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Ridwan Halim

How Usage Monitoring Sustains MLBB-Stats and API-PDDIKTI

How Usage Monitoring Sustains MLBB-Stats and API-PDDIKTI

Following an earlier announcement about potential API shutdowns, mlbb-stats.ridwaanhall.com and api-pddikti.ridwaanhall.com will now remain online thanks to a practical threshold-based control system.

Each API tracks core resource usage—Function Duration, Edge Requests, Image Optimization, and more. If usage nears a specific limit (e.g. 95 GB-Hours out of 100), service is flagged for temporary deactivation. However, unlike automated systems, activation and deactivation remain manually controlled via backend logic—giving developers flexibility while preserving stability.

This manual switching doesn’t interrupt active requests or user experience. It enables the APIs to remain responsive under heavy load, while administrators oversee usage patterns and toggle service availability when needed.

Below is the current usage snapshot used to monitor thresholds:

Metric Limit Threshold Maximum Quota
Function Duration 95 GB-Hrs 100 GB-Hrs
Edge Requests 950K 1M
Function Invocations 950K 1M
Fast Origin Transfer 9.5 GB 10 GB
ISR Reads 950K 1M
Fast Data Transfer 95 GB 100 GB
Image Optimization - Transformations 4.75K 5K
Edge Middleware Invocations 950K 1M
Image Optimization - Cache Writes 95K 100K
Image Optimization - Cache Reads 285K 300K

Thresholds are defined just below the maximum to give room for healthy operation. As long as usage remains under these limits, the APIs stay online and stable.

Users and developers are encouraged to continue supporting via Saweria, Sociabuzz, or GitHub Sponsors. But thanks to this measured resource model, both APIs remain online—driven by sustainable usage, not shutdown.

Tags

#threshold-system #manual-control #api-sustainability #open-data