Setting up Custom metrics

As APIs play a crucial role in your daily business, platform, and service operations, it is essential to regularly check their behavior and perform data validation. This article explains how you can use Custom Metrics to monitor your API’s uptime, capture data, and visually display that data in real-time charts or lists for analysis.

Custom metrics is a feature available in Multi-step API (MSA) monitors that allows you to capture specific numerical data from any internal or external API. From each captured data point, you can store these values in a Custom metric variable to visually display how data progresses over time.

Why use Custom metrics

Imagine you have an API for your e-commerce system that provides real-time information about your product catalog. This includes pricing details, product inventory, and other product information.

Let’s say you want to keep track of the number of stocks per product. Instead of manually calling the API every time, Custom metrics automatically retrieve this data from the API response and store each data point in Custom metric variables :

Every time the MSA monitor runs, it continuously tracks the values of the variables. From there, you can create a Custom metrics list or chart for further data or trend analysis, or to monitor your business reports and operational performance:

There are also various ways to use Custom metrics in different contexts:

• For DevOps, you can easily monitor the health of your system or application by tracking metrics such as the number of errors logged, concurrent users, and network speed.
• For IT operations, you can monitor data center environment metrics like temperature, humidity, and system health.
• For IT support, you can track the number of support calls waiting on hold, the number of tickets, and SLA performance.

Set up Custom metrics

Once you’ve set up an MSA monitor with a single or multi-step definition, you can set up Custom metrics in two ways: Set using a variable or Set using scripting .

Note that when creating a new custom metric, use a metric name that is easy to read and provides context for its function. The metrics names and monitor names will appear in the list of available custom metrics once they are added to your Custom API data report. Therefore, you can use the same custom metric names to represent similar types of data belonging to different groups. For example, a custom metric called totalSum might be used in both product-related APIs and customer-related APIs. Although the name is the same, the data it represents are from different groups. Uptrends recommends giving the correct names right away. Renaming a custom metric later will be treated as creating a new and different metric.

Set using a variable

Let’s set up Custom metrics using the Carbon API as an example. To track the Carbon intensity data using the variable method:

Set using scripting

Let’s set up Custom metrics using the Carbon API as an example. To track the Carbon forecast data using the scripting method:

To know more about snippets and scripting, refer to Multi-step API (MSA) custom scripting .

Inspect the Custom metric data

Once set up, inspect your Custom metrics data to ensure that the monitor captures and tracks the data correctly.

To inspect the Custom metrics data you’re tracking:

1. Go to the API > API monitors setup.
2. Click the Go to dashboard link for the monitor where you created the Custom metric.
3. In the Monitor log tile, click anywhere on a row to open the Check details popup.

From the popup, you can view the Custom metrics data retrieved from the monitor check. Notice that the CarbonIntensity value is 85:

This gives you direct access to the individual custom metric values as they were captured during the execution of the MSA monitor.

If you don’t see any Custom metrics value, consider the following:

• Did you accidentally open check results for an older check that was executed before the new custom metric was defined?

• Is your Custom metric capturing numeric integer data? If it contains text data or non-integer numbers (such as 99.9% or 3.1415), it won’t be captured. Currently, only integer numbers are supported.

• If something went wrong during the execution of the MSA monitor, the variable assigned to your custom metric may not have been created. Check for any typos in the custom metric name or variables.

Display Custom metrics in dashboards

If you may want to dig deeper and work with the underlying data to precisely detect sudden spike in the values, you can display the Custom metrics data in your dashboard using the Custom metrics list or chart:

This allows you to see the metric variable’s trend over time, displaying its minimum, average, and maximum values. For more information, refer to Custom metrics list or chart .

You can also export the Custom metric list or chart data in different data format through the Exporting dashboard data feature.