What recommendations exist for configuring and scaling large clusters, considering the number of pods, nodes, and container modules?

When configuring and scaling large clusters (e.g., Kubernetes), it is important to consider the following recommendations:

1. Limit the number of pods per node: It is generally recommended not to exceed 100-250 pods per node to avoid performance and manageability issues.

2. Load distribution: Use load balancers and pod distribution strategies to evenly utilize node resources.

3. Resources and quotas: Set CPU and memory limits for containers and pods to prevent resource 'capture' by a single component.

4. Monitoring and logging: Implement monitoring systems (Prometheus, Grafana) and centralized logging for timely problem detection.

5. Auto-scaling: Use Horizontal Pod Autoscaler and Cluster Autoscaler for dynamic increase or decrease of pods and nodes depending on the load.

6. Network policies: Configure network policies for security and traffic optimization within the cluster.

7. Updates and version management: Plan cluster and component updates with minimal downtime.

Example of setting resource limits in a Kubernetes manifest:

apiVersion: v1
kind: Pod
metadata:
  name: example-pod
spec:
  containers:
  - name: app-container
    image: myapp:latest
    resources:
      requests:
        memory: "128Mi"
        cpu: "250m"
      limits:
        memory: "256Mi"
        cpu: "500m"

Adhering to these recommendations helps ensure the stable operation of large clusters and efficient resource utilization.