What tools does this skill use for load testing?

The skill primarily utilizes k6 for load testing and kubectl for configuring Kubernetes Horizontal Pod Autoscaling (HPA) and resource management.

What metrics are included in the capacity recommendations?

It provides empirical data on throughput (RPS), P95/P99 latency percentiles, error rates, and peak connection counts to define safe operational limits.

Can this skill help prevent database connection exhaustion?

Yes, it specifically focuses on aligning your application's HPA scaling policies with your Supabase connection pool size to ensure replicas don't overwhelm the database.

Does it support both read and write testing?

Absolutely. The skill is designed to model realistic traffic patterns including both read-heavy and write-heavy scenarios to stress different parts of the Supabase stack.

Supabase Performance & Scaling

Name: Supabase Performance & Scaling
Author: micsapp

bymicsapp

0•

데이터베이스 관리

Optimizes Supabase performance through comprehensive load testing, horizontal auto-scaling, and proactive capacity planning.

The Supabase Load Scale skill empowers developers to architect resilient database integrations by automating the creation of k6 load testing scripts and configuring Kubernetes Horizontal Pod Autoscaling (HPA). It bridges the gap between application performance and database-level constraints by analyzing connection pooling, query latency, and rate limits under stress. Whether preparing for a product launch or managing rapid growth, this skill provides the empirical data and configuration strategies needed to scale Supabase environments reliably without exceeding connection limits or compromising SLAs.

주요 기능

010 GitHub stars

02Performance benchmarking with structured capacity recommendations

03Automated k6 load test script generation for realistic traffic patterns

04Analysis of connection pooling behavior and rate limit thresholds

05Real-time monitoring of P95/P99 latency and database-level metrics

06Kubernetes HPA configuration optimized for Supabase connection limits

사용 사례

01Identifying database query bottlenecks and connection exhaustion points before outages

02Preparing for high-traffic launches by benchmarking application-to-Supabase performance

03Configuring auto-scaling policies that align with Supabase database connection pools

주요 기능

010 GitHub stars

02Performance benchmarking with structured capacity recommendations

03Automated k6 load test script generation for realistic traffic patterns

04Analysis of connection pooling behavior and rate limit thresholds

05Real-time monitoring of P95/P99 latency and database-level metrics

06Kubernetes HPA configuration optimized for Supabase connection limits

사용 사례

01Identifying database query bottlenecks and connection exhaustion points before outages

02Preparing for high-traffic launches by benchmarking application-to-Supabase performance

03Configuring auto-scaling policies that align with Supabase database connection pools