Exploring MetricBase
Summarize
Summary of Exploring MetricBase
MetricBase enables ServiceNow customers to collect, store, analyze, and act on large volumes of time-series data efficiently by summarizing machine-generated data in a specialized database. It integrates seamlessly with ServiceNow IoT applications, allowing users to monitor metrics such as CPU usage or memory consumption and trigger automated workflows based on the data.
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Key Features
- Data Collection and Storage: MetricBase collects time-series data at defined intervals (e.g., every 4 seconds), stores summarized averages in its database, and retains this data for a configurable period before automatic deletion.
- Integration with Workflow Studio: Users can configure triggers that initiate flows based on specific data conditions, such as high CPU usage or data submission gaps.
- Visualization: Time-series data in MetricBase can be visualized using charts within the platform’s Reporting application, enhancing monitoring and analysis.
- Anomaly Detection: MetricBase supports training machine learning models to detect anomalies in the data and trigger workflows when deviations occur.
- APIs for Data Interaction: Data can be sent to MetricBase via REST or JavaScript APIs, enabling automated data ingestion and retrieval.
Practical Usage and Benefits
- Administrators define metrics, configure data collection schedules, set up triggers, and manage anomaly detection models to automate responses to critical events.
- Developers use available APIs to insert and retrieve time-series data, facilitating integration with other systems or custom applications.
- Automated alerts and flows can be set up to send emails, log incidents, or generate other notifications when thresholds or anomalies are detected, improving operational responsiveness.
Next Steps
To effectively implement MetricBase, customers should explore detailed guidance on configuring MetricBase, defining and collecting data, managing triggers for workflows, and maintaining the system. This enables leveraging MetricBase’s full capabilities for time-series data analysis and operational automation.
Collect, retain, analyze, and act on time-series data using MetricBase.
MetricBase overview
MetricBase helps you work with large amounts of data by using a smaller summary of that data that is stored in the MetricBase database.
- Integrate MetricBase seamlessly with ServiceNow IoT-based applications that monitor or act on large amounts of machine-generated data.
- Trigger flows in Workflow Studio based on time-series data in MetricBase.
- Generate an email if the average CPU usage is more than 85% in the last 5 minutes.
- Generate an email if MetricBase detects a gap in data submitted for 10 minutes or more.
- Generate an alert 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.
- Visualize MetricBase data using time-series charts.
- Use the Reporting application to graph the time-series data that is stored in MetricBase.
- Detect anomalies by training a machine language model and execute a Workflow Studio trigger when an anomaly is detected.
- An instance that stores machine-generated data
- A server that has the MetricBase application and database
MetricBase users
| User | Description |
|---|---|
| Administrator | An administrator collects, retains, analyzes, and acts on time-series data using MetricBase. |
MetricBase workflow
The following 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.
- The administrator specifies a metric to store and how often to collect it by creating a time-series definition in MetricBase.
- The administrator sends data from the instance to the MetricBase server using the MetricBase REST or JavaScript APIs.
- The administrator configures trigger definitions that execute flows based on time-series data in MetricBase.
- The administrator configures and trains predictive models in MetricBase to detect anomalies and execute flows when new data is significantly different than the trained data.
- The administrator monitors collected data using time-series charts in MetricBase. Time-series data remains in the MetricBase database for a prescribed amount of time, after which MetricBase deletes the data.
MetricBase benefits
| Benefit | Feature | Users |
|---|---|---|
| Store time series summary of a large collection of data | Create a time-series definition in MetricBase | Administrator |
| Insert and retrieve time-series data from the MetricBase database | Developer resources | Administrator |
| Access and visualize time-series data in the MetricBase database | Accessing MetricBase data | Administrator |
| Trigger flows when new data is significantly different than the trained data | Detecting anomalies in MetricBase data using predictive models | Administrator |
| Trigger flows that can log incidents, send emails, and create other alerts | Triggering flows using MetricBase data | Administrator |