Automated monitoring checks

Last modified on 27-Sep-23

Use automated monitoring checks to instruct Soda to automatically check for row count anomalies and schema changes in a dataset.

automated monitoring:
  datasets:
    - include %
    - exclude test%

About automated monitoring checks
Prerequisites
Define an automated monitoring check
Optional check configurations
Go further

About automated monitoring checks

When you add automated monitoring checks to your checks.yml file, Soda Library prepares and executes two checks on all the datasets you indicate as included in your checks YAML file.

Anomaly score check on row count: This check counts the number of rows in a dataset during scan and registers anomalous counts relative to previous measurements for the row count metric. Refer to Anomaly score checks for details.
Anomaly score checks require a minimum of four data points (four scans at stable intervals) to establish a baseline against which to gauge anomalies. If you do not see check results immediately, allow Soda Library to accumulate the necessary data points.

Schema checks: This check monitors schema changes in datasets, including column addition, deletion, data type changes, and index changes. By default, this automated check results in a failure if a column is deleted, its type changes, or its index changes; it results in a warning if a column is added. Refer to Schema checks for details.
Schema checks require a minimum of one data point to use as a baseline against which to gauge schema changes. If you do not see check results immediately, wait until after you have scanned the dataset twice.

These types of checks require a Soda Cloud account. Soda Library pushes check results to your account where Soda Cloud stores all the previously-measured, historic values for your checks in the Cloud Metric Store. SodaCL can then use these stored values to establish a relative state against which to evaluate future schema and anomaly score checks.

Prerequisites

pip install -i https://pypi.cloud.soda.io soda-scientific

pip install -i https://pypi.cloud.soda.io soda-scientific

Use Docker to run Soda Library

Use Soda’s Docker image in which Soda Scientific is pre-installed.

1. If you have not already done so, install Docker in your local environment.
2. From Terminal, run the following command to pull Soda Library’s official Docker image; adjust the version to reflect the most recent release.

   docker pull sodadata/soda-library:v1.0.3
   

3. Verify the pull by running the following command.

   docker run sodadata/soda-library:v1.0.3 --help
   

   Output:

    Usage: soda [OPTIONS] COMMAND [ARGS]...
   
      Soda Library CLI version 1.0.x, Soda Core CLI version 3.0.xx
   
    Options:
      --version  Show the version and exit.
      --help     Show this message and exit.
   
    Commands:
      ingest           Ingests test results from a different tool
      scan             Runs a scan
      suggest          Generates suggestions for a dataset
      test-connection  Tests a connection
      update-dro       Updates contents of a distribution reference file
   

   When you run the Docker image on a non-Linux/amd64 platform, you may see the following warning from Docker, which you can ignore.

   WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested
   

4. When you are ready to run a Soda scan, use the following command to run the scan via the docker image. Replace the placeholder values with your own file paths and names.

   docker run -v /path/to/your_soda_directory:/sodacl sodadata/soda-library scan -d your_data_source -c /sodacl/your_configuration.yml /sodacl/your_checks.yml
   

   Optionally, you can specify the version of Soda Library to use to execute the scan. This may be useful when you do not wish to use the latest released version of Soda Library to run your scans. The example scan command below specifies Soda Library version 1.0.0.

   docker run -v /path/to/your_soda_directory:/sodacl sodadata/soda-library:v1.0.0 scan -d your_data_source -c /sodacl/your_configuration.yml /sodacl/your_checks.yml
   

Error: Mounts denied

If you encounter the following error, follow the procedure below.

docker: Error response from daemon: Mounts denied: 
The path /soda-library-test/files is not shared from the host and is not known to Docker.
You can configure shared paths from Docker -> Preferences... -> Resources -> File Sharing.
See https://docs.docker.com/desktop/mac for more info.

You need to give Docker permission to acccess your configuration.yml and checks.yml files in your environment. To do so:

1. Access your Docker Dashboard, then select Preferences (gear symbol).
2. Select Resources, then follow the Docker instructions to add your Soda project directory – the one you use to store your configuration.yml and checks.yml files – to the list of directories that can be bind-mounted into Docker containers.
3. Click Apply & Restart, then repeat steps 2 - 4 above.

Error: Configuration path does not exist

If you encounter the following error, double check the syntax of the scan command in step 4 above.

• Be sure to prepend /sodacl/ to both the congifuration.yml filepath and the checks.yml filepath.
• Be sure to mount your files into the container by including the -v option. For example, -v /Users/MyName/soda_project:/sodacl.

Soda Library 1.0.x
Configuration path 'configuration.yml' does not exist
Path "checks.yml" does not exist
Scan summary:
No checks found, 0 checks evaluated.
2 errors.
Oops! 2 errors. 0 failures. 0 warnings. 0 pass.
ERRORS:
Configuration path 'configuration.yml' does not exist
Path "checks.yml" does not exist

Define an automated monitoring check

In the context of SodaCL check types, automated monitoring checks are unique. This check employs the anomaly score and schema checks, but is limited in its syntax variation, with only a couple of mutable parts to specify which datasets to automatically apply the anomaly and schema checks.

The example check below uses a wildcard character (%) to specify that Soda Library executes automated monitoring checks against all datasets with names that begin with prod, and not to execute the checks against any dataset with a name that begins with test.

automated monitoring:
  datasets:
    - include prod%
    - exclude test%

You can also specify individual datasets to include or exclude, as in the following example.

automated monitoring:
  datasets:
    - include orders

Scan results in Soda Cloud

To review the check results for automated monitoring checks in Soda Cloud, navigate to the Checks dashboard to see the automated monitoring check results with an INSIGHT tag.

Optional check configurations

Example with wildcards

automated monitoring:
  datasets:
    - include prod%
    - exclude test%

Go further

• Need help? Join the Soda community on Slack.
• Reference tips and best practices for SodaCL.
• Use a freshness check to gauge how recently your data was captured.
• Use reference checks to compare the values of one column to another.

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• Suggest a docs change in GitHub.
• Share feedback in the Soda community on Slack.

Documentation always applies to the latest version of Soda products
Last modified on 27-Sep-23

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