flow-pie/chamaa.api

Auto-scaling and worker management

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#80 opened on Nov 9, 2025

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good first issue

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Description

Setup auto-scaling and worker management for handling variable load.

Requirements:

  • Configure horizontal Pod autoscaling (HPA) for Kubernetes
  • Implement custom metrics for scaling decisions
  • Setup worker scaling for background jobs (RabbitMQ workers)
  • Configure scale-up and scale-down policies
  • Add monitoring for scaling events
  • Test scaling under load

Deliverables:

  • HPA configuration for API and workers
  • Custom metric definitions
  • Scaling policies and thresholds
  • Monitoring and alerting for scaling events
  • Documentation for scaling configuration
  • Load testing to verify scaling behavior

Contributor guide

Research direction
Learn Kubernetes Horizontal Pod Autoscaling (HPA) with custom metrics, RabbitMQ worker scaling, and load testing tools. Then implement HPA for API and workers, define custom metrics (e.g., RabbitMQ queue length), and configure monitoring with Prometheus.
Tech stack
dockerkubernetesprometheus
Domain
devopsinfrastructure
Issue type
DevOps
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
KubernetesDockerRabbitMQ
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20