Metricbase

Access the time-series data that you sent to the MetricBase database in the way that is convenient to you.

Use JavaScript or REST APIs to insert and retrieve time-series data from the MetricBase database and to run transforms on the data. The transformations enable you to visualize time-series data in a variety of ways.

Now that you created a trigger, use Workflow Studio to specify the flow a trigger executes. The flows can provide alerts for unexpected behavior.

Store time-series summaries of much larger data collections.

Plan and configure your MetricBase implementation.

MetricBase triggers execute based on a single metric. Condition Scripts impose additional requirements that determine whether a trigger kicks off a flow.

Create a MetricBase linear predictor trigger to detect when a metric is likely to cross a specified threshold within a specified period of time.

Create a MetricBase band trigger that detects when a metric value falls within a range of values.

Create a MetricBase gap trigger to alert you when MetricBase stops receiving data.

Model triggers execute when the time-series data deviates from expected values.

Developers can use JavaScript or REST APIs to insert and retrieve time-series data from the MetricBase database and to run transforms on the data. The transformations enable you to visualize time-series data in a variety of ways.

Domain separation is supported in the MetricBase application. Domain separation enables you to separate data, processes, and administrative tasks into logical groupings called domains. You can control several aspects of this separation, including which users can see and access data.

Collect, retain, analyze, and act on time-series data using MetricBase.

After ServiceNow personnel install the MetricBase and MetricBase Demo plugins, you can use the demo to get familiar with MetricBase.

View the overall health and performance of MetricBase, and debug its triggers and scripts.

Experiment with MetricBase APIs using Data Explorer that is part of the MetricBase Demo application. Data Explorer uses the data installed with the MetricBase Demo application.

MetricBase creates a model by training a representative sample of your time series data to determine the model parameters. The training process determines the model parameters that best fit your data, to distinguish normal data from anomalous data.

Retain data in MetricBase according to retention policies.

Specify how long MetricBase stores the time-series data in the MetricBase database.

MetricBase is installed with these roles.

Time-series data that is stored in the MetricBase database can trigger Workflow Studio flows. These triggers can log incidents, send emails, and create other alerts.

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 Workflow Studio flows.

These reference topics provide additional information about MetricBase developer resources and domain separation.

The MetricBase plugin [com.snc.clotho] requires a separate subscription and must be activated by ServiceNow personnel. Be sure to also request the MetricBase Demo plugin [com.snc.clotho.demo], which includes sample tables, metrics, triggers, and data.

Specify the metric that you want to store, how often to collect it, and how long to store it in MetricBase.

Use statistical models to determine significant anomalies in real-time using MetricBase triggers. You will need to train a model using representative data that has already been stored in MetricBase.

Use the list command on a table in the MetricBase database to view time-series data. The data reveals the behavior of the entity that supplies the data.

Trigger logs show different levels of trigger malfunctions.

Familiarize yourself with MetricBase by exploring the MetricBase demo.