Monitor API call frequencies for system health and performance insights.

The API Usage table serves as an important tool for businesses aiming to monitor the regularity of their API calls. Businesses can maintain peak system health and performance with consistent oversight of this table. Every record in this table offers insights into API call patterns, enabling businesses to discern the utilization of their APIs and pinpoint potential areas of concern or inefficiency.

Table Overview

Name: api_usage

Column NameData TypeDescription
idIntegerUnique identifier for each record in the table.
updated_atDateDate indicating the last update to the record.
environment_idIntegerUnique ID associated with a specific environment.
environment_nameStringDescriptive name of the environment, e.g., Production. Note: Only data from the production environment is shared in this table.
property_idIntegerUnique ID representing a specific property.
property_nameStringDescriptive name associated with the property ID.
date_yyyymmddDateDate presented in a standard format (year/month/day).
date_yearIntegerExtracted year from the date.
date_monthIntegerExtracted month from the date.
date_weekIntegerWeek number derived from the date.
loginIntegerNumber of times the Login API was invoked, capturing user authentication attempts.
registerIntegerNumber of times the Register API was invoked, indicating user registration attempts.
otp-sendIntegerNumber of times the Send OTP API was invoked, reflecting two-factor authentication or verification processes.
otp-verifyIntegerNumber of times the Verify OTP API was invoked, showing successful OTP verifications.
forgot-passwordIntegerNumber of times the Forgot Password API was invoked, indicating users who have requested password resets.
pre-registerIntegerNumber of times the Pre-Register API was invoked, capturing preliminary registration steps.
tokenIntegerNumber of times the Token API was invoked, indicating token generation or validation requests.
logoutIntegerNumber of times the Logout API was invoked, capturing user logout actions.
resend-verificationIntegerNumber of times the Resend Verification API was invoked, indicating users who requested another verification email or code.
check-password-strengthIntegerNumber of times the check-password-strength API was invoked, reflecting user password strength checks.

Main Sample Data

idenvironment_idenvironment_nameproperty_idproperty_nameloginregisterotp-sendotp-verifyforgot-passwordpre-registertokenlogoutresend-verificationcheck-password-strength
2g57o...xztklm1b3cPRODUCTION2e986v0kaHelix Digital Twist72068863261990050554967254
3h68p...xztklm1b3cPRODUCTION3f097w1lbInfinity Digital Loop654085393132441734356673184
4i79q...xztklm1b3cPRODUCTION4g108x2mcNova Digital Burst5945388301221709891257810

Note: Only a snippet of the table is shown for brevity.

Additional Date Information

For those interested in the date-related data, here's an example of how the omitted columns would appear:

updated_atdate_yyyymmdddate_yeardate_monthdate_week
2023-08-182023-07-312023731

Use Cases

API Performance Monitoring:
By analyzing the API Usage table, businesses can identify high-traffic APIs and ensure they are optimized for performance, ensuring smooth user experiences.

Security Analysis:
Discrepancies between API calls, like many login attempts with fewer successful logins, can indicate potential security threats or brute force attacks.

System Optimization:
Identifying APIs with low usage can help businesses decide on deprecating certain features or reallocating resources to more frequently used APIs.

User Behavior Insights:
A high number of forgot-password or resend-verification calls can indicate areas where users face challenges, guiding UX improvements.

Frequently Asked Questions (FAQs)

Q: Why are there more login calls than successful_logins in the related tables?
A: This could be due to multiple reasons, including incorrect password entries, system issues, or potential security threats like brute force attacks.

Q: How can I correlate the API Usage data with user activities?
A: The API Usage table can be used in conjunction with tables like User Activity Totals or Detailed User Activities & Drop-offs to understand the relationship between API calls and user activities.

Q: Are the API calls in the API Usage table real-time?
A: The API Usage table is updated regularly, but there might be a slight delay. It's recommended to check the updated_at column for the latest update timestamp.

Q: What are the implications of high API usage?
A: High API usage might indicate increased system interactions, which could lead to higher costs or resource constraints.

Q: How to optimize API calls?
A: API calls can be optimized by caching frequent requests, using pagination, and ensuring efficient frontend-backend communication.

Related Tables

For a more comprehensive understanding, explore related insights in:


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Do you still have questions?

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