diff --git a/docs/guides/guide-vmanomaly-vmalert.md b/docs/guides/guide-vmanomaly-vmalert.md
index c551fc3663..196219309b 100644
--- a/docs/guides/guide-vmanomaly-vmalert.md
+++ b/docs/guides/guide-vmanomaly-vmalert.md
@@ -13,12 +13,13 @@ aliases:
 **Prerequisites**
 - *vmanomaly* is a part of enterprise package. You can get license key [here](https://victoriametrics.com/products/enterprise/trial) to try this tutorial.
 - In the tutorial, we'll be using the following VictoriaMetrics components:
-  -  [VictoriaMetrics](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html) (v.1.93.2)
-  -  [vmalert](https://docs.victoriametrics.com/vmalert.html) (v.1.93.2)
-  -  [vmagent](https://docs.victoriametrics.com/vmagent.html) (v.1.93.2)
+  -  [VictoriaMetrics](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html) (v.1.96.0)
+  -  [vmalert](https://docs.victoriametrics.com/vmalert.html) (v.1.96.0)
+  -  [vmagent](https://docs.victoriametrics.com/vmagent.html) (v.1.96.0)
   
   If you're unfamiliar with the listed components, please read [QuickStart](https://docs.victoriametrics.com/Quick-Start.html) first.
-- It is assumed that you are familiar with [Grafana](https://grafana.com/)(v.9.3.1) and [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/).
+- It is assumed that you are familiar with [Grafana](https://grafana.com/)(v.10.2.1) and [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/).
+
 ## 1. What is vmanomaly?
 *VictoriaMetrics Anomaly Detection* ([vmanomaly](https://docs.victoriametrics.com/vmanomaly.html)) is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real-time. It does so by utilizing user-configurable machine learning models.
 
@@ -90,7 +91,7 @@ ______________________________
 
 ## 5. vmanomaly configuration and parameter description
 **Parameter description**:
-There are 4 main sections in config file:
+There are 4 required sections in config file:
 
 `scheduler` - defines how often to run and make inferences, as well as what timerange to use to train the model. 
 
@@ -113,9 +114,9 @@ Let's look into parameters in each section:
     Here is the previous 14 days of data to put into the model training. 
 
 * `model`
-    * `class` - what model to run. You can use your own model or choose from built-in models: Seasonal Trend Decomposition, Facebook Prophet, ZScore, Rolling Quantile, Holt-Winters and ARIMA.
+    * `class` - what model to run. You can use your own model or choose from built-in models: Seasonal Trend Decomposition, Facebook Prophet, ZScore, Rolling Quantile, Holt-Winters, Isolation Forest and ARIMA.  Here we use Facebook Prophet (`model.prophet.ProphetModel`).
     
-    Here we use Facebook Prophet with default parameters (`model.prophet.ProphetModel`). You can put parameters that are available in their [docs](https://facebook.github.io/prophet/docs/quick_start.html).
+    * `args` - Model specific parameters, represented as YAML dictionary in a simple `key: value` form. For example, you can use parameters that are available in [FB Prophet](https://facebook.github.io/prophet/docs/quick_start.html).
     
 * `reader`
   * `datasource_url` - Data source. An HTTP endpoint that serves `/api/v1/query_range`.
@@ -139,7 +140,8 @@ scheduler:
 
 model:
   class: "model.prophet.ProphetModel"
-  interval_width: 0.98
+  args:
+    interval_width: 0.98
 
 reader:
   datasource_url: "http://victoriametrics:8428/"
@@ -264,7 +266,6 @@ Let's wrap it all up together into the `docker-compose.yml` file.
 
 <div class="with-copy" markdown="1">
 
-{% raw %}
 ``` yaml
 services:
   vmagent:
@@ -286,7 +287,7 @@ services:
   
   victoriametrics:
     container_name: victoriametrics
-    image: victoriametrics/victoria-metrics:v1.93.2
+    image: victoriametrics/victoria-metrics:v1.96.0
     ports:
       - 8428:8428
       - 8089:8089
@@ -309,7 +310,7 @@ services:
   
   grafana:
     container_name: grafana
-    image: grafana/grafana-oss:9.3.1
+    image: grafana/grafana-oss:10.2.1
     depends_on:
       - "victoriametrics"
     ports:
@@ -346,7 +347,7 @@ services:
     restart: always
   vmanomaly:
     container_name: vmanomaly
-    image: us-docker.pkg.dev/victoriametrics-test/public/vmanomaly-trial:v1.5.0
+    image: us-docker.pkg.dev/victoriametrics-test/public/vmanomaly-trial:v1.7.2
     depends_on:
       - "victoriametrics"
     ports:
@@ -379,7 +380,6 @@ volumes:
 networks:
   vm_net:
 ```
-{% endraw %}
 
 </div>
 
diff --git a/docs/vmanomaly.md b/docs/vmanomaly.md
index 152d2b3ea0..17f10f355f 100644
--- a/docs/vmanomaly.md
+++ b/docs/vmanomaly.md
@@ -126,43 +126,67 @@ optionally preserving labels).
 
