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    MetricBase

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    MetricBase

    The MetricBase application stores time-series data, which is data that is sampled at regular intervals. You can graph the stored data or use it with triggers to execute Flow Designer flows. MetricBase helps developers working with IoT-based applications that monitor or act on large amounts of machine-generated data.

    How MetricBase works

    You use MetricBase to deal with large amounts of data by using a smaller summary of that data that is stored in the MetricBase database. For example, an instance might store CPU usage. With MetricBase, you might summarize that data by storing the average CPU usage for every five-minute interval. You can graph the data or you can use it with Flow Designer to trigger flows.

    MetricBase works with:
    • An instance that stores machine-generated data
    • A server that has the MetricBase application and database
    On a very high level, when using MetricBase, you can:
    1. Define the sampling rate for the data (float) on an instance. For example, you can sample the machine-generated data that is stored on an instance once every five minutes. This sampling rate is called the time-series definition.
    2. Use a MetricBase API to send data from the instance to the MetricBase database at the rate that is prescribed by the time-series definition. If you send the data to MetricBase at a different rate, you get an error.
    3. Use the Reporting application to graph the time-series data that is stored in MetricBase, or create triggers that execute Flow Designer flows. The time-series data remains in the MetricBase database for a prescribed amount of time, after which MetricBase deletes the data.
    Storing time series data

    This figure shows that machine-generated data is sampled every 4 seconds. You send the average of the values in each sampling period to the MetricBase database, which stores the data until its expiration date.

    Benefits

    • MetricBase integrates seamlessly with ServiceNow IoT-based applications that monitor or act on large amounts of machine-generated data.
    • MetricBase collects, retains, analyzes, graphs, and acts on time-series data.
    • MetricBase works with Flow Designer to trigger flows and with Reporting to generate reports.

    Use cases

    • Create graphs about metrics, such as about CPU usage over time.
    • Generate an email if the average CPU usage is more than 85% in the last 5 minutes.
    • Train a machine language model to detect anomalies and execute a Flow Designer trigger when an anomaly is detected.
    • If MetricBase detects a gap in data submitted for 10 minutes or more, generate an email.
    • If the average of the collected data is less than 10 or greater than 500 in the last 5 minutes, generate an alert.
    • If memory usage is likely to exceed 90% in the next 10 minutes, generate an alert.

    MetricBase demo

    Use the MetricBase Demo plugin to familiarize yourself with MetricBase. The demo contains sample metrics, triggers, and a scheduled job that collects and stores data. Use the demo to explore MetricBase before you set it up. The Data Explorer, which comes with the demo plugin, provides a place to experiment with MetricBase JavaScript APIs. The demo plugin is separate from the MetricBase plugin. Make sure to request both.

    Next

    Request the installation of the MetricBase and MetricBase Demo plugins.

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    Release version
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      MetricBase

      • Save as PDF Selected topic Topic & subtopics All topics in contents
      • Unsubscribe Log in to subscribe to topics and get notified when content changes.
      • Share this page

      MetricBase

      The MetricBase application stores time-series data, which is data that is sampled at regular intervals. You can graph the stored data or use it with triggers to execute Flow Designer flows. MetricBase helps developers working with IoT-based applications that monitor or act on large amounts of machine-generated data.

      How MetricBase works

      You use MetricBase to deal with large amounts of data by using a smaller summary of that data that is stored in the MetricBase database. For example, an instance might store CPU usage. With MetricBase, you might summarize that data by storing the average CPU usage for every five-minute interval. You can graph the data or you can use it with Flow Designer to trigger flows.

      MetricBase works with:
      • An instance that stores machine-generated data
      • A server that has the MetricBase application and database
      On a very high level, when using MetricBase, you can:
      1. Define the sampling rate for the data (float) on an instance. For example, you can sample the machine-generated data that is stored on an instance once every five minutes. This sampling rate is called the time-series definition.
      2. Use a MetricBase API to send data from the instance to the MetricBase database at the rate that is prescribed by the time-series definition. If you send the data to MetricBase at a different rate, you get an error.
      3. Use the Reporting application to graph the time-series data that is stored in MetricBase, or create triggers that execute Flow Designer flows. The time-series data remains in the MetricBase database for a prescribed amount of time, after which MetricBase deletes the data.
      Storing time series data

      This figure shows that machine-generated data is sampled every 4 seconds. You send the average of the values in each sampling period to the MetricBase database, which stores the data until its expiration date.

      Benefits

      • MetricBase integrates seamlessly with ServiceNow IoT-based applications that monitor or act on large amounts of machine-generated data.
      • MetricBase collects, retains, analyzes, graphs, and acts on time-series data.
      • MetricBase works with Flow Designer to trigger flows and with Reporting to generate reports.

      Use cases

      • Create graphs about metrics, such as about CPU usage over time.
      • Generate an email if the average CPU usage is more than 85% in the last 5 minutes.
      • Train a machine language model to detect anomalies and execute a Flow Designer trigger when an anomaly is detected.
      • If MetricBase detects a gap in data submitted for 10 minutes or more, generate an email.
      • If the average of the collected data is less than 10 or greater than 500 in the last 5 minutes, generate an alert.
      • If memory usage is likely to exceed 90% in the next 10 minutes, generate an alert.

      MetricBase demo

      Use the MetricBase Demo plugin to familiarize yourself with MetricBase. The demo contains sample metrics, triggers, and a scheduled job that collects and stores data. Use the demo to explore MetricBase before you set it up. The Data Explorer, which comes with the demo plugin, provides a place to experiment with MetricBase JavaScript APIs. The demo plugin is separate from the MetricBase plugin. Make sure to request both.

      Next

      Request the installation of the MetricBase and MetricBase Demo plugins.

      Tags:

      Feedback

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