.victoriametrics.com/anomaly-detection/components/models/#online-seasonal-quantile) when `use_transform` is set to `True`.
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- FIX: Resolved a logging issue that could cause a `RuntimeError: reentrant call inside <_io.BufferedWriter name='<stderr>'>` when a termination event was received.
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## v1.15.1
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Released: 2024-08-10
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- FEATURE: Introduced backward-compatible `data_range` [query-specific parameter](https://docs.victoriametrics.com/anomaly-detection/components/reader/#per-query-parameters) to the [VmReader](https://docs.victoriametrics.com/anomaly-detection/components/reader/#vm-reader). It enables the definition of **valid** data ranges for input per individual query in `queries`, resulting in:
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@ -11,12 +11,15 @@ aliases:
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- /anomaly-detection/components/models/custom_model.html
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- /anomaly-detection/components/models/models.html
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---
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This section describes `Models` component of VictoriaMetrics Anomaly Detection (or simply [`vmanomaly`](../Overview.md)) and the guide of how to define a respective section of a config to launch the service.
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- `vmanomaly` includes various [built-in models](#built-in-models).
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- you can also integrate your custom model - see [custom model](#custom-model-guide).
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This section covers the `Models` component of VictoriaMetrics Anomaly Detection (commonly referred to as [`vmanomaly`](../Overview.md)) and provides a guide on how to configure the service.
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- `vmanomaly` includes various **[built-in models](#built-in-models)**.
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- You can also integrate a **custom model**—see the [custom model guide](#custom-model-guide) for more details.
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- Models have **different types and properties**—refer to the [model types section](#model-types) for more information.
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> **Note: Starting from [v1.10.0](../CHANGELOG.md#v1100) model section in config supports multiple models via aliasing. <br>Also, `vmanomaly` expects model section to be named `models`. Using old (flat) format with `model` key is deprecated and will be removed in future versions. Having `model` and `models` sections simultaneously in a config will result in only `models` being used:**
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> **Note:** Starting from [v1.13.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1130), models can be dumped to disk instead of being stored in RAM. This option **slightly reduces inference speed but significantly decreases RAM usage**, particularly useful for larger setups. For more details, see the [relevant FAQ section](https://docs.victoriametrics.com/anomaly-detection/faq/#resource-consumption-of-vmanomaly).
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> **Note:** Starting from [v1.10.0](https://docs.victoriametrics.com/anomaly-detection/changelog/#v1100) model section in config supports multiple models via aliasing. <br>Also, `vmanomaly` expects model section to be named `models`. Using old (flat) format with `model` key is deprecated and will be removed in future versions. Having `model` and `models` sections simultaneously in a config will result in only `models` being used:
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```yaml
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models:
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