What is the rollback strategy for Rate limiting in k8s?

When implementing rate limiting in Kubernetes, a rollback strategy is essential to ensure that any issues arising from configuration changes can be quickly addressed. Rate limiting can help protect APIs from being overwhelmed, but if incorrectly configured, it can lead to service disruptions. Below, we outline a rollback strategy along with an example implementation.

Rollback Strategy for Rate Limiting

  1. Version Control: Use version control for your configuration files, such as ConfigMaps or Custom Resource Definitions (CRDs) that manage your rate limiting settings.
  2. Automated Backups: Before applying new rate limiting rules, create a backup of the current configuration that can be easily restored.
  3. Testing: Implement changes in a staging environment first to identify any issues before applying them to production.
  4. Monitoring: Set up monitoring tools to immediately alert you to any issues that occur after the deployment of new rate limiting settings.
  5. Quick Rollback: Establish a clear process for rolling back to the last known good configuration, which could be automated through CI/CD pipelines.

Example Configuration and Rollback Code

apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: my-ingress spec: rules: - host: myapi.example.com http: paths: - path: / pathType: Prefix backend: service: name: my-service port: number: 80 annotations: nginx.ingress.kubernetes.io/limit-connections: "1" nginx.ingress.kubernetes.io/limit-rpm: "30" nginx.ingress.kubernetes.io/limit-rps: "10"

rollback strategy rate limiting k8s Kubernetes configuration service disruptions

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