Stop guessing about usage of your web API

Get insights in trends, bottlenecks and errors in a simple intuitive interface

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See your API health in seconds

Dougnut chart of http status codes returned

Important health KPIs such as response time and HTTP error counts provide immediate feedback. Filter by user agent to find API users that might need your help with using the API. Identify authentication problems or moments of degraded service using the time period filter.

Find most used parts of your API

See which API calls are used most and make your systems more efficient by optimizing them. Filter by period or use filters on path or HTTP method to segment the data futher. Using filter on user agent you'll even be able to see which customers use which parts of your API the most.

Most used calls list
“We use Callcounter to quickly get meaningful insights in the usage of our API's. An invaluable tool!”
Michel Fiege

Michel Fiege
Co-owner at Ivaldi

Find slow calls and bottlenecks

Analyse the response times of the API you develop to find slow outliers and bottlenecks. Optimising these will make your product more efficient while also retaining more users.

Identify possible timeout problems when average response times in seconds exceed single digits. Especially with mobile or other interactive apps it is important to keep API responses as fast as possible. Callcounter helps you identify slow parts of your web API that need to be optimised.

Table with the slowest responses tracked

Discover usage trends and plan around peak times

Discover trends in API usage such as workweek rhythm or seasonal influence by evaluating API usage in line graphs. This can be used to schedule your planned maintenance in a quiet period or scale server resources at peak moments.

Filter by user agent to find misbehaving clients or help customers that have problems integrating with your API.

Request count line chart

Segment users based on their used technology

Table of user agents with the most requests

Understand your customers better by filtering on their user agents. This is a GDPR safe method to get valuable insights while protecting user privacy. User agents are not considered to be Personal Identifiable Information.

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