  
 ## Usage
-The vmanomaly accepts only one parameter -- config file path:
+> Starting from v1.5.0, vmanomaly requires a license key to run. You can obtain a trial license key [here](https://victoriametrics.com/products/enterprise/trial/).
 
-```sh
-python3 vmanomaly.py config_zscore.yaml
-```
-or
-```sh
-python3 -m vmanomaly config_zscore.yaml
-```
+> See [Getting started guide](https://docs.victoriametrics.com/guides/guide-vmanomaly-vmalert.html).
 
-It is also possible to split up config into multiple files, just list them all in the command line:
+### Config file
+There are 4 required sections in config file:
 
-```sh
-python3 -m vmanomaly model_prophet.yaml io_csv.yaml scheduler_oneoff.yaml
+* `scheduler` - defines how often to run and make inferences, as well as what timerange to use to train the model. 
+* `model` - specific model parameters and configurations, 
+* `reader` - how to read data and where it is located
+* `writer` - where and how to write the generated output.
+
+[`monitoring`](#monitoring) - defines how to monitor work of *vmanomaly* service. This config section is *optional*.
+
+#### Config example
+Here is an example of config file that will run FB Prophet model, that will be retrained every 2 hours on 14 days of previous data. It will generate inference (including `anomaly_score` metric) every 1 minute.
+
+
+You need to put your datasource urls to use it:
+
+```yaml
+scheduler:
+  infer_every: "1m"
+  fit_every: "2h"
+  fit_window: "14d"
+
+model:
+  class: "model.prophet.ProphetModel"
+  args:
+    interval_width: 0.98
+
+reader:
+  datasource_url: [YOUR_DATASOURCE_URL] #Example: "http://victoriametrics:8428/"
+  queries:
+    cache: "sum(rate(vm_cache_entries))"
+
+writer:
+  datasource_url: [YOUR_DATASOURCE_URL] # Example: "http://victoriametrics:8428/"
 ```
 
 ### Monitoring
 
-vmanomaly can be monitored by using push or pull approach.
+*vmanomaly* can be monitored by using push or pull approach.
 It can push metrics to VictoriaMetrics or expose metrics in Prometheus exposition format.
 
 #### Push approach
 
-vmanomaly can push metrics to VictoriaMetrics single-node or cluster version.
+*vmanomaly* can push metrics to VictoriaMetrics single-node or cluster version.
 In order to enable push approach, specify `push` section in config file:
 
 ```yaml
 monitoring:
    push:
-      url: "http://victoriametrics:8428/"
+      url: [YOUR_DATASOURCE_URL] #Example: "http://victoriametrics:8428/"
       extra_labels:
          job: "vmanomaly-push"
 ```
 
 #### Pull approach
 
-vmanomaly can export internal metrics in Prometheus exposition format at `/metrics` page.
+*vmanomaly* can export internal metrics in Prometheus exposition format at `/metrics` page.
 These metrics can be scraped via [vmagent](https://docs.victoriametrics.com/vmagent.html) or Prometheus.
 
 In order to enable pull approach, specify `pull` section in config file:
@@ -176,10 +200,30 @@ monitoring:
 
 This will expose metrics at `http://0.0.0.0:8080/metrics` page.
 
-### Licensing
+### Run vmanomaly Docker Container
 
-Starting from v1.5.0 vmanomaly requires a license key to run. You can obtain a trial license
-key [here](https://victoriametrics.com/products/enterprise/trial/).
+To use *vmanomaly* you need to pull docker image:
+
+```sh
+docker pull us-docker.pkg.dev/victoriametrics-test/public/vmanomaly-trial:latest
+```
+
+You can put a tag on it for your convinience:
+
+```sh
+docker image tag us-docker.pkg.dev/victoriametrics-test/public/vmanomaly-trial vmanomaly
+```
+Here is an example of how to run *vmanomaly* docker container with [license file](#licensing):
+
+```sh
+docker run -it --net [YOUR_NETWORK] \
+               -v [YOUR_LICENSE_FILE_PATH]:/license.txt \
+               -v [YOUR_CONFIG_FILE_PATH]:/config.yml \
+               vmanomaly /config.yml \
+               --license-file=/license.txt
+```
+
+### Licensing
 
 The license key can be passed via the following command-line flags:
 ```
@@ -194,10 +238,7 @@ The license key can be passed via the following command-line flags:
                         verification offline.
 ```
 
-Usage example:
-```
-python3 -m vmanomaly --license-file /path/to/license_file.yaml config.yaml
-```
+
 
 In order to make it easier to monitor the license expiration date, the following metrics are exposed(see
 [Monitoring](#monitoring) section for details on how to scrape them):
@@ -212,7 +253,7 @@ vm_license_expires_in_seconds 4.886608e+06
 ```
 
 Example alerts for [vmalert](https://docs.victoriametrics.com/vmalert.html):
-{% raw %}
+
 ```yaml
 groups:
   - name: vm-license
@@ -236,4 +277,4 @@ groups:
           description: "{{ $labels.instance }} of job {{ $labels.job }} license expires in {{ $value | humanizeDuration }}. 
             Please make sure to update the license before it expires."
 ```
-{% endraw %}
+